In 1996 麻豆原创 held its first event for developers. Thirty years later in Berlin, 麻豆原创 CTO Philipp Herzig told the 麻豆原创 TechEd keynote audience, 鈥淲e are experiencing the biggest and fastest technological shift in our lifetime.鈥�

鈥淔or decades developers have been building systems in a structured, deterministic way. But the world for builders has changed tremendously with AI,鈥� he said. 鈥淚t changes what’s possible. This is what 麻豆原创 TechEd is all about: combining both classical and new technologies that unlock the magic for business and provide endless opportunities to innovate.鈥�

From vision to execution

Underscoring his point, Herzig noted that during the 麻豆原创 Sapphire conference earlier this year, the company 鈥減ut out a bold vision to enable the Autonomous Enterprise, re-imagining every business process end-to-end with AI. And just like 30 years ago, the whole tech stack is shifting.鈥�

For 麻豆原创, this is reflected in Joule Work and the new 麻豆原创 Business AI Platform. Herzig described Joule Work as a 鈥済roundbreaking new way to experience software鈥� that taps into 麻豆原创鈥檚 five autonomous domains and assistants that reason and act across 麻豆原创 and non-麻豆原创 data, and 麻豆原创 Business AI Platform as 鈥渢he foundation where you build and extend agents, manage all your data, and govern AI experiences.鈥�

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Designed for better business outcomes

Elaborating, he emphasized that 麻豆原创 Business AI Platform 鈥渋sn鈥檛 just another tech platform, it鈥檚 specifically designed to build better business outcomes, deliver faster time-to-value and better price performance.鈥� In addition, it is enterprise-readiness from day one: secure, governed, and compliant, 鈥渁ll made possible through our unique context layer built on 50 years of domain and industry expertise.鈥�

Together, Joule Work and 麻豆原创 Business AI Platform underpin 麻豆原创鈥檚 commitment to build the Autonomous Enterprise. 鈥淎nd it鈥檚 here today,鈥� Herzig told the audience. 鈥淲e are excited to show you our latest updates at 麻豆原创 TechEd.鈥�

For the rest of the keynote, Herzig and his 麻豆原创 colleagues鈥攊ncluding 麻豆原创 Chief AI Officer Jonathan von Rueden; Manoj Swaminathan, president and chief product officer for 麻豆原创 Autonomous Suite; Tina Berlin, head of AI Foundation EU at 麻豆原创; Michelle Niedernhuber, lead product manager for 麻豆原创 AI Agent Hub; and Soeren Ruder, chief product officer and global head of Customer Experience & Solutions鈥攄etailed these updates and demonstrated them on stage.

Joule Work

Beginning with Joule Work, Herzig said 麻豆原创 had re-designed the user experience from the ground up: 鈥淎ll to make it more delightful and intuitive to use than ever. One starting point. One experience.鈥�

Joule Work now connects all 麻豆原创 applications as well as Office365, Claude Cowork, Glean, and ServiceNow out of the box. It remembers preferences and context from past interactions and continuously adapts. In addition to the conversational interface, shareable spaces that dynamically assemble data into interactive applications are also available.

The keynote speakers described Joule Work as a redesigned, cross-application AI experience available everywhere, including web, desktop, mobile, voice, and even Apple CarPlay. And they noted that Joule Work has been tested for months by more than 110,000 麻豆原创 employees, along with more than 150 customers, who joined the 麻豆原创 Early Adopter Care program, 鈥渁ll so you get the best AI experience.鈥�

One early adopter, Robert Mueller from Bosch Digital, joined Herzig on stage and said his teams had been testing Joule Work, Joule Studio, and the first assistants and agents and that the first user feedback had been positive. 鈥淥ur next step is to bring Joule into daily use,鈥� he said.

麻豆原创 Autonomous Suite

Manoj Swaminathan then took the stage to demonstrate the 麻豆原创 Autonomous Suite. 鈥淔or over five decades, 麻豆原创 has built the systems that help you run your business in the best way possible. Continuing that focus, we now deliver out-of-the-box a suite of 麻豆原创-managed assistants and agents across five horizontal domains, with industry specialization.鈥�

鈥淚鈥檓 excited to announce today 40 assistants and 300 agents between 麻豆原创 and our partners for you to explore,鈥� he added. 鈥淭hese give you a baseline for systems of intelligence and systems of action, built around three priorities, delivering: automation, intelligence and insights, and optimizations, with value that can be realized and measured, across reduction in cost, increased productivity, increased speed, improved quality, and more.鈥�

The new assistants include a Financial Consolidation Assistant that can reduce the time to close the books by up to 68%, a Sourcing Assistant that can reduce total cost of ownership by 15%, and a Supplier Management Assistant that detects and responds to supplier risk 60% faster.

鈥淔or these tasks, an answer that is 鈥榩robable鈥� is just not good enough,鈥� Swaminathan said. 鈥淵ou need the right answer, every single time, and they need to be compliant and traceable. That is what these assistants and agents uniquely enable, because every single one of these agents are ISO and SOC compliant.鈥�

麻豆原创 Business AI Platform

He noted that every agent is natively an Agent to Agent (A2A) endpoint, connected through 麻豆原创鈥檚 A2A gateway, and the platform supports extensions by default. 鈥淔or you as a builder, we鈥檝e made available the 麻豆原创 Business AI Platform, the foundation the 麻豆原创 Autonomous Suite is built on, so you can build to whatever your requirements are in Joule Studio.鈥�

鈥淵ou might ask, 鈥業’m already doing this with support from public models, why build on top of 麻豆原创鈥檚 Business AI Platform?鈥� Because a public model does not know your processes, your master data or your company. 麻豆原创 Business AI Platform does,鈥� Swaminathan shared. 鈥淥ur AI agents are embedded in the deterministic workflows of our applications. They deliver the one true answer as they run on the same data, following the same rules, and leave the same audit trail as our applications and you decide the level of autonomy.鈥�

But he pointed out that the 麻豆原创 Autonomous Suite does not restrict itself to only back-office operations. 鈥淥ur biggest customers are losing 11% of revenue to unplanned downtime experiences with on-site operations. Customers understand the problem but there hasn’t been a solution that responds to these challenges until now.鈥�

Physical AI by 麻豆原创

To address this issue, Swaminathan announced physical AI by 麻豆原创, which extends the Autonomous Enterprise into the physical world, turning business decisions into physical action, and bringing verified outcomes back into 麻豆原创 in a secure and governed way.

During an on-stage appearance, Ricky Watts, who runs the Industrial and Robotics Division of Intel, said the company is already running physical AI at its operational site in Chengdu, where 麻豆原创 warehouse management is driving autonomous robots closing the loop, writing outcomes back into 麻豆原创 as live transactions.

Jonathan von Rueden then took over the keynote stage to talk about the more than 300 standard Joule agents across the suite and how Joule Work and skills can adapt and customize standard agents to get the most from AI. If you want to go further still, he said, 鈥淛oule Studio is just one click away.鈥�

Joule Studio: Extend, build, and integrate your agents

Joule Studio, 麻豆原创’s agent-building platform, lets anyone customize AI with a skill: a natural language description and a few lines of code defining what an agent should do, opening agent-building beyond developers.

If you want to go deeper, and need to know where to begin, the Process Consulting Agent identifies where and what to build before development begins. “Just say what you want to get it done,” said von Rueden. 麻豆原创 Knowledge Graph finds the relevant APIs, MCP servers, and data products, and Joule Studio generates the specifications, structure, and integration logic.

The result: Moving from intent to a working agent takes roughly 2.5 hours instead of 13. Because agents don’t need to guess at requests, they use fewer tokens. “In our testing, that adds up to 50% lower cost per task,” von Rueden told the audience.

“With Joule Studio on 麻豆原创 Business AI platform, we focus on four things: business outcomes, time to value, performance for price, and enterprise readiness with deep integration.”

That last point matters in complex landscapes. With dozens of platforms, data sources, and tools running alongside 麻豆原创 systems, agents need to work across those boundaries safely and with governance, without a custom integration for every new platform.

“You’d expect a certain level of out-of-the-box capabilities and we’ve delivered,” Tina Berlin said. Agent gateway is generally available today, connecting agents and endpoints across any landscape boundary.鈥�

For more complex scenarios requiring rate limiting, routing, protocol translation, and advanced access control, 麻豆原创 is announcing 麻豆原创 Enterprise AI Gateway, built on 麻豆原创 Integration Suite as a natural overlay to agent gateway.

Herzig then returned to the stage to underscore the importance of reliable data for business AI. “Any AI system is only as good as the data it reasons over,” he said, “data that lives in different physical systems, be it 麻豆原创 or non-麻豆原创, on clouds, on-premise, and the edge.”

麻豆原创 Business Data Cloud

鈥淪o how do you bring it together in a consistent, AI-ready way?鈥� The answer, Herzig said, is 麻豆原创 Business Data Cloud, which provides customers with universal business context across their entire multi-cloud landscape. 鈥淎nd thousands of customers are benefitting from the outcomes, time to value, and lower cost already today.鈥�

In addition, he announced that the full scope of the entire Databricks platform will now be available natively in 麻豆原创 Business Data Cloud. This means that data from different systems can now be combined into a 鈥済olden鈥� master record, providing customers with a unified, AI-ready data foundation.

麻豆原创 executives also introduced a new 麻豆原创 Business Data Cloud Ontology Manager, available as beta. With it, customers can enrich 麻豆原创 Knowledge Graph with their industry-specific concepts or build entire ontologies.

A new Governance Assistant ensures compliance with EU regulation, while agent observability, and 麻豆原创 Signavio agent mining close the loop between agent design and production behavior to deliver governance. Runtime verification enforcement ensures that agents not verified in 麻豆原创 AI Agent Hub cannot be invoked.

Governance

All of it is 麻豆原创-managed with governance built in: ISO and SOC compliant, runtime enforced, with every agent testable and traceable via 麻豆原创 AI Agent Hub. And the new 麻豆原创 Enterprise AI Gateway delivers policy enforcement, enhanced observability, and runtime controls all in one place.

鈥淔or AI governance we need to connect the design time layer where we define, assess and verify an agent with the runtime layer that enforces, monitors and optimizes agent behavior,鈥� Michelle Niedernhuber said.

With the EU AI Act now in force, 麻豆原创 is releasing the AI Governance Assistant for the 麻豆原创 Early Adopter Care program customers in November, she shared. The assistant uses existing information, guides the agent owner through the remaining questions, and produces an audit-ready AI risk classification.

Together, 麻豆原创 AI Agent Hub and 麻豆原创 Enterprise AI Gateway serve as the design and runtime integration layer that connects oversight with enforcement. By connecting oversight, runtime enforcement, and continuous improvement, 麻豆原创 gives enterprises confidence that their agents operate as intended.

鈥淕overnance is not what slows AI adoption,鈥� Niedernhuber noted. 鈥淚t is what makes AI adoption at scale possible.鈥�

AI proven under pressure: 麻豆原创 brings AI to space

Rounding out the keynote, Herzig announced that together with partner Hewlett Packard Enterprise (HPE), 鈥溌槎乖� is taking our tabular foundation models, 麻豆原创-RPT and TabPFN, for real-time predictions in space to put AI to work under extreme conditions.鈥�

In space, a delayed decision can mean the difference between system safety and total loss. 麻豆原创’s AI enables faster decision-making and earlier failure prediction, when the stakes are highest.

Herzig explained how the foundation models analyze live hardware telemetry, identify sensor degradation, and reconstruct missing readings in real time. The outcome is a structured report recommending actions to the spaceship crew or ground staff on what to do to prevent a problem from becoming a crisis.

鈥淣ow, if we can run predictions like this in one of the most unforgiving environments, think about what this means for your operations here on Earth. That鈥檚 AI proven under pressure,鈥� Herzig said, bringing the keynote to a close.

鈥淚t’s time to show you the Autonomous Enterprise in action underpinned by great customer stories,鈥� 麻豆原创 CEO Christian Klein told his keynote audience at the start of the event.  

Klein reminded the audience that 麻豆原创 introduced the Autonomous Enterprise at its 麻豆原创 Sapphire conference in May 2026 as 鈥渢he beginning of better.鈥� Since then, he said, 麻豆原创 has worked with hundreds of customers to implement Joule Work as the AI engagement layer for the Autonomous Enterprise. 

A new UI for AI 

鈥淭his month, we are rolling out Joule Work for all customers,鈥� Klein said, describing it as a new UI for AI. He noted that for decades, users had to learn how 麻豆原创 worked, but with Joule Work, 麻豆原创 learns how people work. 鈥淔rom now on, the more than 400 million 麻豆原创 users can talk in their own language to 麻豆原创, and Joule Work gets the job done.鈥� 

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Klein explained that Joule Work is based on three pillars: conversations, where users ask questions and delegate tasks to agents; spaces, which display content, insights, and shared work; and Joule Studio, where customers extend Joule or build agents tailored to their own processes.   

He called 麻豆原创鈥檚 deep business and data context its 鈥渟ecret sauce.鈥� That context includes 麻豆原创 Knowledge Graph, which maps more than 7 million data fields, 50 million tables, more than 50,000 public and private APIs, 400 data products, and extensive process knowledge. 鈥淭hat’s why Joule doesn’t guess,鈥� he said. 

麻豆原创鈥檚 110,000 employees are already using Joule to perform hundreds of thousands of tasks every day, he shared: 鈥淲e are already seeing productivity gains in central functions like HR, finance, and procurement of over 20% and even bigger gains in more complex analytical and planning tasks.鈥� 

麻豆原创 Autonomous Suite 

Klein then turned his attention to the 麻豆原创 Autonomous Suite, the second layer in the Autonomous Enterprise. The suite initially covers five domains: finance, procurement, supply chain, human resources, and customer experience. 麻豆原创 Autonomous Suite is designed for work where a good answer is insufficient and 鈥渢he right answer鈥� is required every time, he said.  

鈥淟LMs are probabilistic and only give you the most likely answer,鈥� Klein said. He contrasted that probabilistic approach with 麻豆原创’s embedded agents. Because the agents operate within deterministic application workflows, they use the same data, follow the same rules, and leave the same audit trail as the applications themselves. Customers can choose the level of autonomy appropriate to each process, retaining human approval where risk is high and allowing greater automation for routine work. 

Since 麻豆原创 Sapphire, Klein said 麻豆原创 has created more than 20 Joule Assistants and over 200 Joule Agents, and is aiming for more than 400 agents by year-end. 鈥淏ut the real story isn鈥檛 the number of agents. It鈥檚 the business outcomes they deliver,鈥� he said. 

麻豆原创 Business AI Platform 

鈥淭hese agents can only understand your business so well because of the 麻豆原创 Business AI Platform,鈥� Klein said. 鈥淭he platform gives customers the best frontier model for every agentic use case, the deepest out-of-the-box business context and 麻豆原创-managed governance.鈥�  

Building on Klein鈥檚 remarks, Manoj Swaminathan, president and chief product officer of 麻豆原创 Autonomous Suite, described the 麻豆原创 Business AI Platform as the infrastructure that enables the Autonomous Enterprise. The platform is organized around three capabilities: building agents, contextualizing them with business data, and governing how they operate. 

Swaminathan explained how the context layer makes agents more accurate. Joule Studio spans no-code and professional development and offers access to more than 70 models, a strategy he said reduces lock-in and controls token costs.  

鈥淛oule Studio is natively integrated with our context layer,鈥� he said. 鈥淪o, the agents you build are more accurate, faster to deploy, and more efficient to run. Our knowledge graph is the map with the processes, data flows, and business tools. The agents find the right processes among thousands and the right information among over 7 million feeds. 麻豆原创 Business Data Cloud brings that understanding to all your data, one consistent view, the processes, policies, and logic to make it meaningful.鈥� 

Swaminathan said no AI can compensate for a broken data model. To help agents understand customers鈥� business rules, 麻豆原创 Domain Models are trained on 麻豆原创鈥檚 code. For predictions, 麻豆原创 provides two engines grounded in how a customer’s business operates: 麻豆原创-RPT, 麻豆原创’s model family trained on its business data, and the Prior Labs tabular AI model.

Jerseys from Jersey 

During his section of the keynote, Jan Gilg, global president of Customer Success & Americas, used an imaginary startup 鈥� 鈥淛erseys from Jersey鈥� 鈥� to invite a handful of customers to the stage to answer his questions and validate aspects of 麻豆原创鈥檚 Autonomous Enterprise strategy.  

The customers included Novartis, which is piloting Joule sourcing agents for bid analysis and negotiation support; Morgan Foods, which described a supply-chain transformation built on 麻豆原创 S/4HANA and 麻豆原创 Integrated Business Planning; Nestl茅, which emphasized the importance of a unified digital core; and 麻豆原创 customer and partner PwC, which spoke about the value of the Industry AI portfolio from 麻豆原创. 

Summing up their comments, Gilg noted that the elements of the 麻豆原创 Autonomous Suite 鈥渁re more than a collection of functional components. It鈥檚 one system working together like connective tissue that provides connectivity, context, and control.鈥�

Gilg also made several product announcements, including the launch of 麻豆原创 Pay, an embedded payments service that can automatically execute and reconcile supplier payments once an invoice is approved. He also announced 麻豆原创鈥檚 planned acquisition of TechWolf, a Belgian workforce-intelligence startup designed to help close skills gaps. 

Security and governance 

In the closing section of the keynote, 麻豆原创 Chief Security Officer Marielle Ehrmann focused on trust and governance. She noted that ransomware handovers that once took eight hours now take 22 seconds with AI, and while 83% of enterprises use AI daily, only 13% have real visibility into it.  

鈥淭he biggest threat to companies is not malicious AI; it鈥檚 unmanaged AI,鈥� Ehrmann said. To counter that threat, she said every agent should have a verified owner, a risk tier, and scoped access rights, supported by zero-trust checks on identity, purpose, and data sensitivity as well as human oversight. 

She emphasized that 麻豆原创 Business AI Platform incorporates regulatory and localization requirements, applies user authorizations, keeps customer data from being used to train foundation models, and supports three levels of oversight: human-in-the-loop approval, human-on-the-loop monitoring, and human-in-command override authority. 鈥淭he more autonomously an agent operates, the tighter the oversight applied,鈥� Ehrmann said, calling the principle 鈥渇reedom within boundaries.鈥� 

A clear shift among customers 

Wrapping up the keynote, Klein emphasized that trust is key to everything 麻豆原创 does and has been for over 50 years. 鈥淲e are delivering the most trusted and governed AI in the industry,鈥� he said, but added, 鈥淎I also requires significant change management to ensure it delivers the desired outcomes for your business.鈥� 

That is where 麻豆原创鈥檚 business transformation solutions come in, he said. 麻豆原创 Signavio measures process value before and after a change to help justify token spending; 麻豆原创 LeanIX discovers and tracks AI agents; and 麻豆原创 WalkMe supports user adoption and trust. Klein also highlighted an agent-led migration toolchain. Together, he said, these capabilities mean that the days of multi-million-dollar migration spend are gone.

鈥淭his is no longer the start of something better. This is better,鈥� Klein told the audience. He described a clear shift among 麻豆原创 customers: 鈥淔rom manual steps to connected workflows, from reactive decision-making to predictive insights, from humans in spreadsheets to humans in and on the loop–all powered by our AI platform to keep AI accurate, governed, and extensible.鈥�

And, most importantly, Klein said, 鈥淚ts ready for you today鈥� This is the Autonomous Enterprise.鈥� 

His dream led to the founding of Colombina and听to听a colorful corporate logo inspired by a character from an Italian opera who swung on the moon.听In听the 1960s,听his son, Don Jaime H.听Caicedo,听took over the company and drove a major transformation,听diversifying its offerings and听expanding听sales abroad.

Expansion 

That early spirit of reinvention has continued to shape Colombina鈥檚 growth, turning a family-founded confectionery business into a diversified food company with international reach.听Today, Colombina is a听multinational听leader in food production with a portfolio of 19 categories, including confectionery,听cookies,听chocolate,听sauces,听preserves,听ice cream, and coffee, along with a global workforce of more than听8,000.听听

From seven processing plants听and听39 distribution centers in Colombia, Venezuela, Central America,听and the U.S., Colombina serves听750,000 customers听in听more than听90 countries worldwide and generates annual sales of almost听US$1 billion.听

But with a global footprint spanning manufacturing, distribution, and retail, the company had to continually review and adapt specialized technology solutions for each market segment.  

Colombina鈥檚 leadership recognized that this fragmented approach made it difficult to ensure the听integrity, availability, and confidentiality听of business information at scale,听and that the company听needed听to听standardize听processes across dozens of markets while continuing to grow sales and manage costs.听

IT priorities 

Colombina听identified听key areas in need of standardization, particularly finance and supply chain management, and recognized that a鈥痷nified technology foundation鈥痺as critical to sustaining growth and operational efficiency.鈥� Security鈥痑lso听emerged听as a top priority, shaping many of the technology decisions that would follow.听

To address these challenges,听it embarked on a major transformation led听by CIO Jes煤s Brand, a long-time ASUG Colombia chapter president and respected figure across the region. Colombina鈥檚 objective was to effectively use data to achieve its business goals faster and with less risk.听

By moving to the cloud, Colombina was seeking to streamline product planning, manufacturing operations and models, and quality management processes. It also focused on simplifying supply chain tasks, including inventory, warehousing, delivery and transportation, order promising, and logistics material identification.  

RISE with 麻豆原创 

A long-term 麻豆原创 customer, Colombina signed up for RISE with 麻豆原创,听migrating from 麻豆原创 ERP Central Component to 麻豆原创 S/4HANA Cloud Private听Edition in a full, simultaneous migration听executed across听16 countries.听The solution听covers key business functions听including finance, asset management, manufacturing, supply chain, and sales, but the company went a step further.听

To听harmonize its operational data, Colombina integrated its cloud ERP with a broad ecosystem of 麻豆原创 solutions, including听麻豆原创 Fiori, 麻豆原创 SuccessFactors, 麻豆原创 Integrated Business Planning,听麻豆原创 Analytics Cloud, and听麻豆原创 Ariba,听among others.听听

At the same time, John Carlos Jaramillo, an IT project manager at Colombina for over 20 years, noted that governance and security were strengthened through 麻豆原创 Cloud Application Services, which helps run, manage, and continuously optimize the company鈥檚 expanded 麻豆原创 landscape.听

Jaramillo also highlighted the value derived from engaging with the 麻豆原创 Enterprise Architect, particularly through strategic advisory and guidance on adoption opportunities. He emphasized the benefit of gaining a clearer understanding of the contractual entitlements available to the organization, enabling more effective听utilization听of existing 麻豆原创听investments听and maximizing the value of their licensed capabilities.听

He also听highlighted the听guidance provided around key strategic initiatives, including clean core, helping drive a sustainable and extensible ERP landscape; 麻豆原创 Cloud ALM, enabling stronger operational visibility and application life cycle management practices; and Joule Base, supporting the exploration of AI-driven capabilities and accelerating the organization’s journey toward business innovation and increased user productivity.听

Security benefits 

Among the overall security benefits, the new system provides听protection听at different layers, including the operating system, applications,听and听users, while delivering听low downtime and quick, thorough resolutions. Before implementation,听system downtime was a significant issue for Colombina;听now,听with double the number of application servers,听downtime has been听reduced听and most customer issues can be resolved within 45 minutes.听

Colombina鈥檚 IT team also reports high confidence when looking ahead to updates, with reduced concerns thanks to predictable update windows that typically take place at the weekend. In addition, the new system provides early watch alerts, enabling the IT team to get in front of potential risks on a day-to-day basis. 麻豆原创 for Me helps monitor and maintain the flow of these activities and gives a clear view of current infrastructure, operating system, activities, and risk profiles. 

Tangible results 

The impact has been tangible: Colombina now offers next-day delivery and has improved average customer response times by more than a third. Workload distribution has improved dramatically, while the business has seen fewer customer returns, stronger demand planning, and more efficient HR management. 

But the company is not stopping there. Having introduced听Joule听for 麻豆原创 SuccessFactors, Colombina is听preparing听to听activate听Joule Agents across its business and is implementing 麻豆原创听Databricks for data models,听working with 麻豆原创听Business Data Cloud听to build the right data foundation听for future听AI capabilities.听

It鈥檚 about making consequential decisions inside complex processes that require a deep industry specific context of data, regulations, human workflows, and processes.

For example, tasks like deploying and coordinating thousands of field technicians to restore energy grids after a storm and reduce unplanned downtimes or like keeping critically important production lines running and service levels high despite global supply chain disruptions involve many difficult decisions.

“These problems are incredibly hard to solve,” says Dominik Metzger, president of Industry AI at 麻豆原创, because solving them demands immense organizational change, especially in highly regulated industries.

Frontier LLMs are not enough

There is a growing realization among business leaders that solving these challenges requires more than just a powerful AI language model. In these situations, AI must do more than generate suggestions. It needs to act on insights and context to support the execution of business processes. This requires agentic AI that can work with trusted business data, apply industry-specific knowledge, and take actions in ways that are reliable, explainable, and useful to the people closest to the work.

AI is most valuable when it understands the context in which decisions are made. Manufacturers need to balance demand, production capacity, supplier risk, and quality requirements. Energy companies need to manage assets, safety, sustainability, and regulatory obligations. Life sciences companies need to innovate while meeting strict compliance expectations.

To help solve the most complex problems facing large enterprise customers, 麻豆原创 is bringing together 50 years of deep industry听expertise, leading AI engineering know-how, and customer-facing forward-deployed delivery capabilities in one organization听to combine forward-deployed engineering with strong productization capabilities.

This enables 麻豆原创 to move beyond custom AI solutions and build, productize, and scale end-to-end AI transformations for industry-specific business problems.

Think of it this way: the Autonomous Enterprise is 麻豆原创鈥檚 strategic direction, 麻豆原创 Business AI Platform is its foundation, and Industry AI acts as a highly focused customer transformation offering, solving industry-specific challenges for individual customers to generate substantial business value.

What makes Industry AI different

The Industry AI portfolio is built on three differentiators: first, more than 50 years of 麻豆原创鈥檚 industry and process expertise across 26 industries; second, the richness of 麻豆原创 customers’ data footprint and ontologies in an existing system of record; and third, a dedicated forward-deployed engineering (FDE) workforce to solve problems that do not have off-the-shelf answers, customer by customer.

Forward-deployed engineering embeds AI specialists, such as data scientists and AI builders, directly with customers to solve high-value, industry-specific problems, rather than relying solely on packaged software. Metzger explains that forward-deployed engineering involves 鈥済etting obsessed with the problems of our customers鈥� and immersing 麻豆原创鈥檚 agentic AI developers in the challenges these customers face. 鈥淲orking directly with customers, we will build, deploy, and scale Industry AI applications to deliver tangible business value for our customers,鈥� he says.

Lessons learned by building these tailored solutions with selected customers will be productized as a standardized platform offering for many more customers to deploy and use. This model allows fast scaling and delivery, while also building up 麻豆原创鈥檚 platform and solution portfolio of high-value agentic solutions that are close to customer needs and current industry priorities.

Getting up close with customers

麻豆原创鈥檚 decision to establish Industry AI as a focused business offering reflects the conviction that true value from agentic AI is created in close collaboration with the industry experts who face specific business challenges every day. This proximity is the fastest way to identify the most critical problems, develop and test practical AI solutions, and refine them based on real-world experience. Most importantly, it allows to deliver tangible business value and prove the impact of AI in practice.

This approach helps reduce the gap between a promising idea and a solution. On the one hand, teams can move more quickly from identifying a need to deploying a solution that delivers measurable value. It also ensures that what is built reflects real-world needs rather than assumptions made far from the customer environment.

For 麻豆原创鈥檚 enterprise customers, the promise of the Industry AI offering is not simply smarter software. It is a more practical path to the Autonomous Enterprise. Instead of asking teams to adapt to generic tools, Industry AI can help bring deep intelligence into the processes people already use and the decisions they already make, while staying connected to the business data, controls, and applications that keep organizations running.

Benefits

Examples of these benefits are easy to describe. An energy provider avoids costly downtime by identifying a likely spare part demand early and recommending relevant suppliers. A retailer adjusts inventory positions and trade promotions based on simulated scenarios and real demand signals before stockouts occur. A pharmaceutical manufacturer ensures the safe and reliable release of life-saving drugs through a highly precise, high-quality, and fully automated batch release process.

That matters because it can help organizations move faster, improve quality, and free employees to focus on higher-value work. It can also help companies turn industry knowledge into a lasting advantage, especially as AI becomes a larger part of how businesses operate.

For 麻豆原创, the formation of the Industry AI unit represents a strategic leap, combining industry-specific expertise, end-to-end offerings, and a value-based offering in a way that is clearly designed to differentiate 麻豆原创 from competitors.

麻豆原创鈥檚 differentiation from other AI platform providers and more traditional forward-deployed engineering companies is not simply about providing custom AI services: the focus is on turning industry-specific expertise into scalable, repeatable offerings that can be deployed across customers, creating a more sustainable and differentiated model for delivering AI value.

Specifically, the Industry AI offering is positioned as an all-in-one commercial package, including platform consumption and cloud services, solutions, forward-deployed engineering, and expert support, with pricing based on real customer business value and a single contract.

It is based on 麻豆原创鈥檚 unique deep industry-specific knowledge, business AI platform, and knowledge graph, enabling tailored processes for customers. In addition, 麻豆原创鈥檚 approach is grounded in customers鈥� business logic, decades of experience and enterprise grade governance, all implemented in standard products, differentiating it from some recently announced market offerings.

What comes next

As the World Economic Forum has highlighted, successful AI scaling depends not only on the technology itself, but also on practical changes to how people work, how decisions are made, and how organizations govern new capabilities.

麻豆原创 solves industry problems that generic AI鈥攅ven if super powerful鈥攃annot. Ultimately it is about enterprise and business process transformation, not AI deployment only. This then can redefine how AI transforms industries, by moving beyond isolated use cases toward autonomous, end-to-end agentic execution.

Agentic AI builds on the economic potential of generative AI, which McKinsey has estimated could add US$2.6 to $4.4 trillion annually to the world economy. This represents the next stage of enterprise AI adoption: a shift from content generation to autonomous execution, and from isolated pilots to operational deployments.

Agent sprawl

That shift creates a new governance challenge. Agent sprawl occurs when AI agents are created, deployed, or connected across systems faster than the enterprise can inventory them, assign ownership, control permissions, monitor behavior, and optimize or retire them when they are no longer fit for purpose.

Underscoring this shift, found that 98% of companies have already deployed AI agents or plan to do so. But as adoption accelerates, governance is struggling to keep pace. According to the same report, less than half of the organizations surveyed have visibility into an inventory of AI agents.

The mechanics of agent sprawl are familiar to any technology leader who has navigated a wave of SaaS adoption. Individual teams, motivated by genuine productivity goals, deploy agents independently. Each one is designed for a specific task鈥攁 marketing automation agent, a supply chain monitoring agent, an HR onboarding bot鈥攁nd each works in isolation. Without a centralized platform or governance framework, the organization accumulates a fragmented landscape of agents that do not interoperate, cannot be audited consistently, and accumulate technical debt faster than they generate value.

, the average global Fortune 500 enterprise will have more than 150,000 AI agents in use, yet only 13% of organizations believe they have the right governance in place to manage those agents. Max Goss, senior director analyst at Gartner, told his audience at a London conference in April: 鈥淎s CIOs and IT leaders see an explosion of AI agents across their organizations, many are contending with an ungoverned sprawl of agents that expose their organizations to a range of risks, including misinformation, oversharing, and data loss.鈥�

He added: 鈥淢any organizations resort to blocking or restricting the use of AI agents, but this is not a long-term solution. If employees are unable to work in the sanctioned tools, they will likely go around the organization鈥檚 controls and start using shadow AI, which presents far greater risks. Organizations need to find a balance where they can govern agents and manage sprawl, but also safely empower employees to innovate with these tools.鈥�

Agents typically need broad, cross-environment permissions to function, but those permissions are rarely governed with the same rigor applied to human users. The risk posed by unmanaged or rogue AI agents in the enterprise is therefore real and growing.

AI agent security concerns

Publicly reported enterprise-security examples also point to agents leaking sensitive information or acting outside their intended scope, including cases where malicious instructions caused agents to bypass guardrails, delete production records, or trigger irreversible financial transactions.

The security concern is what registers most sharply with enterprise technology leaders. With chatbots and early generative AI, a security failure typically meant bad output: an inaccurate or inappropriate response that could usually be corrected after the fact. In the agentic era however, the consequences of an agent failure or security breach can be far more damaging because agents can take action, call tools, access systems, and initiate business processes.

That is why agent governance is no longer only an IT operations issue. It increasingly touches board-level concerns: risk ownership, regulatory exposure, data protection, auditability, operational resilience, and accountability for autonomous decisions.

The emerging AI governance platform

Leading organizations are beginning to treat agent governance not as a compliance overhead but as a strategic capability that determines whether AI investments compound as advantages or liabilities. As a result,  effective AI agent governance has quickly become a boardroom topic and is contributing to the emergence of a new platform category: the AI governance platform.

The category is still forming, but its purpose is becoming clear. Enterprises need a way to discover agents, understand what they do, control what they can access, verify whether they are compliant, and monitor how they behave in production.

麻豆原创 is one of the agentic AI pioneers in this emerging category. Through its 2023 acquisition of LeanIX, 麻豆原创 gained a foundation in enterprise architecture management. This has quickly become a recognized differentiator for 麻豆原创 AI Agent Hub鈥攑ositioning AI artifacts like agents, models, and MCP servers within the full architecture and business context of the organization.

麻豆原创 AI Agent Hub builds on this foundation as a command center for managing and governing AI agents and related AI assets across an enterprise, even when they come from different vendors and run on different systems.

As 麻豆原创 CTO Philipp Herzig explained on stage at this year’s 麻豆原创 Sapphire event, 麻豆原创 AI Agent Hub is intended to provide a governance layer of record for the enterprise agent ecosystem. 鈥淎gents are everywhere,鈥� he said. 鈥淪ome are great, some are not, and almost no one has a consistent picture鈥攏o central governance, no clear view of what each agent does, whether it adds value or whether it adheres to your policies.鈥�

He added: 鈥溌槎乖� AI Agent Hub changes that. One entry point and command center to discover, manage, and govern all AI agents, LLMs, and MCP servers in your landscape鈥攙endor-agnostic. [麻豆原创] AI Agent Hub allows you to discover all your agents in context: your landscape, your business processes. Once you have identified the right agents, you can control their risk and define architectural decisions or compliance rules.鈥�

A closing window

Given the pace of AI agent deployment, the window for implementing effective enterprise governance before a serious incident occurs is narrowing. For CIOs, CEOs, and company boards, the question is no longer whether to govern AI agents. It is whether governance gets designed into the architecture from the start or retrofitted after the first serious failure.

Organizations that treat agent governance as a strategic priority in 2026 will be better positioned to scale AI as a durable competitive advantage. Those that defer could spend 2027 cleaning up: in enterprise technology, the cost of speed without structure eventually gets paid. But with AI agents, the bill arrives faster鈥攁nd at greater scale鈥攖han anything that has come before.

AI infrastructure as strategic asset 

Although infrastructure ownership is just one element of digital sovereignty strategy, European politicians and policymakers have argued that without domestic data centers, Europe risks dependence on U.S. and Chinese providers for critical AI capabilities.

This concern is echoed by some industry leaders鈥攑articularly those in finance and regulated sectors鈥攚ho increasingly view AI infrastructure as a foundation of economic security. Specifically, they argue that sovereign data centers enable companies to comply with stringent European regulations on data protection and AI governance. They say that locally operated infrastructure ensures that data remains under European jurisdiction, reducing exposure to foreign legal regimes and enhancing trust among customers and regulators.

Security and compliance imperatives 

European leaders also frame AI infrastructure as a hedge against geopolitical risk. They argue that dependence on external providers introduces vulnerabilities, whether through legal exposure, supply chain disruptions, or political tensions.

As Christian Klein, CEO of 麻豆原创 SE, noted at the 麻豆原创 Sapphire Madrid event last month, many European customers operate in the public sector or other highly regulated industries. 鈥淕eopolitical risk is a growing concern,鈥� he said. 鈥淲hat if sanctions suddenly block data flows across borders? Or if the latest LLMs can鈥檛 be deployed in certain regions?鈥�

Christine Lagarde, president of the European Central Bank, also highlighted this concern in her November 2025 speech titled noting that Europe must 鈥渁void single points of failure鈥� in critical areas such as data centers and compute capacity.听听

Proponents of sovereign AI infrastructure also argue that it can stimulate broader economic growth. Data centers often anchor the ecosystems of startups, research institutions, and industrial applications, enabling Europe to capture more value from the AI stack.

From a technical standpoint, proximity also matters. Locally sited data centers reduce latency and improve performance for AI applications, particularly those requiring real-time processing or integration with industrial systems.

But despite these perceived advantages, many European business leaders have urged policymakers to take a more moderate, nuanced approach towards sovereign data. Their concerns are not about the need for data sovereignty itself, but about how it is implemented鈥攑articularly the push to rapidly build new, domestically controlled AI data centers. They emphasize that that data residency (location) is only one element of the four standard pillars of a sovereign data strategy, which also include legal sovereignty (jurisdictional control), operational sovereignty (independent operations), and technical sovereignty (data control).

In discussions with policymakers, European business leaders from diverse sectors have been warning that reducing reliance on U.S. technology too quickly is unrealistic. This reflects a structural reality: Europe remains deeply dependent on non-European providers for cloud infrastructure, chips, and AI platforms.

Research from Swiss cloud provider Proton suggests that around 75% of publicly listed European companies rely on U.S. tech services, (primarily Microsoft and Google) for critical infrastructure, including e-mail, cloud, and software. Therefore, attempting rapid substitution risks disrupting operations without delivering viable alternatives.

Barriers and concerns

Even the most ardent proponents of sovereign AI infrastructure acknowledge that there are major practical barriers to building massive AI data centers in Europe, including energy. AI data centers are extremely power-intensive, and Europe already faces grid constraints, high electricity prices, and long permitting timelines.

Without significant investment in energy systems, some European business leaders warn that new data center projects risk delays, cost overruns, or cancellation.

Another concern is that infrastructure-focused, sovereignty-driven policies may distort markets. Critics warn that infrastructure subsidies could flow to less competitive domestic providers resulting in slower innovation and the misallocation of capital resources to politically driven projects rather than economically viable ones.

In this view, sovereignty risks becoming industrial policy for its own sake, rather than a driver of efficiency or innovation. But perhaps the most significant critique is that the focus on infrastructure may distract from a more pressing issue: AI adoption.

Europe has historically lagged in deploying digital technologies. Some business leaders, including 麻豆原创鈥檚 Klein, argue that the priority should be accelerating AI use across industries and point out that infrastructure alone will not drive productivity gains. Over-emphasis on the infrastructure component of sovereignty could slow deployment through added complexity and cost. As Klein has noted, focusing primarily on infrastructure is a mistake if it is at the expense of developing AI applications and software.

Europe, he said recently, should prioritize 鈥渃ode over concrete.鈥� At the World Economic Forum in Davos earlier this year, senior executives from major European firms, including Capgemini and Ericsson, also warned against an overly protectionist approach. They argued that excluding or limiting global providers would raise prices, slow tech adoption, and reduce competitiveness.  

The business view 

From a business standpoint, AI is rapidly becoming a general-purpose technology, and the costs of AI infrastructure directly impacts productivity. If European AI infrastructure is more expensive, European companies risk falling behind global peers.

While data residency and the other elements of digital sovereignty are essential for some businesses operating in sensitive and highly regulated sectors, the sovereignty debate in Europe risks oversimplifying a fundamentally global industry. As Henna Virkkunen, the European Commission鈥檚 technology chief, noted: 鈥淣obody can be competitive alone.鈥�  

Indeed, since AI development depends on globally integrated supply chains, including semiconductors, software, and talent, fully localized infrastructure may be neither feasible nor desirable.

Rather than building duplicative infrastructure to support AI development, Europe鈥檚 real competitive advantage may lie in its treasure trove of operational data鈥攁 resource that is often difficult to access because of overly restrictive regulation and data access rules, prompting growing calls for reform from business leaders across Europe.

Easing and standardizing data access rules would help European businesses tap into this resource and compete more effectively with international rivals as they move into the next phase of AI enablement鈥攖he .

鈥淓very motorcycle we sell comes with an experience,鈥� he explains. 鈥淐ustomers come back to us for service, for spare parts, and for workshop support, so we truly connect each customer to a different kind of user experience, starting from the moment of purchase.鈥�

Many people in Colombia get around every day on motorcycles鈥攐ften on 鈥楤oxer鈥� motorcycles made by UMA, which aims to ensure riders feel safe on the road, Urrea Ospina says. To help achieve that, UMA has implemented rigorous quality processes that run on . 鈥淓very motorcycle leaving our factories follows best quality practices,鈥� he says. 鈥淎nd we pass that value onto our customers.鈥�

In addition to Colombia, UMA operates in five countries in Central America: Guatemala, El Salvador, Costa Rica, Honduras, and Nicaragua. 鈥淲e鈥檙e also in Venezuela, as well as Spain and Portugal,鈥� Urrea Ospina says. 鈥淎cross all these regions, we aim to make a positive impact on our customers with each of our brands and motorcycles.鈥�

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鈥淔or us, our 鈥楢dventure鈥� project鈥攖he name we gave the 麻豆原创 project鈥攚as crucial to our expansion and growth,鈥� he says. 鈥淲e needed global models so we could expand faster and run more efficient, automated operations.鈥�

Working with 麻豆原创, UMA established global models and automated operations across finance, production, and logistics, says Victor Bedoya Aristizabal, corporate solutions manager at Grupo UMA. 鈥淲e defined global models, starting in finance with global charts of accounts that let us analyze information and make financial decisions much more efficiently. From there, we extended the approach through production and plant operations and into logistics.鈥�

鈥淭oday, 麻豆原创 is a fundamental pillar for our processes from the start of the value chain to the end,鈥� Bedoya Aristizabal says. 鈥淲e utilize the full suite for production, pricing, finance, and warehouse management to deliver a superior product.鈥�

鈥淭aken together, these cross-cutting global modules have helped us evolve, save time, shorten implementations, and expand across regions,鈥� Urrea Ospina says. 鈥淔or example, in Colombia we鈥檙e implementing our spare parts warehouse with 麻豆原创 Extended Warehouse Management, 麻豆原创鈥檚 supply chain management application. What we鈥檙e learning in Colombia can be replicated in Central America. Standardizing these logistics modules makes operations much more efficient while still accounting for each country鈥檚 specific needs.鈥�

He adds: 鈥淚 believe that if we hadn鈥檛 prepared with 麻豆原创 and the technologies we have today, the strong growth we鈥檝e had in Colombia would have been far more difficult. For example, we went from assembling 11,000 motorcycles in January of last year to around 17,000 motorcycles per month today鈥攏early doubling our output. Without 麻豆原创鈥檚 well-defined structures, process controls, and automations that replaced a lot of manual work, it would be much harder to reach the 20,000 motorcycles per month we expect to achieve soon.鈥�

鈥淭hat ability to scale鈥攂oth assembly volume and sales volume鈥攈as been driven by the Adventure project and everything we implemented with 麻豆原创,鈥� he says. 鈥淚 think it has significantly improved employees鈥� day-to-day work. And that鈥檚 where we need to take the organization: toward a data-driven company that makes better decisions. Before we implemented Adventure, a person鈥檚 day-to-day was mostly operational work.鈥�

Urrea Ospina emphasizes that one of the main motivations UMA had for adopting 麻豆原创 Cloud ERP Private was to have concrete, real-time information鈥攆or example, knowing exactly the assembly cost of a motorcycle. 鈥淭hat is key for an organization,鈥� he says. 鈥淏eyond that, another need was to remove the manual work that all the company鈥檚 areas had, working and operating completely by hand.鈥�

Luis Orrego, production supervisor at Grupo UMA, agrees: 鈥淚nstead of having many Excel files open with multiple sheets and trying to reconcile everything, we now consolidate the data in one place. With 麻豆原创, all the sheets and reports I used to present are now available in a single view. I don鈥檛 have to run multiple steps, and I can see all my indicators: capacity, materials, and line resources.鈥�

Another motivation was UMA鈥檚 expansion plans to enter other regions and countries efficiently. 鈥淲e wanted defined global models that we could replicate quickly with 麻豆原创 in the regions where we operate,鈥� Urrea Ospina explains. 鈥淭hose factors led us to undertake the 麻豆原创 project, which has been a highly strategic and very successful initiative.鈥�

Implementing 麻豆原创 Cloud ERP Private has also had a profound impact on Urrea Ospina鈥檚 technology team. 鈥淚t completely changed our roles and what we focused on,鈥� he says. “We used to be a technology team focused on operations, not one that added value. Today, the technology team plays a strategic role. We have time to analyze where we鈥檙e going and what we can implement next for the business. Culturally, 麻豆原创 gave us confidence through information traceability, and it also gave us time to think. It opened the door to innovation鈥攅specially around analytics.鈥�

David Aguirre is a media production specialist on the Multimedia Team for 麻豆原创 News.
Rana Hamzakadi is deputy head of the Multimedia Team for 麻豆原创 News.

In his kickoff keynote at 麻豆原创 Sapphire Orlando, Florida, Klein and other 麻豆原创 Board members detailed how 麻豆原创 plans to bring agentic AI to the world’s most critical business workflows so that humans and AI can meet the accelerating demands of global business profitably, strategically, and safely.

鈥淭oday I鈥檓 super proud to launch our new 麻豆原创 Business AI Platform, which forms the basis for our vision of the future of business: the Autonomous Enterprise, where agents run the business and you can focus on what truly matters,鈥� Klein said.

Enterprise AI is at an inflection point, Klein told his 30,000-strong in-person and virtual keynote audience, and 麻豆原创 is in a unique position to deliver what customers need to turn their businesses into autonomous enterprises.

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The business AI imperative

Across industries, organizations are investing heavily in artificial intelligence, yet many still struggle to translate that investment into meaningful business value. At 麻豆原创 Sapphire, the message was clear: This isn鈥檛 a technology problem; it鈥檚 a context and execution problem.

While 80% accuracy may be sufficient for consumer AI applications, Klein said, 鈥淓ighty percent is just not good enough when you run the world鈥檚 most business-critical businesses. They [LLMs] should not guess; they should deliver accurate, compliant, and secure outcomes.鈥� 

Klein acknowledged that while adoption of AI has become near-universal, tangible business value remains elusive. Citing a recent Stanford AI survey, he noted that almost every company is now using AI, but seeing only limited return.

The reason, he argued, lies in a structural gap. Above the waterline of enterprise AI, LLMs continue to improve at tasks trained on publicly available data, while below it lies what enterprises truly need: AI that understands mission-critical business data, end-to-end processes, and operates within security, compliance, and governance frameworks.

ERP as the foundation for business AI

麻豆原创鈥檚 answer to this challenge begins with what Klein described as 鈥渢he brain of every company: its ERP system.鈥� For over 50 years, 麻豆原创 has had solutions with incredibly deep process and data domain know-how alongside the governance requirements, compliance controls, and company-specific configurations that define how businesses actually run.

Now, as part of the company鈥檚 new vision, 麻豆原创 plans to infuse this institutional knowledge into AI agents, enabling them to navigate thousands of business processes, select from more than 7 million data fields, and verify identity and access authorizations before returning any output.

鈥淲e鈥檙e bringing together LLMs with 50 years of business know-how stored in our ERP. But to do this, we had to do nothing less than completely reinvent our company,鈥� he told the audience. 鈥淭oday we are very excited to show you the new 麻豆原创 and our vision for the Autonomous Enterprise.鈥�

麻豆原创 Business AI Platform

To bring this vision to life, 麻豆原创 executives on stage announced a series of important innovations, beginning with the launch of the new 麻豆原创 Business AI Platform, a unified architecture bringing together 麻豆原创 Business Technology Platform, 麻豆原创 Business Data Cloud, and AI Foundation under a single roof.

鈥淭he heart of this new platform is the rich context layer,鈥� said Klein. 鈥淗ere, we infuse the deep ERP business domain know-how into the AI agents. Through our knowledge graphs, our AI agents have now a compass, a map, to find the right process and data in your ERP universe. And to provide the agents even more context, we are also introducing our new 麻豆原创 Domain Models. They have been trained on 麻豆原创’s code to even better understand the business logic of your company.鈥�

But, he said, 麻豆原创 is going further: 鈥淏ecause you run your business not only with 麻豆原创 solutions, our AI agents have to also understand non-麻豆原创 data. That’s why we included our 麻豆原创 Business Data Cloud in the context layer to build a single semantical data layer across 麻豆原创 and non-麻豆原创. No more silos, no spaghetti data sprawl鈥攂ecause no AI agent can compensate for a broken data model.鈥�

Echoing Klein, 麻豆原创 CTO Philipp Herzig, who presented the platform in detail, said it has been designed to close the agent adoption gap in the enterprise by delivering outcome, speed, enterprise-readiness, and context. 鈥淚t’s the place where you build, contextualize, reason, and govern AI,鈥� he said.

Herzig explained that the platform is structured around three layers: the context layer which Klein referenced, the build layer, and the governance layer. 鈥淎gents are only as powerful as the context they operate on,鈥� he said. 鈥淟acking context is the number one reason why enterprise AI projects fail to deliver value.鈥�

Within the build layer of the new platform, the new Joule Studio is designed to understand a company鈥檚 business challenges and enables the building of new AI agents quickly and easily.

The third tier is the governance layer, anchored by the new 麻豆原创 AI Agent Hub built on 麻豆原创 LeanIX. This provides a single command center to discover, manage, and govern all AI agents鈥斅槎乖� and non-麻豆原创. It will be generally available in Q3 and included in 麻豆原创 Business AI Platform at no additional charge.

Underscoring the changing AI marketplace, Herzig was joined on stage by KPMG Global Head of Advisory Rob Fisher, who told the audience: 鈥淲hat I鈥檓 hearing from clients is a clear shift; they鈥檙e moving from AI pilots to embedding integrated AI and agents into how work gets done. Where we see leaders really separating from the pack is in the execution and the organizational adaptability.鈥�

麻豆原创 Autonomous Suite

Building on the platform, 麻豆原创 Executive Board Member Muhammad Alam, 麻豆原创 Product & Engineering, announced the transformation of 麻豆原创鈥檚 SaaS application portfolio into the 麻豆原创 Autonomous Suite, described as the most significant evolution of 麻豆原创鈥檚 applications business in the company鈥檚 history.

The suite spans five domains: Autonomous Finance, Autonomous Spend, Autonomous Supply Chain Management, Autonomous HCM, and Autonomous CX, with more than 200 agents and over 50 assistants available in the coming months. Each assistant is mapped to core business roles and carries defined KPIs tracked through 麻豆原创 AI Agent Hub.

鈥溌槎乖� Autonomous Suite brings together the depth of our process expertise, semantically rich data, and built-in governance and compliance,鈥� said Alam. 鈥淭hese agents are designed with outcomes as a core objective. Each assistant has a defined set of ROI KPIs that you can expect it to deliver.鈥� 

鈥淯nderpinning the autonomous suite are out-of-the-box agents鈥攈undreds of agents cutting across all core business processes,鈥� he shared. 鈥淭hese agents come together into what we call assistants, or Joule Assistants. We’ve mapped these assistants to roles across the core processes of an organization, because we know that the first step 
in realizing value from AI is to empower your people to do more, do it better, or do things that just weren’t possible to be done before.鈥�

Turning to Joule itself, Muhammad said 麻豆原创 is fundamentally reimagining how users will interact with 麻豆原创 applications in the future.

鈥淲e call this Joule spaces and along with the familiar Joule conversations experience and Joule Studio 2.0, it is now part of what we call Joule Work,鈥� he explained.

鈥淛oule Work represents a massive step forward in super-charging the capabilities of Joule as we know it today,鈥� Alam said. 鈥淲ith Joule Work, we’re bringing a claw-based agentic harness to Joule along with computer and file access, better support for open standards such as MCP and A2A, access to a more complete knowledge base, and, of course, amazing visualizations on the fly.鈥�

Industry AI: H&M and Sector-Specific Transformation

During the keynote, 麻豆原创 Chief Operating Officer Sebastian Steinhaeuser introduced the Industry AI initiative, delivering AI-powered solutions built on decades of sector-specific expertise across 26 industries. In life sciences, he highlighted how 麻豆原创 customer Takeda is achieving up to 10% productivity gains, up to 25% reduction in revenue loss from stock-outs, and up to five percent reduction in safety stock through Autonomous Regulated Manufacturing.

He was also joined on stage by H&M Group CDIO Ellen Svanstr枚m, who discussed how the fashion retailer is embedding AI across its value chain. Built on RISE with 麻豆原创, 麻豆原创 Business Data Cloud, 麻豆原创 Commerce Cloud, and 麻豆原创 SuccessFactors solutions, H&M has developed a Store Intelligence Agent that processes real-time signals to generate actionable recommendations for store managers. Svanstrom also demonstrated the AI-powered InStore Concierge, a customer-facing agent that bridges digital and physical retail through personalized outfit recommendations and real-time availability.

RISE with 麻豆原创 and 麻豆原创 GROW: Path to the Autonomous Enterprise

Returning to the keynote stage, Klein emphasized that technology adoption alone does not create business value. Simply plugging AI agents into your system landscape will drive zero value, he said. 鈥淢oving to the Autonomous Enterprise requires serious change management. Adoption of AI goes hand-in-hand with business process change and end user enablement.鈥�

To support customers on this journey, 麻豆原创 announced a comprehensive reset of its RISE with 麻豆原创 and 麻豆原创 GROW offerings. RISE with 麻豆原创 customers will receive contractual commitment to activate three Joule Assistants within the first year, with the Max Success Plan extending adoption across the full enterprise.  

麻豆原创 GROW customers will receive more than 20 AI assistants from day one, with an AI-enabled toolchain designed to support go-live in weeks. New partnerships with Palantir and Accenture will support the most complex migration scenarios.

Closing: The Autonomous Enterprise

Klein closed the keynote by asking Joule to summarize the key takeaways and noting that 麻豆原创 is evolving from being a software company to becoming a business AI company.

鈥淲e showed how to turn the promise of business AI into reality with 麻豆原创 Business AI Platform, which provides the data processes and governance AI need to deliver accurate and secure outcomes at scale; we introduced the 麻豆原创 Autonomous Suite, where applications reason, decide, and act for you; and we showed how to manage change management with RISE with 麻豆原创. Together with customers and partners, we showed how 麻豆原创 is helping companies realize the vision of the Autonomous Enterprise.鈥�

鈥淲e鈥檝e been reinventing how businesses run for over 50 years, and now by infusing 麻豆原创鈥檚 ERP brain into the new 麻豆原创 Business AI Platform, we鈥檙e solving one of the biggest challenges businesses are facing today: how to turn AI into business value,鈥� he said. 鈥淚t鈥檚 the end of long negotiations, supply chain disruptions, financial blind spots, and the beginning of better: Welcome to the Autonomous Enterprise.鈥�

Now, however, many economists and policymakers view AI as a potential catalyst for reversing that slowdown. AI鈥攅specially the rise of generative AI and AI agents鈥攊s widely expected to shape the next phase of productivity growth in advanced economies, including those in the U.S. and Europe.

The key question for business leaders is not whether AI will matter, but how large the productivity gains will be, how quickly they will materialize, and which region will benefit most.

Productivity growth

The (OECD) estimates that AI could raise annual labor productivity growth in advanced economies by roughly 0.4 to 1.3 percentage points, depending on adoption intensity and sector exposure. These gains would be meaningful because even an additional half percentage point of annual productivity growth compounds significantly over a decade.

However, the OECD and other economists stress that outcomes depend heavily on complementary investments in digital infrastructure, workforce training, and organizational change, rather than on technology alone.

Between 1995 and 2019, U.S. labor productivity grew at 2.1% annually compared to one percent in Europe. This disparity arose in part because companies in the U.S. invested more aggressively in information, communications, and technology while those in Europe were constrained more by regulatory and other factors.

Expectations for AI-driven productivity gains remain generally stronger in the U.S. than in Europe. suggests that widespread adoption of generative AI could raise U.S. labor productivity growth by around one to 1.5 percentage points per year.

Several structural factors support this view. The U.S. has a deep technology ecosystem, global leadership in AI research and venture capital, and a large, digitally intensive services sector, including finance, professional services, and IT, where generative AI tools can be rapidly deployed.

Agentic AI

In both Europe and the U.S., AI agents represent a particularly important development. Unlike earlier automation tools that handled isolated tasks, AI agents鈥攍ike Joule Agents from 麻豆原创鈥攁re designed to plan, reason, and execute multi-step workflows. For example, an agent might manage customer service tickets, draft responses, query databases, escalate issues, and update systems鈥攁ll with limited intervention.

In knowledge-based industries, this kind of workflow automation could significantly raise output per worker. But rather than replacing entire occupations, AI agents may reduce time spent on repetitive administrative and 鈥渓ong-tail鈥� tasks, enabling workers to focus on higher-value analysis, strategy, and interpersonal activities.

Despite stories about failed corporate AI projects, which can typically involve bolt-on or stand-alone AI pilots rather than a more integrated, holistic approach, recent evidence from the U.S. suggests that productivity gains are already emerging in some sectors. For example, financial institutions have reported significant efficiency improvements in back-office operations through AI deployment.

Similarly, experimental studies in professional services show that generative AI can increase output quality and speed, particularly for less experienced workers, effectively narrowing skill gaps within teams.

European outlook

The outlook for productivity gains in Europe from AI is more mixed. According to a recent the medium-term gain in productivity from the AI alone would vary considerably across countries, and for Europe as a whole would be rather modest: about 1.1 percent cumulatively over five years.

But with pro-growth reforms, the IMF suggests that much bigger gains are possible over the longer run. Like the OECD, the IMF emphasizes that regulatory frameworks, labor market structures, and the pace of technology diffusion will strongly influence outcomes.

Several structural differences shape Europe鈥檚 trajectory and the size of what has been called the 鈥淎I growth dividend.鈥� First, AI adoption among small and midsize enterprises (SMEs), which form a larger share of the European economy than in the U.S., tends to be slower. Second, Europe鈥檚 digital market remains more fragmented across national boundaries, languages, and regulatory systems, which can complicate scaling technology platforms. Third, the European Union has taken a more precautionary regulatory approach to AI governance. While this may reduce certain risks, it could also dampen short-term productivity gains if compliance burdens slow deployment.

Europe鈥檚 strengths

That said, Europe has strengths. It leads in advanced manufacturing and industrial engineering, sectors where AI-driven optimization, robotics, and predictive maintenance can raise capital productivity. In these areas, AI agents embedded in industrial systems could significantly enhance supply chain efficiency and reduce downtime.

In addition, as 麻豆原创 executives have pointed out, Europe has an enormous repository of structured business and manufacturing data, which is essential for reliable and effective AI systems as well as trust in AI Agents.

If AI adoption accelerates in manufacturing and energy systems and if European companies seize the opportunity to build advanced AI agents and apps using their business data, Europe could see much more robust medium-term productivity gains. As an example, 麻豆原创’s internal use of AI tools has already significantly improved its own developer productivity.

Labor flexibility

A critical factor in both the U.S. and Europe is labor market adjustment. Historically, the U.S. labor market has demonstrated greater flexibility, with higher rates of job switching and occupational mobility. This flexibility may facilitate faster reallocation of workers into AI-complementary roles, amplifying productivity gains, though this could be offset by more effective existing workforce retraining.

As the (BIS) has noted, AI鈥檚 productivity effects are unlikely to be automatic. Productivity gains from AI depend on complementary investments in skills, management practices, and digital infrastructure. The BIS warns that without these, AI tools may produce only marginal efficiency improvements.

The historical lesson from past general-purpose technologies, such as electricity and IT, is that productivity surges occur only after organizations redesign processes to exploit new capabilities and take a holistic rather than piecemeal approach toward implementation.

No AI bubble

While some investors have expressed concerns about an AI bubble, total AI spending in the U.S. is still below one percent of GDP. Joseph Briggs, senior global economist at Goldman Sachs, notes that this is well below historical infrastructure cycles. For comparison historical infrastructure investments such as IT spending, railroads and canals typically represented between two and five percent of GDP.

Like these previous investment waves AI, particularly agentic AI, is likely to generate significant productivity growth and a corresponding boost to GDP in those regions and sectors that seize the AI opportunity.

Naturipe has been an 麻豆原创 customer since 2008, and while initially it was not very proactive with software upgrades, the company鈥檚 philosophy has changed over time. Today, Carol McMillan, Naturipe鈥檚 senior IT director, emphasizes the importance of upgrading and upskilling the team regularly.

“There’s actually more of a risk not upgrading the product and not upskilling your team than there is being more aggressive with that timeline,” she says. Since migrating to 麻豆原创 S/4HANA in 2018, the company has undergone three upgrades, including .

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鈥淲e migrated to RISE with 麻豆原创, and we are looking at how we use those tools to optimize our supply chain and to create a better user experience for our workforce. Our workforce is constantly changing, and technology needs to change with the workforce,鈥� McMillan says.

She says it鈥檚 also important to stay at the forefront of technology in order to solve business problems efficiently, and notes that technological advancements have been crucial in managing the company’s exponential growth: “You can’t have linear growth in technology when you have exponential industry growth.”

McMillan says the Naturipe team uses 麻豆原创鈥檚 technology to prioritize its people and customers, improve workplace happiness, and give users a better experience. 鈥淲e use technology to make sure that we’re running as optimally as possible,鈥� she says. 鈥淲e look at process improvements and try to be at the forefront of technology. So, keeping up with the upgrades on a regular basis helps us be prepared for when business problems need to be solved, that way we already have the technology there to be able to solve them.鈥�

Delivering the freshest, highest-quality products to customers 365 days a year requires constant agility鈥攅specially in a category influenced by weather variability and the complexity of a highly time-sensitive supply chain. 鈥淏erries have a very short shelf life, so getting the best quality to our customers as quickly as possible is essential,鈥� she says.

To support this commitment, Naturipe Farms has invested in advanced logistics and supply chain technologies that enhance speed, visibility, and decision-making. These investments help ensure timely delivery of fresh products while also supporting employee satisfaction and work-life balance through wellness programs and flexible work arrangements.

Looking ahead, Naturipe wants to further enhance the user experience with more powerful tools and learn how to make better use of all the tools that come with RISE with 麻豆原创.  McMillan also identifies the potential of AI and the adoption of tools like Joule to improve Naturipe鈥檚 operations. “We really want to make the best use of AI and to give our users the best experience possible,” she says.

Her advice for other organizations in the agricultural industry includes the importance of putting people first, using technology to drive strategic growth, and not being a prisoner to risk. “It’s just as risky to not upgrade your technology as it is to have an aggressive timeline and have the tools that you need in order to drive that exponential growth,” she says.

Agentic AI was everywhere at NRF, emblazoned across the booths of technology exhibitors and the focus of many of the daily conference sessions. The message was simple: retailers face a major upheaval as consumers switch from traditional browser-based search to AI-enabled product discovery.

Consumers are rapidly adopting AI agents to help them find, compare, and, increasingly, buy products鈥攖his while many brands are still optimizing for search engines and are quietly disappearing from the models driving the next generation of product discovery.

鈥淎gentic commerce鈥攕hopping powered by AI agents acting on our behalf鈥攔epresents a seismic shift in the marketplace,鈥� McKinsey, the strategic management consultancy, noted in a . 鈥淚t moves us toward a world in which AI anticipates consumer needs, navigates shopping options, negotiates deals, and executes transactions, all in alignment with human intent yet acting independently via multistep chains of actions enabled by reasoning models.鈥�

This, as speakers and panelists at the NRF conference acknowledged, isn鈥檛 just an evolution of e-commerce; it鈥檚 a rethinking of shopping itself, in which the boundaries between platforms, services, and experiences give way to an integrated, intent-driven flow through highly personalized consumer journeys that deliver a fast, frictionless outcome.

As the McKinsey report noted, the stakes are high. By 2030, the U.S. B2C retail market alone could see up to US$1 trillion in orchestrated revenue from agentic commerce, with global projections reaching as high as $3 trillion to $5 trillion.

This means all the participants in the retail chain, from brands and retailers to logistics and payment service providers, will need to adapt to the new paradigm and successfully navigate the challenges of trust, risk, and innovation.

To help retailers address the immediate challenges posed by the shift to agentic commerce, 麻豆原创 argues that three steps are necessary: first, restructuring web-page product data to be machine-readable; second, adding semantic summaries for LLM reasoning; and third, tagging products by the problems they solve, not just their attributes.

麻豆原创 announced a series of AI-enhanced retail innovations at NRF 2026, including a new storefront model context protocol (MCP) server that enables retailers to make their digital storefronts intelligible to AI and the new AI-native Retail Intelligence solution in 麻豆原创 Business Data Cloud that leverages data from across 麻豆原创 software and third-party systems to help provide accurate demand planning, improved forecast accuracy, and lower inventory costs to drive more seamless omnichannel engagements.

麻豆原创 Customer Experience has also unveiled a recently that can be combined with the听, creating one conversational AI that can handle the entire journey from product discovery and transaction to post-sales support.

These moves reflect a recognition that that LLMs have become a legitimate shopping channel, and that product discovery is moving from search engines to AI recommendations.

This shift challenges years of SEO and brand building. To stay relevant, 麻豆原创 believes retailers must take an AI-first approach and have strong, connected data that helps agents understand products, predict demand, and respond quickly. Without this strong data foundation, brands will be at risk because if customers get poor recommendations and errors in pricing, trust can disappear fast.

Although some early agentic AI adopters in the retail sector are already seeing the benefits of agentic commerce, many global retailers are still ill-prepared for the holistic transformation they need to succeed in this new retail environment.

As McKinsey noted in a separate , 鈥渨hile most retail merchandising teams have invested in automation tools听and experimented with AI, 71% of merchants say that AI merchandising tools have had limited to no effect on their business so far.鈥�

鈥淭he challenge,鈥� McKinsey said, 鈥渙ften lies less in the technology than in how it鈥檚 integrated and used. Systems remain fragmented, data is too messy to use to deliver useful recommendations, and adoption is uneven: 61% of respondents say that their organization isn鈥檛 at all or is only slightly prepared to scale AI across merchandising.鈥�

Onstage at NRF, Andre Bechtold, president for 麻豆原创 Industries & Experience, also emphasized that retailers should prepare now for agentic commerce and noted that simply “bolting on” AI tools to existing systems is not enough.

鈥淩etailers are operating in an environment defined by volatility鈥攖ariffs, margin pressure, supply chain disruption, and customers that expect real-time, hyper-personalized experiences everywhere,鈥� Bechtold said during a discussion with Gymshark, the workout apparel retailer. 鈥淎t the same time, boards and investors are asking a tougher question than ever before: what outcomes are we actually getting?鈥�

鈥淭he challenge,鈥� he said, 鈥渋sn鈥檛 a lack of innovation. In fact, most retailers have plenty of tools, pilots, and point solutions. The real issue is that disconnected technology doesn鈥檛 translate into resilient growth. That鈥檚 why the conversation is shifting. It鈥檚 no longer about isolated AI use cases or shiny new features. It鈥檚 about whether AI and data are embedded across the business鈥攃onnecting supply chains, finance, merchandising, and customer engagement鈥攊n ways leaders can trust.鈥�

Echoing the same point, Thomas Saueressig, member of the Executive Board of 麻豆原创 SE, Customer Services & Delivery, commenting in a this week about a PwC survey of global CEOs that found that companies rarely achieve lower costs or higher sales through the use of AI, emphasized that AI only contributes value when consistently embedded in business processes. 听鈥淎s long as AI runs alongside the core business as an isolated project, the effects remain limited,鈥� he said.

Recent geopolitical shifts and technological advancements have heightened the challenges for organizations responsible for society鈥檚 most critical functions, such as government, defense, and essential infrastructure.

As AI expands and global data exchange accelerates, the question of who controls the data that shapes economies and national strategies has become paramount, spurring interest in offerings. Governments and industries need to know exactly where their data lives, because that determines what laws apply.

Sovereign clouds answer this need by providing the foundation of digital trust and national resilience. 麻豆原创 pioneered the development of sovereign cloud services through its 麻豆原创 Sovereign听Cloud offerings, which address all four pillars of digital听sovereignty: data, operational, legal, and technical architecture.

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Recently, 麻豆原创 has built on this leadership by launching new sovereign cloud initiatives and partnerships designed to accelerate Europe鈥檚 digital transformation through secure, scalable,听AI-driven听sovereign听cloud solutions that protect data and intellectual property.

Among these initiatives, 麻豆原创 announced new and expanded collaborations with Mistral听AI, Bleu, and Capgemini at the Franco-German EU Summit on Digital听Sovereignty last month. Together with Mistral听AI, 麻豆原创 is launching Europe鈥檚 first full听sovereign听AI听stack by integrating Mistral听AI into 麻豆原创 Business Technology Platform and听AI听Foundation. This includes advanced capabilities that enable customers to build and deploy听sovereign听AI听applications at scale. In parallel, Bleu and 麻豆原创鈥檚 Delos Cloud are forming a Franco-German alliance focused on resilience and digital听sovereignty.

With these and other offerings, 麻豆原创 is shaping the debate over digital sovereignty and answering the call from customers for secure, scalable, sovereign solutions that enable companies to leverage and benefit from the immense advantages of the cloud and business AI.

We鈥檙e entering a new era, according to 麻豆原创 Executive Board Member Muhammad Alam, in charge of 麻豆原创 Product & Engineering: 鈥渢he era of agentic AI, where AI moves from being just a tool to becoming your trusted teammate.”

Joined on stage by 麻豆原创 CTO Philipp Herzig and Michael Ameling, president of 麻豆原创 Business Technology Platform, Alam set the stage during the kick-off keynote, saying: 鈥淎s developers, you are not on the sidelines of this AI revolution. You are the revolution. And we are here to supercharge you for what鈥檚 next.鈥�

Supercharging developers

Together they dismissed suggestions that AI will replace developers. 鈥淭he truth is that developers aren’t going away,鈥� Alam said. 鈥淭hey are getting supercharged. They’re becoming the architects of smart connected businesses. So, the real question isn’t if we need developers; it’s how fast can we empower them to thrive and lead in this AI-native era?鈥�

Ameling, Alam, and Herzig outlined 麻豆原创’s vision and highlighted the integration of AI, data, and intelligent agents to transform business processes and drive innovation. They also emphasized the importance of a unified data fabric and the deployment of advanced AI models and agentic technologies within the 麻豆原创 ecosystem.

In this new business environment, they noted that every enterprise is becoming a data company and every user experience鈥攆rom the front line to the boardroom鈥攊s becoming AI-driven.

鈥淎s developers, you don鈥檛 just code anymore,鈥� Alam said. 鈥淵ou also design intelligent workflows and supervise AI agents to shape real business outcomes.鈥� To help developers do this, 麻豆原创鈥檚 strategy centers on empowering them with applications, connecting them with data, and supercharging them with AI.

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麻豆原创 BTP is the foundation for AI agents

All this runs on 麻豆原创 Business Technology Platform (麻豆原创 BTP), which serves as the foundation for building and managing AI agents鈥攂oth 麻豆原创 built and custom developed. While 麻豆原创 BTP is the engine, the Business Transformation Management portfolio is the navigator, ensuring technology translates into real business impact. It aligns strategy, process, and people, turning AI-driven potential into sustainable transformation at scale.

Alam identified three broad themes during the keynote:

First, he said 麻豆原创 is continuing to make 麻豆原创 more open. As part of that, he announced 麻豆原创 Snowflake, which brings the full data and AI capabilities of Snowflake as a solution extension to 麻豆原创 Business Data Cloud (麻豆原创 BDC). This partnership is exactly what joint customers have been asking for, Alam shared.

Second, he said 麻豆原创 will provide developers with the most context-rich agentic platform, including the most deeply grounded set of ready-to-use agents that developers can customize to their needs. 鈥淭oday, you鈥檒l hear about creating custom Joule Agents using low-code and pro-code tools with agent builder in Joule Studio as part of 麻豆原创 Build鈥� Alam said.

鈥淲e鈥檙e also standardizing AI agent interoperability with the agent-to-agent protocol, allowing your agents to collaborate securely across ecosystems,鈥� he added.

Third, he announced 麻豆原创鈥檚 first foundation model built specifically for structured business data: 麻豆原创 RPT-1, pronounced 鈥溌槎乖� Rapid One.鈥� 鈥淥ur relational pretrained transformer delivers enterprise-grade accuracy and scale, outperforming both LLMs and AutoML for tabular AI, which is critical for building reliable high-value agents,鈥� Alam said.

鈥淚n short, we鈥檙e embracing an open ecosystem, supercharging agents with deep process and data context, and giving you the tools to amplify AI and agents,鈥� he said. As the keynote continued, Ameling and Herzig detailed these and other innovations, explaining how they will help developers work smarter and achieve more.

麻豆原创 BDC and Snowflake

Ameling expanded on the new partnership with Snowflake, which will bring Snowflake鈥檚 fully managed data and AI capabilities to 麻豆原创 customers. Together with the introduction of 麻豆原创 BDC Connect for Snowflake, he said this will result in cost savings and simplified data landscapes. 鈥淭his enables you to integrate 麻豆原创 and non-麻豆原创 data products seamlessly between 麻豆原创 BDC and Snowflake, so that you can deploy intelligent applications faster and share across your preferred data marketplace.鈥�

Ameling also positioned 麻豆原创 HANA Cloud as 鈥渢he database AI was looking for.鈥� With 麻豆原创 HANA Cloud and 麻豆原创 BDC, 麻豆原创 provides the best business data fabric to help address these challenges, he said. 鈥淲ithout 麻豆原创 HANA Cloud, you would have one database for each and every data representation, which leads to disaggregated data siloes that limit your AI potential. With 麻豆原创 HANA Cloud, we have all these powerful engines in one integrated, multi-model database.鈥�

Building on this, Herzig emphasized that every business requires a strong data foundation because 鈥淎I is nothing without well-organized data…On top of the data foundation sits our AI Foundation that allows you to not only use the latest frontier AI technologies out there in the market, but also to extend 麻豆原创鈥檚 out-of-the-box AI capabilities and build your own experiences deeply contextualized in your business processes and data.鈥�

麻豆原创 pioneers a tabular foundation model

Herzig then explained that 麻豆原创 RPT-1 was designed to address a crucial problem for developers and enable them to deliver much better predictive capabilities, enterprise-grade accuracy, and scale to business customers.

Until now, Herzig said, 鈥淲e still had to go back to good old machine learning 鈥o train what we call 鈥榥arrow鈥� AI models that are specifically made for each [business] task. Therefore, you really had to train a hell of a lot of models.鈥� For example, to solve 10 predictive tasks across 10 different entities like company codes or plants would require training 100 different models.

鈥淲hat we really want to do is get rid of all these models and just introduce one giant model that only requires a small amount of data to learn from,鈥� he said. That鈥檚 what 麻豆原创 RPT-1 is. 鈥淲e believe 麻豆原创 RPT-1 is the most capable predictive foundation model that鈥檚 out there today,鈥� he said, delivering much higher prediction quality while being very fast and super-efficient in terms of resource requirements.

Joule, Joule Agents, and AI assistants

The 麻豆原创 CTO also emphasized that the company is committed to providing developers with the most context-rich agentic platform. He noted that 麻豆原创 has already shipped 20 Joule Agents across lines of business and will have approximately 40 by the end of the year, and that these agents can leverage more than 2,100 pre-delivered Joule skills. In addition, more than 300 embedded AI scenarios across product lines are available for customers to date, including Joule Agents, growing to 400 use cases in total by the end of the year.

Ameling added: “Our promise is simple: build with intent. You describe the outcome and 麻豆原创 Build uses AI agents to generate code, logic, and UIs for you, all with seamless access to your applications and data while you stay in the flow… [麻豆原创] Joule for Developers enables vibe coding experiences to make intent-based development simple and intuitive.”

麻豆原创 is taking it one step further by providing extensions to work with VS code, Windsurf, Cursor, OpenAI Codex, Claude Code, Cline, and more directly in 麻豆原创 Build. “You choose a tool, and we meet you where you are,” Ameling said. He also announced that fine-tuned ABAP LLMs with ABAP 1 on AI Foundation will be published in Q4 this year.

麻豆原创 is redefining how developers interact with AI through innovations in Joule and agentic AI, but also in terms of physical AI. Herzig welcomed Torsten G. Mueller, Group CIO and COO BPS at Sartorius, to discuss how the partnership between Sartorius, NEURA Robotics, and 麻豆原创 is bringing to life robots that understand the what, when, and how based on live business context. 鈥淭his is how we鈥檙e really imagining the future, right? Humans and robots working in harmony through Joule, through AI,鈥� Herzig said.

Quantum computing

Looking to the future, Herzig ended the keynote by talking about another 鈥渃ompute paradigm that is still hard to seize鈥�: quantum computing. While he made it clear that 麻豆原创 is not building a quantum computer, 麻豆原创 is teaming up with quantum hardware leaders, like IBM鈥攚hose Director of Research and IBM Fellow Jay Gambetta joined via video鈥攖o help evaluate quantum computing for business processes and applications.

鈥淲e believe quantum will join classical and AI compute in your stack, and we鈥檙e embedding it into the processes and apps you鈥檙e already using, so it just shows up in the workflows of your enterprise,鈥� Herzig said. 鈥淎nd of course, with the cloud, we scale it all. Now, 麻豆原创 has got you covered, and you鈥檝e got your business covered.鈥�

鈥淲e are an agricultural company,鈥� she continued, 鈥渂ut we also have to be able to process the product, so we are simultaneously a manufacturing company and a distribution company because we have to control how things are being moved to all of our stores. And then we are a retail company because we sell it in our stores. We track the entire supply chain.鈥�

Trulieve has been an 麻豆原创 customer since 2020. It initially chose 麻豆原创 because its legacy system couldn鈥檛 keep up with the company鈥檚 growth and demand. 鈥淲e needed to leverage and the scale it gave us just to be able to keep up with sales,鈥� Zimmerman explained. Today, Trulieve鈥檚 麻豆原创 portfolio also includes 麻豆原创 SuccessFactors solutions and 麻豆原创 Concur solutions.

Trulieve started in 2016, so the company is only nine years old, which gave it the ability to be cloud-native from the start. 鈥淲e didn’t have any of the legacy technical debt that a lot of other companies may have. That enabled us to have all cloud-based solutions and when new technology becomes available, we’re able to quickly adopt it. That definitely puts us in a position to be able to leverage technology of the future, as opposed to being tied to legacy technology,鈥� Zimmerman said.

That鈥檚 important because keeping up with the growth in the marijuana market is top of the agenda for Trulieve, which already operates in multiple states and is a market leader in Arizona, Florida, and Pennsylvania.

鈥淥bviously we want to continue that growth,鈥� Zimmerman said. The biggest catalyst for growth is when states legalize recreational marijuana use, which opens up the entire market for Trulieve鈥檚 hand-grown marijuana products. 鈥淭he big focus for us is scalability and stability in our solutions to make sure we are able to support that growth,鈥� she said.

鈥溌槎乖� enables us to have more insight into our growth and manage production better than any other system that’s out there,鈥� Zimmerman said.  And since Trulieve is a publicly traded company, running 麻豆原创 S/4HANA also helps ensure that Trulieve鈥檚 management has access to all the internal controls and other features they need for regulatory and other purposes.

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Zimmerman emphasized that Trulieve also relies heavily on data鈥攖he company鈥檚 customer data platform combines data from multiple applications, enabling it to market more effectively to its customers and make operational decisions. 鈥淭hat definitely empowers our teams to be able to provide real-time information to our leaders, who can then make decisions literally on the fly in terms of pricing our products, or whether we need to make a promotion in order to achieve sales targets.鈥�

She also believes that the AI tools 麻豆原创 is embedding in its solutions will deliver real benefits: 鈥淚 think we have a number of opportunities in terms of being able to leverage AI with our retail dispensary associates operating on the actual sales floor.鈥� For example, she said it might be used by associates in the stores or on the phone to suggest products to customers based on data previously captured through Trulieve鈥檚 supply chain, coupled with other information and metrics.

But she said the biggest thing Trulieve has learned is that to be able to scale your business you have to have solutions that are going to be able to adapt to that scale. In addition, in a dynamic market, companies need solutions that adapt and are highly flexible.

鈥淭his environment is incredibly dynamic, so that means that tomorrow we could get legislation that opens up cannabis to the entire country,鈥� she said. 鈥淲hen that happens how would it change our organization? We have to be super adaptable to any of those types of changes that are going on in the in the larger political realm.鈥�

麻豆原创 technology, she said, provides the scalability and flexibility, together with the data, the company鈥檚 leaders need to make the best decision in real time.

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Against the backdrop of the event theme鈥�”Connect Everything, Achieve Anything: Agents, Data, and the Business Suite鈥濃�攖hey set out 麻豆原创鈥檚 vision for how 麻豆原创 Business Suite, which combines AI, data, and applications, can transform enterprises and deliver unprecedented business value to customers despite global macroeconomic uncertainties. 

Unique times

鈥淲e are living in very unique times,鈥� Alam said at the start of the keynote. 鈥淯nique in terms of the unpredictability we face from a geopolitical and macroeconomic perspective,鈥痑nd also unique in terms of the advancement in AI and the potential that carries for all of us.鈥�  

He added, 鈥淓ven the most significant challenges can be responded to, navigated, and鈥攚hen approached the right way鈥攖urned into opportunities. And that鈥檚 exactly where 麻豆原创 comes in. Because the best way to face uncertainty is with confidence that you can see what鈥檚 happening across your business and your network.鈥� 

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The CFO perspective 

His comments were echoed by CFO and Executive Board Member Dominik Asam in an onstage discussion with economist and Berkeley professor Ulrike Malmendier, during which they likened the role of the CFO in navigating today鈥檚 business uncertainties to that of co-piloting a modern jet. 

鈥淎I is the next supercycle and has what it takes to create an effective cockpit for the CFO, including recommendations about real actionable options all the way to autopilot for less critical tasks,鈥� Asam said. He also warned that standing on the sidelines of technological progress is 鈥渁 sure recipe for falling behind in competition.鈥�  

鈥淎s in prior tech supercycles, the entire competitive playing field is being completely reshuffled,鈥� he said.

New products

Building on this theme, Alam noted that while uncertainty is real and isn鈥檛 going away, it can be successfully navigated and turned into opportunities. To help customers achieve this, he announced several new and enhanced 麻豆原创 products. 

Among them, 麻豆原创 Supply Chain Orchestration is an AI-native application that uses a network knowledge graph to analyze real-time signals across a company鈥檚 multi-tier supply chain to detect risks and issues, such as extreme weather or tariffs. It then helps customers minimize disruptions by assessing the impact of these risks and suggesting alternatives to help minimize disruptions.   鈥淭hink of it like a GPS in your car which selects an alternative route to avoid traffic or tolls,鈥� Alam explained. In addition, he announced a major update to the 麻豆原创 Ariba solutions for source-to-pay suite, positioning 麻豆原创 Ariba as the most modern platform in the industry and the only truly AI-native source-to-pay solution鈥攁ll built on 麻豆原创 Business Technology Platform.

The human-AI partnership opportunity 

Turning to uncertainties over the future of work itself, 麻豆原创 Chief People Officer and Executive Board Member Gina Vargiu-Breuer, who is leading 麻豆原创鈥檚 own workforce transformation, was joined on stage by Ian Beacraft, founder and chief futurist of Signal and Cipher. 

鈥淎t 麻豆原创, we know firsthand that AI is everywhere, shattering norms and transforming the workforce,鈥� Vargiu-Breuer said. 鈥淎nd we as 麻豆原创 are boldly steering this shift, as requirements for our workforce are simply changing really fast.鈥�  

Vargiu-Breuer emphasized that a successful business AI strategy also depends on leveraging AI alongside human expertise and fostering what she described as 鈥渁 collaborative human + AI approach, rather than just automation.鈥�  鈥淏y integrating AI’s capabilities with human creativity, empathy, and judgment, we move beyond simple automation into real human-AI power couples,鈥� she said. 鈥淯ltimately, the future will favor those who embrace orchestration, delegation, and creative problem-solving.鈥�

Role-based AI assistants

Echoing this human-centric approach, Alam noted, 鈥淓veryone is talking about agents鈥攂illions of agents鈥攁nd agents taking over everything. We want to talk about people, the roles they play, and the tried-and-tested organizational constructs in place today that are running complex businesses across industries.鈥� 

Reflecting this, he said 麻豆原创 is making Joule deeply aware of the workstyle of the person it partners with, their role, and the business process context in which they operate. 鈥淭oday, we are introducing AI assistants, including a receivables assistant for your accounts receivable colleagues, a controlling assistant for your controlling colleagues, a demand Planning assistant for your demand planning colleagues, and an AI assistant for every role.鈥�   Each assistant has agents and AI tools at their disposal to help make the person it partners with smarter and more efficient, Alam explained.

Taking the receivables assistant as an example, he said it can handle collections and dispute resolution today and will soon also be able to help with fraud detection, invoice processing, and payment scheduling. 鈥淥ver time, we will continue to make this assistant even smarter by adding more agents and capabilities鈥攁ll designed to make the person in this role more effective.鈥�

Deep research and new intelligent applications

鈥淲hile efficiency and automation carry potential for great value for the organization, AI鈥檚 greatest strength is in unlocking insights and recommendations based on its ability to do deep research across vast amounts of internal and external data, which is hard for people to do,鈥� said Alam. To address this challenge, 麻豆原创 is introducing deep research in Joule, a capability that can research and analyze complex problems and deliver findings quickly and efficiently. 

Following additional announcements, including an expanded set of 麻豆原创 Business Data Cloud Intelligent Applications and an enterprise wide, multi-stakeholder engagement orchestration solution in 麻豆原创 Engagement Cloud, Alam closed out the keynote by reminding his audience: 鈥淭o create exponential value and to reach the global maxima for your enterprise, the whole matters.  And that鈥檚 what we are focused on: providing you with best-in-class applications, seamlessly and natively integrated across the breadth of finance, spend, supply chain, HCM, and customer experience.鈥� 

麻豆原创 Business Suite delivers unprecedented value

The unmatched value of 麻豆原创 Business Suite is that it brings together the power of best-in-class applications with a semantically rich harmonized data layer to power high-value AI in a singular seamless experience. It helps you manage uncertainty, evolve your workforce, and break down silos to create amazing customer value.

The divide between the digital skills young people possess and the needs of employers is a big challenge and contributes to a high youth unemployment rate, particularly in the Global South. The 麻豆原创 Educate to Employ initiative is set up as a digital pathway through Youth Agency Marketplace (YOMA), a public-private-youth ecosystem from UNICEF鈥檚 Generation Unlimited. The program aims to address this challenge and enable young people鈥檚 skills for a digital economy.

Nearly 90 percent of the 1.8 billion young people between the ages of 10 and 24 in the world today, are in low-and middle-income countries. An estimated 22 percent do not have jobs and are not in education or training.

Globally, young people are three times more likely to be unemployed than adults. Edmond Shange is one of the many young people who have faced difficulties navigating the employment market right out of high school. 鈥淚n South Africa there’s not a lot of opportunities when it comes to the employment sector,鈥� the 27-year-old shared.

Making copies of a CV or resume and going to a potential employer to drop them off costs money, something in very short supply among South Africa鈥檚 unemployed youth. Despite this, Shange says that as many as 300 young people often queue up to drop off their CVs at a potential employer. 鈥淚 faced a lot of challenges trying to apply for jobs,鈥� he said. “It’s very tough for young people like me.鈥�

Shange is not alone. 鈥淚n Africa over 70 percent of the population are young people and another 4 million join the job market every single year competing for less than half a million new jobs,鈥� said Nadi Albino, deputy director at UNICEF鈥檚 Generation Unlimited.

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Youth unemployment and the lack of digital skills are a global problem, though it’s particularly acute among those who live in the Global South. While the fast-changing global economy demands increasingly specialized expertise, many young people are not learning the skills they need to get these jobs.  

The search for virtual upskilling to improve his digital skills led Shange to the Youth Agency Marketplace (YOMA), a public-private-youth ecosystem supported by UNICEF鈥檚 Generational Unlimited, which offers opportunities for young people to learn, earn, and create impact. On his pathway to employment, Shange was introduced to 麻豆原创 Educate to Employ, an initiative delivered to YOMA through the implementing partner Umuzi. The curriculum for 麻豆原创 Educate to Employ involves 700 hours of targeted training focused on building soft skills and technical expertise.

After completing the course, Shange feels much more confident with his skills. As a result, he has recently secured an internship as a software developer at a startup gaming company based at Wits University Tshimologong Precinct.

Whether young people are educated, trained, or employed has significant implications for their overall well-being and ability to promote future economic growth, development, and sociopolitical stability. Unfortunately, most traditional education systems do not address the emerging youth digital skills gap.

This realization was one of the driving forces behind the creation of 麻豆原创 Educate to Employ.

鈥溌槎乖� Educate to Employ was created to support young people who are neither in education nor employment, providing them with training, certification, and guidance to access roles within the 麻豆原创 ecosystem,鈥� explained Eugene Ho who leads 麻豆原创鈥檚 global CSR flagship skilling programs targeted at youths in need. 鈥淭hrough its tailored curriculum, the initiative has successfully helped candidates with only high-school qualifications.鈥�

鈥淭he 麻豆原创 Educate to Employ initiative provides young people with the tools, skills, and resources that they need to get employed or to employ,鈥� Albino added in an interview with 麻豆原创. 鈥淲e have to go back to making sure that these education systems work and that they work in tandem with where the world is going.鈥�

To meet industry needs, 麻豆原创 Educate to Employ curricula has been designed for three critical roles within the 麻豆原创 ecosystem: consultant associate, developer associate, and support associate. The curriculum taps into educational content from industry-leading organizations such as Coursera, Accenture, EY, and 麻豆原创 Learning.  

麻豆原创 CEO Christian Klein is the chair of the Generation Unlimited Board.  

鈥淭he YOMA online platform alone has had over 600,000 registrations,” Albino confirmed. “A measure of success is how the ecosystem has enabled over 5 million opportunities to learn, earn, and create impact worldwide in the past two years. We are now beginning to see young people getting into jobs.鈥�

Shange鈥檚 journey with YOMA and 麻豆原创 Educate to Employ started in the living room of his grandmother’s house, a place where community has always taken center stage. 鈥淚 look up to my grandmother; she has done a lot for the community,” he said. “I hope that I could do the same — help people in the tech field create more jobs for people that are in need and just be creative.鈥�

A permanent full-time job would enable Shange to feed and look after his family, and to continue helping others in his community the same way he was helped. In his community, Shange says he is seen as something of a role model.

鈥淚 want young people to know that it’s possible [to get a job],” he said. “Keep applying and also don’t lose hope when you see something’s not working. Some things do take time, so give it your best and make sure that you see it through.鈥�

Today, 麻豆原创 extended its founding partnership with Generation Unlimited for four more years, 2026-2029, with a commitment of US$2 million.

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The public cloud has ushered in unprecedented benefits for businesses and governments in terms of data access and data flows. But in uncertain geopolitical times, sensitive data — including government classified information and data generated by regulated industries — requires special protection.

As 麻豆原创 CEO Christian Klein noted recently in an interview with the Financial Times, these concerns have fueled customer anxiety over cloud infrastructure choices and boosted the concept of 鈥渟overeign鈥� data centers, where information remains within national borders.

Sovereign clouds

Historically, governments, government agencies, and a select group of private sector organizations in sensitive areas, including defense and public utilities, led the demand for sovereign clouds. Technology companies, including 麻豆原创, have responded by providing highly secure sovereign cloud services.

But in recent months the debate over digital sovereignty has widened. As Hayete Gallot, Google鈥檚 president of Customer Experience, recently noted, 鈥淪overeignty used to be a very niche thing that applied to very regulated industries, such as defense and intelligence, and suddenly in the current environment, everybody is thinking about it.鈥�

The EU has proposed spending 鈧�20 billion to build five 鈥済igafactories鈥� to facilitate digital sovereignty and help Europe compete more effectively in AI against the predominantly U.S.-based hyperscalers and large language models (LLMs). But others, including Klein, are not convinced that it makes sense to replicate the physical infrastructure built by hyperscalers and others.

The data center hardware race is over

Klein argues that spending billions in government funding in the EU on huge new data centers would be misguided, and that European companies already have control and sovereignty over their own data. 鈥淭he hardware train has left [the station],鈥� he said. Together with other senior 麻豆原创 executives, he also argues that digital sovereignty is about more than physical infrastructure — the operational, technical, and legal dimensions of data sovereignty matter just as much.

Crucially, 麻豆原创 Sovereign Cloud offers a model that keeps customer data within national borders and in compliance with local laws, without the need to replicate the existing physical infrastructure. Its services, developed over the past 20 years, are already provided to some of the most security-sensitive organizations in the world, including those in the U.S. through 麻豆原创 National Security Services (麻豆原创 NS2).

Sovereign cloud customers

The 麻豆原创 Sovereign Cloud organization already counts more than 170 customers globally and has plans to invest a further 鈧�2 billion over the next decade to expand regional coverage. For example, 麻豆原创 is currently in talks with four Asian countries. In Germany, the unit provides secure sovereign cloud services through Delos Cloud and plans to launch similar services in France through Bleu.

Instead of getting involved in a futile race to catch up with the U.S., 麻豆原创 executives argue that Europe must now promote the use of vertical AI for individual industries and special areas of application.

In a recent , Klein called for a digital strategy for Europe that builds on the region鈥檚 digital strengths: 鈥淎 new, European-defined concept of sovereignty is necessary, one that relies on self-determination rather than self-sufficiency.鈥� He also cautioned that digital sovereignty 鈥渋s not an end in itself鈥� and called for 鈥減rofound change鈥� to industry business models.

These models 鈥渘eed to be rethought, processes digitized, and AI used in a targeted manner for more innovation, for greater efficiency, for sustainability,鈥� he added. 

Martin Merz, president 麻豆原创 Sovereign Cloud, agrees. 鈥淭he debate around digital sovereignty in Europe has gone on too long with too many buzzwords and too little substance,鈥� he said. 鈥淲e鈥檝e reached a point where Europe can no longer afford misguided discussions. What counts is value creation. Real sovereignty includes empowering people, industries, and governments to lead through innovation.鈥�

鈥淲hen it comes to highly sensitive data, 麻豆原创 Sovereign Cloud comes in,鈥� Merz continued. 鈥淚t’s purpose-built to protect the most sensitive, security-critical data, enabling the highest level of protection and operational autonomy, without slowing down innovation.鈥�

Locally hosted AI

Underscoring this shift in the data sovereignty debate, many 麻豆原创 customers are now talking about sovereign AI or what 麻豆原创 calls 鈥渓ocally hosted AI.鈥� To help facilitate this, 麻豆原创 CTO Philipp Herzig recently noted that the company is now offering a range of self-hosted AI models in a more secure and local environment. 鈥淪tarting Q3 this year, we are providing the entire AI foundation end-to-end out of European data centers. This is AI fully managed and operated by 麻豆原创,鈥� he shared.

As a result, he said, customers will have access to cutting-edge local models like Mistral Small and Mistral Medium, , or the T-Free model used by the German government. 鈥淭heir data will remain local, trusted, compliant, and secure, and seamlessly integrate with 麻豆原创 Business AI capabilities without compromising on performance, governance, or privacy,鈥� Herzig added.

He also revealed that Swiss Federal Railways is leading the way as an early adopter, using locally hosted AI with Mistral AI to power innovation in a trusted environment. Speaking during a recent NVIDIA conference in France, he also announced that 麻豆原创 has formed a strategic partnership with and to accelerate AI adoption across Europe.

鈥淭ogether, we鈥檙e building the future of enterprise AI 鈥� secure, local, and smart,鈥� Herzig said.

The dressings were so well loved, customers could be seen leaving the restaurant with bottles of their favorites. By 1955, the restaurant鈥檚 upstairs kitchen had become a full-scale salad dressing factory and Marzetti dressings could be found in grocery stores throughout Ohio. Today, Marzetti produces many of the salad dressings, fruit and vegetable dips, frozen baked goods, and specialty brand items found on U.S. store shelves.

Liam Durbin, Marzetti鈥檚 Chief Information Officer, was brought onboard in December 2018 by Marzetti鈥檚 CEO, Dave Ciezinski, who had worked with Durbin previously at Heinz. Durbin was charged with replacing Marzetti鈥檚 legacy green-screen PRISM software, which had become outdated, with a modern ERP system.

After a competitive bidding process, 麻豆原创 was chosen as the new ERP system. Durbin says 麻豆原创 was selected in part because of its dominance in the industry, which aligned well with Marzetti’s business requirements.

Tailwind

The transformation project, known as Project Ascent to reflect its aspirational nature, received board approval within months of Durbin joining, and by April 2019 the company had begun hiring personnel for the project with Capgemini as the system integrator.

Durbin emphasized the strong support the project received from both the CEO and the board鈥攕upport which he said 鈥渃reated a lot of tailwind鈥� for a project they saw as crucial to ensure the company’s future success.

鈥淭he CEO and the board were clear that they wanted the 鈥楢 players鈥� for the project, creating a dream team to ensure its success,鈥� Durbin said, so they rented a new building to house the project team, providing separation from the main office and allowing the team to focus on the project. This approach ensured that the project team had the necessary resources and environment to work effectively and deliver the project on time, Durbin said.

The initial plan was to execute the project and move to 麻豆原创 S/4HANA Cloud running on Microsoft Azure in four waves, but it eventually became six waves because of COVID-19. The pandemic forced the team to send everyone home, adding an extra year to the project timeline.

Implementation waves

To adapt, they created wave zero, which involved moving a facility in New Jersey鈥攐ne of about 16 facilities overall鈥攐nto 麻豆原创 from a technical perspective. 鈥淭his allowed us to kick the tires and make sure the functionality worked,鈥� Durbin said.

The project team also implemented during this extra time. Overall, the phased approach allowed the team to manage risks and ensure that each wave was successfully completed before moving on to the next.听For example, wave one covered finance, trade, procurement, and customer support鈥斺�渆verything touching the customer,鈥� Durbin said, adding that waves two, three, and four went pretty much as planned. 鈥淲e chose to split wave four in two to de-risk it because it contained two large facilities,鈥� he added.

Project Ascent is now considered complete, and over the past two years the IT team has focused on standing up the product organization and building relationships between product owners and department heads. The product owners, who were part of the project team, now work closely with their respective departments to prioritize and implement enhancements. Durbin said this structure ensures that the company continues to optimize and improve its ERP system, delivering ongoing value to the business.听

Master data project and analytics

As part of the final wave, the team undertook a master data project to ensure data accuracy and consistency across the organization. By standardizing and cleaning the master data, the company improved its ability to make data-driven decisions and enhance overall business operations.

The company chose Microsoft for its analytics platform, which, Durbin said, 鈥渁llowed us to keep the clean core so we now do most of our reporting and analytics on the Microsoft platform.鈥� 听

He said one of the objectives of the project is to democratize access to data within the company. As part of this process, the team is trying to build a community of super users who can create reports themselves using Power BI and Power Platform, 鈥渟o the democratization is underway,鈥� he said while acknowledging that those employees in operations 鈥渁re going to need some help.鈥�

AI projects

The company already has several AI projects underway, including an accounts payable (AP) automation project using optical character recognition to streamline the process and reduce manual effort.听鈥淚n addition to projects like AP automation, we are also very excited to see what AI capabilities 麻豆原创 will be adding to its products,鈥� Durbin said.

Looking back at the Project Ascent, he highlighted the importance of having a fully-staffed organizational change management team for 麻豆原创 training and change management. He said the team played a crucial role in ensuring the project was rolled out on time and provided training and support to employees, helping users鈥攕ome of whom had never used a computer mouse鈥攁dapt to the new system.

鈥淭he amount of work involved in training people on how to interact with 麻豆原创 was a lot bigger than we thought because how technology has changed,鈥� Durbin said, adding that another challenge has been recruitment. 鈥淎s COVID-19 started to ebb and people were starting to go back into their jobs鈥攁nd this condition still persists today鈥攁 lot of factories and manufacturing businesses have had difficulty hiring hourly workers again.鈥�

鈥淪ome of the glamour of a well-paying manufacturing job has sort of gone away in America, and I think other companies, other countries as well, need to restore that,鈥� he said. 鈥淪o, we’ve had to deal with high turnover in some of our locations. Turnover is a wild card, and for the success of a project you just can’t understate it.鈥�

In addition to groceries and food, the group sells electronics services and has around 400,000 customers, along with 80,000 business clients and more than 1,800 suppliers, according to Vital CIO and CTO Alexander Gonzalez.

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Gonzalez is part of a new executive committee that is leading with the purpose of seeking to expand company reach, improve efficiency, and strengthen its market position.

鈥淚t all started in 2018, when we decided to have an analytics system and a clean core 麻豆原创 system to make all the data available to all the different parts of the company so they can make real-time decisions on purchasing and pricing for our customers,鈥� he said.

Gonzalez explained that this is particularly important in a nation like Argentina because prices are extremely volatile. 鈥淚t’s important for us to have that information readily available because Argentina is a highly inflationary country, where prices change really quickly,鈥� he said. For example, during the COVID-19 pandemic Vital sometimes had to change 20,000 product prices in less than a day, 鈥渟o we have to do all of that analysis really fast.鈥�

Vital was a long-time 麻豆原创 customer, but when it came to choosing a digital transformation technology partner, the company did its due diligence.

“One of the main reasons we chose 麻豆原创 [S/4HANA] is we were used to using 麻豆原创,鈥� says Gonzalez. 鈥淏ut we did do our homework. We analyzed our business and processes for a year, then we took six months to talk with a lot of suppliers, 麻豆原创 included, and another three.鈥�

Ultimately, he said Vital decided on 麻豆原创 S/4HANA because it offered the potential to integrate a customer activity repository with its basic financial and core systems.

It took Vital 18 months to implement, but Gonzalez said the system 鈥渋ntegrated with our providers on the first day and we had all this real-time data within a week of going live. So that was great for us.鈥�

As a result, analytics that used to take three to four days can now be done in two hours and Vital can have a new pricing structure implemented in less three hours. Instead of employees wrangling Excel spreadsheets, Gonzalez said decisions are now based on real-time data and 鈥渁re not influenced by what a person wants, but by what the data is telling them to do.鈥�

Because all the company鈥檚 data — including customer data and POS data — are stored in a centralized customer activity repository, Vital now has complete visibility into that data and can use algorithms to predict sales and set prices and distribution priorities. 鈥淲e can change our pricing policy based on reception of goods and new purchase orders and adopt new pricing in real time,鈥� said Gonzalez.

Over the last year, he says, Vital saved around $35 million on perishables after the system warned managers that they would not be able to sell products on time. 鈥淲e negotiated with our suppliers; we made offers and made predictions of how it would work out and it turned into a real savings — that鈥檚 what technology is doing for our company.鈥�

Just as importantly, Gonzalez said Vital now works with one version of the truth. 鈥淚n all of the applications every user sees the same data, be it clustered by store or by department. The result is the same for everyone. There’s no difference in what the financial department sees, what operations see, what our buying department sees, or what our pricing department sees. All the data is clustered in one huge data center.鈥�

鈥淭he technology has really advanced how our users in the company experience data and decision making,鈥� Gonzalez added. Instead of spending time pouring over spreadsheets and reports, much of the analytical work is now done by the system, enabling users to make decisions in real time, for example, while they are negotiating with a supplier.

Now Vital is in the process of migrating all its applications, including its ERP, to the cloud. 鈥淎ll our applications are cloud-ready, and we maintain a clean core, so we can upgrade really fast,鈥� said Gonzalez, who expects to be ready to make that the move by the end of the year. 听

The Vital CIO and CTO is also looking to AI to help the company鈥檚 employees make even better purchase and pricing decisions. 鈥淲e don鈥檛 see AI as replacing our personnel or people in the industry,鈥� he said. 鈥淲e see it at enhancement, we see it as turbocharging our system and making the data more reliable and useful.鈥�

Gonzalez believes that other companies can learn from Vital鈥檚 experience democratizing access to data.

鈥淎 lot of companies regard their data as really private and don’t share it with everyone in the company,鈥� he noted. 鈥淲e are open with the data. We tell everyone– from our people in the stores to our managers and our directors — that they have all the same data. This has really opened us up to be a really integrated and group-friendly company.鈥�

In a kickoff keynote at the Orlando event, they unveiled a raft of new AI tools, business apps, and partnerships designed to help customers overcome these challenges, transform their operations, and 鈥渂ring out your best.鈥�

Uncertainty

鈥淎ll of us face one problem 鈥� every company, no matter which industry or geography. And that problem is uncertainty,鈥� said Klein. 鈥淯ncertainty about trade disruption, about new regulatory requirements, and about how AI will transform my business and impact my workforce.鈥�

麻豆原创 can鈥檛 take away macroeconomic uncertainty, he said, 鈥淏ut you have my commitment that we will help your business become more resilient and more agile 鈥� especially in times like these. We will help you bring out your best.鈥�

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Flywheel effect

麻豆原创 can do this by utilizing what Klein and other senior 麻豆原创 executives called the 鈥渇lywheel effect,鈥� explaining that in physics this is about bringing individual elements together to create new energy.

鈥淭he first element of the 麻豆原创 flywheel is our applications,鈥� Klein explained. 鈥淣ot only do we have the broadest application portfolio in our industry, we also run the most-mission critical business processes end-to-end. No one understands business and industry like 麻豆原创 does.鈥�

The second element of the flywheel is data. 鈥淭he apps give us the richest treasure of mission-critical business data, and no other tech company has more access to semantically rich business data,鈥� he said.

This data then feeds into the third element of the flywheel: AI. Having access to an enormous amount of business data is key to developing extremely powerful Business AI.

麻豆原创 Business Suite

鈥淭hen we make the flywheel spin by infusing AI back into the apps, which run your company,鈥� Klein said before introducing the first of several on-stage demos showing how a company can manage uncertainty like shifting tariffs with the power of 麻豆原创 Business Suite and AI.

Expanding the flywheel theme, Muhammad Alam, member of the Executive Board of 麻豆原创 SE leading 麻豆原创 Product and Engineering, noted that the demo highlighted how the flywheel of apps, data, and AI is critical to the company鈥檚 quest to reimagine business applications.

To achieve this, a company needs an application suite that is end-to-end and seamlessly integrated; a data layer that provides a harmonized data model with high-quality data, strong governance and a rich semantical context; and AI that is built on high-quality data and natively available in the apps used every day.

Alam noted that while the concept of the flywheel effect isn鈥檛 new and most company CIOs have been working hard to achieve it, they have been frustrated by the disparate and heterogeneous applications landscape often built up over time out of necessity.

Fragile balance

Most companies spend a significant amount of time and money integrating the apps they use together and extracting and bringing together disparate data sets. 鈥淚n fact,鈥� Alam said, 鈥淲e estimate that organizations can spend up to 80 percent of their effort and budget in putting together this fragile balance of apps and data, leaving only 20 percent of your resources to focus on value creation.鈥�

While this fragile balance has existed for a while, he explained that it breaks down completely in the age of AI, because to create exponential value you need to have your data available with the end-to-end business process context. 鈥淓nabling this in a disparate, disconnected landscape is close to impossible,鈥� he said.

The only real solution is to move to a best of breed as a suite, or what 麻豆原创 calls 鈥渟uite-as-a- service,鈥� Alam told the audience. 鈥淭he new SaaS is what will allow you to take advantage of the flywheel effect.鈥�

鈥淚n the age of AI, true differentiation will lie in how you create value from this end-to-end context for your organization,鈥� he said. 鈥淭his can only happen when you simplify and innovate your core, and not add another layer of complexity to your landscape.鈥�

This is what the 麻豆原创 Business Suite offers.

麻豆原创 Business Data Cloud

Klein and Alam also emphasized the importance of the launch of 麻豆原创 Business Data Cloud in February and its positive reception from customers and partners. Klein described it as 鈥渢he crystal ball we need in times of uncertainty, because it offers you the biggest semantical data layer in the industry harmonizing 麻豆原创 and non-麻豆原创 data.鈥�

Klein also announced the expansion of business data analysis capabilities in 麻豆原创 Business Data Cloud through a new partnership with Palantir, while Alam unveiled a new partnership with Adobe to develop an intelligent application on 麻豆原创 Business Data Cloud that combines 麻豆原创 Cloud ERP data with data in the Adobe Experience Platform.

To enhance the power of the flywheel, Klein and Philipp Herzig, CTO and chief AI officer of 麻豆原创, also made a series of AI-related announcements. 鈥淎t 麻豆原创, our goal is to make every end user 30 percent more productive,鈥� said Klein.

Joule

To achieve this goal, 麻豆原创 is enabling end users to use human language to interact with Joule, 麻豆原创鈥檚 generative AI copilot, as our new UX, he said. Joule will provide answers to any business questions they have, while in the backend, very smart Joule Agents will take over tasks from employees across end-to-end processes.

鈥淭oday we are proud to announce that we are making Joule available to you everywhere and giving you answers on everything,鈥� the 麻豆原创 CEO said. By combining Joule with WalkMe, the adoption platform acquired by 麻豆原创 last year, Joule becomes an omnipresent, always-on, proactive, and personalized AI assistant.

鈥淣o matter in which app the end user is working, 麻豆原创 or non-麻豆原创, Joule will be everywhere,鈥� Klein said.

In addition to making Joule available everywhere, 麻豆原创 is also enabling Joule to answer everything through a new partnership with Perplexity whose CEO, Aravind Srinivas, joined Klein onstage to demonstrate how Perplexity鈥檚 answer engine will integrate with 麻豆原创 data to provide trusted answers to everyday business questions.

Business AI

During his keynote section, Herzig highlighted the progress made with 麻豆原创 Business AI. 鈥淲e committed that 80 percent of our most-used transactions would be managed via Joule, and we have delivered more than 1,600 skills supporting a wide range of tasks across HR, finance, supply chain, and more out-of-the-box,鈥� he said. 鈥淲e also introduced Joule for developers and Joule for consultants, helping tens of thousands of people every day to achieve more.鈥�

Herzig said 麻豆原创 is on track to deliver more than 400 AI scenarios by the end of this year, and he is thrilled to see more than 34,000 customers are already using 麻豆原创 Business AI every day to transform the way they work.

For example, he shared that British Telecom is already saving 85 percent of the time it took to find the right skilled candidates for jobs with Joule, which is also helping employees to complete HR tasks in 40 percent less time.

鈥淥ur AI strategy is super simple, it鈥檚 really about three things,鈥� Herzig said. 鈥淛oule as the new UI in the age of AI, its Joule Agents to reimagine business processes and AI Foundation on 麻豆原创 BTP, which is becoming the operating system for AI.鈥�

Joule Agents

While Joule transforms the experience layer, Herzig said, Joule Agents are transforming the business process layer, 鈥渞eimagining business processes from the ground up.鈥� Instead of designing enterprise apps around the principle of 鈥渋nsight-to-action,鈥� Joule Agents streamline decision-making through reasoning and action.

鈥淲ith this, we are making a paradigm shift in enterprise software, going really from insight to action to reason and action with AI,鈥� Herzig said. 鈥淛oule Agents will take your business processes to a completely new level.鈥�  Soon, he said, companies will have a huge team of agents 鈥� Joule Agents, third-party agents, and custom agents built in Joule Studio 鈥� as part of their workforce.

To control and govern these agents, Herzig announced the launch of AI agent hub in 麻豆原创 LeanIX. 鈥溌槎乖� LeanIX already knows your business processes and enterprise application landscape, so it was just a logical step to expand the methodology to Joule Agents too,鈥� he said.

Among other innovations, Herzig announced that 麻豆原创 is introducing more than 60 new and updated capabilities into AI Foundation, including a prompt optimizer in AI Foundation developed in joint collaboration with Not Diamond, a frontier AI lab out of San Francisco. Prompt optimizerautomatically converts existing prompts to different models, and a futuristic new partnership with Neura Robotics and Nvidia is designed to blend digital and physical worlds and help empower humanoid robots to achieve business outcomes.

麻豆原创 runs 麻豆原创

Rounding out the kickoff keynote, Sebastian Steinhaeuser, chief operating officer and newest member of the Executive Board of 麻豆原创 SE, explained how the company has achieved considerable gains by running its own operations on 麻豆原创 using the combined power of apps, data, and AI.

鈥淲ith Joule, our developers, consultants, and HR are seeing strong efficiency benefits today. Across 麻豆原创, we track several hundreds of millions in AI-powered efficiency gains committed to our budget.鈥�

Steinhaeuser also discussed the benefits of 麻豆原创 Business Data Cloud, noting, “Earlier this year, we became customer zero of 麻豆原创 Business Data Cloud, offering us distinct advantages: First, we can connect all data in one semantically rich data layer. Second, this helps us generate better insights faster, and across our financial, workforce, and sales planning. And third, we can fuel even better Business AI.鈥� Next up, he said, we are excited to go live with the first set of intelligent applications, starting with People Intelligence.

Moving to 麻豆原创鈥檚 own app layer, Steinhaeuser shared more about 麻豆原创鈥檚 own RISE with 麻豆原创 journey. He also emphasized the importance of tools like 麻豆原创 Signavio and 麻豆原创 LeanIX in mapping process landscapes and enterprise architecture, for 麻豆原创’s own transformation journey. 鈥淢any of our meetings no longer start with PowerPoint, instead we use Signavio and LeanIX to discuss how we can improve our processes and architecture,鈥� he said.

Summary

Summing up the keynote messages, Christian Klein said: 鈥淭ogether we have seen how the 麻豆原创 Business Suite infused with Business AI can help you in times of uncertainty, and how we help you to get there faster, simpler, and at lower cost.鈥�

鈥淟et me finish this keynote with a personal commitment which is really dear to my heart: We will continue to listen to your needs, we will continue to deliver great innovations, and we will stay by your side along the entire journey 鈥� especially in times of uncertainty 鈥� so that you can run your business in sheer harmony.鈥�

Retailers are looking at new technology tools like AI to help them move into new channels and discover new growth streams, enter new markets and find new ways to engage with consumers, and work with suppliers to find efficiencies in their supply chain, Kristin Howell, 麻豆原创鈥檚 global vice president of Retail Solution Management, said.

鈥淭here is a tremendous market out there for retailers to utilize AI and improve their business processes,鈥� she said during an open theater session at the 麻豆原创 booth during the show.

Over two days, retailers who came to the 麻豆原创 booth spoke about the challenges they face, talked about data, data management, and the opportunities presented by AI, and heard about how new solutions and services from 麻豆原创 tailored specifically to the retail sector can help them become more efficient and serve their customers better.

麻豆原创 officially launched the at the show. The new solution helps centralize operational data and can integrate finance, procurement, and merchandising processes.

“Whether you’re a franchisee with a handful of stores or the biggest retailer out there, there’s a certain level of complexity that comes with running any retail business, especially with consumers who expect a very flexible fulfillment experience,” Howell said during a press briefing. “In order to really fulfill these expectations profitably and meet the needs of these consumers, we believe that this retail-tailored ERP solution is going to make the difference for them.”

麻豆原创 also announced plans to bolster its retail offerings with two new tools鈥攁 refreshed loyalty management cloud service and a generative AI assistant designed to give store employees and consumers an easier way to find what they need.

麻豆原创 S/4HANA Cloud Public Edition retail, fashion, and vertical business is available immediately, while the shopping assistant, which is based on听, 麻豆原创鈥檚 unified copilot, will be released during the first half of 2025.听

The shopping assistant is designed to make recommendations and help shoppers find what they are looking for more easily while also helping store associates close sales. Because it can be integrated into the retailer鈥檚 ERP system, users can discover specific information, like the current availability of stock.

The new loyalty management application takes data from 麻豆原创 S/4HANA Cloud and applies AI to create profiles around customers and their shopping behavior and preferences.

Howell identified the customer experience in retail, including product recommendations and helping consumers search, 鈥渁s areas where retailers can start consuming AI.鈥� She also expects retailers to be early adopters of AI tools to help with their pricing strategies and to use generative AI copilots, including 麻豆原创鈥檚 offering, to ask questions and get answers immediately鈥攁bout inventory for example鈥攚herever they are.

While it’s still early days in terms of adoption, almost every retailer presenting in the 麻豆原创 booth theater at the show said they are preparing to implement AI tools and some said they are already testing AI tools in specific use cases. And 麻豆原创鈥檚 retail team made it clear at the NRF show that 麻豆原创 is ready to help.

The company has expanded its international operations in recent years through organic growth and acquisitions, says Roca Group Digital Transformation Director Jacques Nieuwland. 鈥淲e have had the challenges of most industries in the last years,鈥� he says. 鈥淢y job is to help Roca leverage technology to support the different strategic objectives of the company, which are growth, innovation, operational excellence, and sustainability.鈥�

Global Supply Chain

鈥淲e have a global supply chain for some of our components, so we need to plan in a more agile way,鈥� Nieuwland says. 鈥淲e need to update our planning and we need to be able to put in some buffers to have a resilient supply chain.鈥�

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Nieuwland says technology helps by giving Roca greater visibility into its supply chain. 鈥淓verybody collaborates against the same processes with the same data. We include our own value chain and also the value chain of our suppliers and customers,鈥� he says. 鈥淎nd this enhanced visibility allows us to optimize the whole value chain and to take the right decisions.鈥�

麻豆原创 is the backbone of the company鈥檚 application landscape, he says: 鈥淲e perform our core processes, which include order processing, reordering planning, and many others via 麻豆原创 solutions. It helps us because it gives us a structure of processes, of data, and of reports that allow us to understand our business, to replicate it, to scale it, and to continuously improve it.鈥�

Roca uses the solution to help it anticipate the demand for specific products and adjust production accordingly. That way, Nieuwland says, 鈥渨e are able to give an excellent service and to optimize stocks.鈥�

Long-Term Partnership

Nieuwland says Roca Group chose 麻豆原创 to be its technology partner because of its long-term relationship with 麻豆原创 and because 麻豆原创 is a leader in many of the solutions Roca needed. 鈥淲e have a long history of collaboration and have been successful. [鈥 We trust the technology, the digital supply chain solution, [and] the business network solution. We like to work with leading solutions 鈥� we trust them.鈥�

Earlier this year Roca selected and is preparing to go live with 麻豆原创 S/4HANA Cloud at the beginning of 2025 for the next phase of its digital transformation 鈥� a move that Nieuwland believes will enable even more innovation. 鈥淲e have chosen the cloud-based solution because 麻豆原创 innovates first on the cloud-based solution and we want to leverage that innovation,鈥� he says.

He adds that the integration of 麻豆原创鈥檚 generative AI copilot into 麻豆原创鈥檚 cloud ERP will also fuel innovation and productivity. 鈥淲e think there is huge potential to increase our productivity,鈥� he says. More generally, he says 麻豆原创鈥檚 cutting-edge technology will help Roca improve its service to customers and interact better with them, as well as help the company achieve operational excellence including, for example, reducing waste and improving sustainability.

Sustainability

On sustainability, Nieuwland says Roca Group is studying scope 1, scope 2, and scope 3 emissions. It has already set yearly targets for the reduction of CO2 and wants to be carbon neutral by 2045. More generally, he says Roca鈥檚 goal is to deliver 鈥渢he best bathroom experience for customers worldwide.鈥�

Asked what other manufacturers can learn from Roca鈥檚 experience, he says: 鈥淚t’s very important to start with a business problem, a business challenge, and put technology at the service of generating business value. Then it’s very important to work in cross-functional teams. So, this is not about buying hundreds of solutions to solve isolated problems. We need to think on a bigger scale and to work together to find the best solution to our challenges and use few solutions and have an enterprise architecture that support our goals.鈥�

颅颅颅鈥淲e are a local club in Bavaria, but have fans around the globe,鈥� says Stefan Mennerich, the club鈥檚 director for digital media and communications. In addition to its 1,200 employees in Munich, New York, Shanghai, and Bangkok, the club has around 175 million followers on its social media and its own media platforms.

Mennerich says the club鈥檚 digital and media platforms are very important because fans expect to be able to interact with their club wherever they are. 鈥淭hey want to send us their feedback and they want to receive feedback.鈥�

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Fans Are Everything

The fans are at the center of everything FC Bayern does, Mennerich confirms: 鈥淥ur aim is to optimize all the processes for them, so they have the best user experience. Technology helps us with personalization, with the sales processes, with content 鈥� with everything.鈥�

He says the club chose 麻豆原创 as its technology partner for several reasons, including the fact that FC Bayern has different businesses. 鈥淲e have ticketing, we have merchandising, we have fan experience, we have digital platforms, and 麻豆原创 is able to deliver the best solutions for all these areas.鈥�

He also cites 麻豆原创鈥檚 commitment to continuously develop its cloud-based platforms and says this makes the digital experience 鈥渂etter and better every day.鈥�

The club uses the 麻豆原创 Emarsys Customer Engagement solution to capture fan data and create newsletters and personalized content for them, and the 麻豆原创 Customer Checkout application for point-of-sale management and real-time sales and stock updates.

鈥淲e have around 50,000 transactions every match day in the Allianz Arena, and we use 麻豆原创 Customer Checkout for that,鈥� Mennerich explains. 鈥淔ans can buy their merchandise articles, they can buy food or beverages, they can walk into our restaurants and pay there with 麻豆原创 Customer Checkout.鈥�

Separately, 麻豆原创 Event Ticketing software handles ticketing at FC Bayern; not just for football fans, but also for its basketball team and museum. The club also uses 麻豆原创 tools for its employees. For example, the AI-infused 麻豆原创 SuccessFactors HCM suite gives employees and managers access to an expanding array of human capital management tools.

Personalization

Looking ahead, Mennerich says he believes personalization will become even more important.

鈥淲e want to become better and better and better with personalization. We want to be able to really contact the people one by one, and not to speak about target groups in the future. We want to interact in a truly personal way with the fans.鈥�

He believes that embedding artificial intelligence capabilities in 麻豆原创 solutions will help achieve this aim and that overall, AI will help FC Bayern become more efficient, lower costs, and meet the expectations of the fans.

鈥淥ur biggest aim for the future on the horizon of FC Bayern is to meet every single expectation of any single fan around the globe, be it in Tokyo, be it in Rio de Janeiro, or be it in Munich,鈥� he says. 鈥淲e want to meet the expectations of the fans, and this expectation should be met in real time. This is our big aim for the future.鈥�

Lessons Learned at FC Bayern

If other organizations want to learn from FC Bayern, Mennerich says one lesson is that with a good technology partner like 麻豆原创, even midsize companies with broad business activities like FC Bayern can cover all the bases and be able to be competitive.

鈥淚 think what we are good at is meeting fan expectations via digital platforms,鈥� he says. For that, interactive communication is very important. 鈥淵ou always have to take into account what the fans, other organizations, and customers really expect and want from you. You have to be able to deliver that via digital platforms.鈥�

鈥淭his year is a very special Sapphire,鈥� Klein said. 鈥淲e are entering a new phase of AI, with endless possibilities for us all.鈥�  

Klein and Chief Marketing and Solutions Officer Julia White used the keynote to outline how AI will deliver real business benefits for different corporate functions and 鈥淏ring Out Your Best,鈥� this year鈥檚 event theme.

Delivering on an AI Promise

Klein emphasized how 麻豆原创 has delivered on its promise to infuse generative AI throughout its business portfolio, has enabled customers to exploit the potential of business AI, and has positioned the Joule copilot as the new front end for 麻豆原创 applications.

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Together, the two also announced the next evolution and new capabilities in both RISE with 麻豆原创 and GROW with 麻豆原创. 听Since it was launched over three听years ago, more than 6,000 customers have selected RISE with 麻豆原创. During his keynote, Klein announced that RISE with 麻豆原创 will now include a dedicated enterprise architect to guide customers through the RISE with 麻豆原创 Methodology as well as an integrated tool chain to help manage the process, system, and data landscape holistically across the RISE with 麻豆原创 life cycle.

Meanwhile White, broadcasting live from the central showcase on the 麻豆原创 Sapphire show floor, announced that cloud ERP offering GROW with 麻豆原创 will now include 麻豆原创 Sales Cloud and Concur Expense at no additional charge. Whether its managing your finances or managing your expenses, GROW with 麻豆原创 has you covered, she said.

AI Momentum

Building on 麻豆原创鈥檚 business AI momentum, Klein and White also announced a series of expanded partnerships to help companies make the most out of this decisive AI moment. The expanded partnerships include deals with Amazon Web Services (AWS) and Google Cloud. Klein also announced the integration of Microsoft 365 Copilot with Joule, delivering what he described as a 鈥渢ruly differentiated employee experience.鈥�

Together onstage with customers and 麻豆原创 Chief AI Officer Philipp Herzig, they showcased how 麻豆原创 is infusing generative AI throughout the application portfolio and enabling customers to thrive in the AI era.

鈥淭he business AI innovations we鈥檙e announcing will not only change how people work with 麻豆原创 solutions, but how people work overall,鈥� said Klein ahead of his keynote address.

New Joule Capabilities

Klein announced Joule for consulting capabilities and Joule for ABAP developer capabilities, which will help 麻豆原创鈥檚 6-million-strong consultant and developer community to accelerate projects by 30% and implement 麻豆原创 solutions faster than ever before.

During his keynote he described business AI as being 鈥渁n inflection point鈥� and added, 鈥淭oday鈥檚 AI announcements and partnerships build on our commitment to deliver revolutionary technology that drives real-world results, helping customers unleash the agility and ingenuity they need to succeed in today鈥檚 fast-moving business landscape.鈥�

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鈥溌槎乖� is the only tech company who can infuse AI capabilities right into your business processes and workflows,鈥� he said, saluting the achievements of the 40,000 麻豆原创 employees in the Product Development organization.

Shout Out to 麻豆原创 Developers

鈥淣o other tech company can offer a more powerful platform to transform enterprises to rewrite how business is run.鈥� 麻豆原创 developers have transformed 麻豆原创鈥檚 portfolio 鈥渇rom an ERP system that enabled transactions in real time, to a system with modular applications and embedded AI so that you can run intelligent, connected, and sustainable enterprises.鈥�

鈥淲e promised this to you, and we delivered,鈥� Klein told audiences online and the 14,000 customers and partners attending 麻豆原创 Sapphire in person this week in Orlando. 鈥淣ow we are using the power of generative AI across our stack to once again revolutionize how businesses run and end users will work in the future.鈥�

After announcing generative AI copilot Joule in September 2023, Klein confirmed that it will become the new front-end and UX for 麻豆原创 applications and 鈥渨ill turn your words into action.鈥� Joule is ready for prime time, he declared, 鈥渁nd going forward, it will be embedded out of the box for all our cloud customers.鈥�

Joule: Key to Higher Productivity

He predicted that Joule will also become the biggest productivity engine for every 麻豆原创 end user, and that by the end of the year, 80% of the most used tasks will be managed via Joule and the 300 million end users of 麻豆原创 products will be 20% more productive.

While AI is a powerful technology facilitating huge opportunities for business and employees, the 麻豆原创 CEO emphasized that it is also crucial to offer responsible AI. To that end, he announced that 麻豆原创 is among the first tech companies to adhere to UNESCO鈥檚 AI principles.

Klein wrapped up the keynote by emphasizing that 麻豆原创 does not view AI as an end in itself, but rather as a tool to help the world run better and improve people鈥檚 lives. 鈥淵ou have my commitment that we will continue to listen to your needs, we will continue to deliver great innovations and we will continue to deliver great outcomes for your company.鈥�

Paul Saunders, head of Product Strategy and chief evangelist of Cloud ERP for鈥槎乖粹�疭/4HANA put it this way during a : 鈥淭rust is not the engine oil, it鈥檚 the essence of business.鈥�

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In the interview, Saunders explains this and other aspects of the changing relationship between humans. The former Gartner analyst believes that this changed relationship has pushed trust to the top of the corporate agenda and made 麻豆原创鈥檚 commitment to relevant, reliable, and responsible business AI all the more crucial.

鈥淭he relationship between 麻豆原创 and our customers for the longest time was transactional,鈥� he says. But the shift to the cloud has changed that. From the customer鈥檚 perspective, in a cloud environment the SaaS vendor is effectively running the business and that requires a whole new level of trust.

As Saunders notes, “When a data center goes down the customer can’t just say, ‘Hey Bob, get down to the computer room and reboot the box.’ Now, with AI, it’s not just the data we’re providing, but information and recommendations. And some of those recommendations might challenge what the person thinks intuitively.”

For example, when Saunders was CIO of a golf cart maker in Georgia that shipped the carts all over the United States, he put in an early AI-based route planning package designed to optimize the deliveries of the carts to customers across the country.  

But despite the potential efficiency gains promised by the technology, the CEO who had run the company for 40 years and was accustomed to relying on his own judgment overruled the software and insisted that the drivers follow his preferred delivery route.

This resistance to change reflects a broader reluctance to embrace data-driven decision-making, with individuals often interpreting data in a way that reinforces their existing beliefs rather than challenging them.

When faced with the suggestion from a machine to do something different, most people will only follow the advice if they have solid confidence in the accuracy of the underlying data and can retain oversight of the process. 

That, according to Saunders, plays to 麻豆原创鈥檚 advantage. He acknowledges that 麻豆原创 is sometimes considered to be 鈥渁 little bit old fashioned,” but also thought of as “incredibly reliable and trustworthy.鈥� 

In such a fast-changing and unpredictable environment 鈥� one in which many experts, including Saunders, predict that at least one big brand name company will be in the news 鈥渇or doing something terrible with AI鈥� 鈥� 麻豆原创鈥檚 commitment to delivering dependable solutions infused with relevant, reliable, and responsible business AI is key. 

For Saunders, the importance of fostering trust and confidence in both the technology itself and the organizations deploying it, particularly in industries where risk aversion and conservatism are prevalent, cannot be overstated.  

But he also believes that organizations need to strike a balance between automation and human intervention, recognizing that while AI can streamline processes and improve efficiency, human judgment and oversight remain essential for ensuring the accuracy and reliability of AI-generated insights.  

In the end, what really matters to customers is not the technology itself, but the business value that it creates. 鈥淚f you go to any CEO or CFO, they will tell you they only care about three things: revenue, cost, and risk. That鈥檚 it.鈥�

Ultimately, he says, 鈥淓verything we do has to show the business value.鈥� 

Like many other farmers on Kalangala, Berna started growing oil palm trees in 2012 while emphasizing sustainability and avoiding the deforestation and other issues associated with oil palm farming in some parts of the world.

Oil palm trees bear the fruit that makes palm oil, a much more reliable and lucrative crop than the cash crops they were producing previously. 鈥淲hen we were farming cassava, bananas, and coffee, we were affected by monkeys. They came and destroyed our crops,鈥� she says.

She also explains that she had to leave home and go to the market to find a buyer for the crops that survived the monkey attacks and never knew in advance how much they would fetch. 鈥淥ur living conditions where bad,鈥� she remembers. She and her family lived in a makeshift timber house. 鈥淚n the night when we were sleeping, winds would come and destroy our houses and our children fell sick almost every day.”

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Change

That began to change when Berna began working with the Kalangala Oil Palm Growers Trust (KOPGT) and the family planted their first oil palm trees in 2012. They expanded their crop in 2019 and again in 2022. In Kalangala, many of the people are oil palm farmers. 鈥淲hen a day starts, some of my family members help me with the pruning,鈥� she says. 鈥淭he others go to the plantation and do other activities.鈥�

As part of its mission, KOPGT teaches farmers better agricultural practices. But perhaps most importantly, it has created a transparent payment system so farmers get paid faster and know if what they鈥檙e getting paid is accurate, increasing the standard of living of the farmers and, subsequently, much of the island itself.

As the number of farmers and transactions increased, KOPGT needed a digital solution to enable continued growth. Since 2009, 麻豆原创 has worked to create applications that help smallholder farmers in developing nations, primarily across Africa, enhance food production.

David Balironda, KOPGT鈥檚 general manager, explains that the trust鈥檚 system is based on 麻豆原创 Rural Sourcing Management, which can digitally record information on producers, their farms, and communities at every level of the value chain. This helps provide visibility and allows parties to easily and quickly communicate with each other.

Sustainability

Underscoring the importance of sustainability to KOPGT, the trust conducted an initial environmental impact assessment before launching the project and uses to monitor the farmer plantings and ensure they are in compliance with the National Environment Management Authority guidelines.

麻豆原创 cloud technology also enables KOPGT to ensure that the oil palm planting meets the most stringent sustainability guidelines set by Uganda鈥檚 National Environmental Authority. 鈥淲e are in the process of applying for that certification by the Roundtable on Sustainable Palm Oil to make sure that we work within those guidelines,鈥� says Fredrick Sulwe, KOPGT鈥檚 finance and administration manager.

As part of KOPGT鈥檚 commitment to sustainability, the trust maintains a lake buffer zone between the planting and the lake itself and even rehabilitates those areas that have been damaged by other plantings. 鈥淩estoration of those areas 鈥� the lake buffer zones 鈥� is key,鈥� says Sulwe.

In addition to maintaining the buffer zones, the trust also follows recommendations for the stocking of trees and ensures that no chemicals or herbicides are used. 鈥淎s we increase household income, we must keep an environment that is free of any distortion by the project,鈥� explains Sulwe.

The KOPGT system allows the farmers to input information about their crops using the lead farmer鈥檚 mobile phone and enables them to receive information and advice back from the trust. The system also includes a mapping feature that has helped farmers to know exactly how much land they are farming. 鈥淭hat means when I go to the bank to get a loan, I鈥檓 sure of the size of my lot,鈥� explains Berna.

In addition, she also knows exactly how much of the loan is outstanding and when it needs to be repaid. 鈥淧reviously, we would almost spend a year without knowing the status of our loan,鈥� she says. 鈥淣ow we can learn the status of our loans monthly. This never existed before.鈥�

Better Information

She also credits the system with making her a better and more informed oil palm farmer. 鈥淎t the end of the month I get an SMS that shows how much I have harvested from my lot,鈥� she says. Before the system came online, she says the family was spending a lot of money on transport going to and from the KOPGT office.

鈥淥il palm has not only impacted my life, but also the community,鈥� she says. 鈥淭here are many farmers who are like me who have built houses and some have bought cars. They have used the money they got from oil palm to start new businesses on Kalangala and outside.”

Big Dreams

Berna says her hopes and dreams are enormous. 鈥淚 have started to achieve some of them,鈥� she says. 鈥淣ow, because I have a permanent house, I am able to sleep well, my children no longer get sick, and I鈥檓 sure that the winds won鈥檛 take my house.鈥�

鈥淣ow, we are able to take our children to school. We can live a decent life. We have some place to stay, and we get paid every month. We are sure that our life has greatly changed,鈥� she adds. And although she doesn鈥檛 yet own a car, she hopes to learn to drive in the coming years.

Meanwhile, she says she wants to thank everyone for their help. 鈥淲hat gives me confidence is we have good officers at KOPGT that have tried to give us a good direction. We hope that when they continue doing what they are doing our lives will be impacted greatly.鈥�

Berna鈥檚 confidence and newly found optimism reflects the success of the vegetable oil program on Kalangala island. Because palm fruits can be harvested throughout the year 鈥� compared to one or two seasonal harvests 鈥� and have high yields, palm farming has become a viable alternative for the residents.

Palm oil is already the most widely used vegetable oil on the planet, with about 71 million tons consumed in 2021. And there is not only a domestic need, but also a demand from the foreign market that Ugandan smallholder farmers like Berna鈥檚 family and neighbors can help fill.

But in order to succeed, the leaders of consumer goods (CPG) companies need to undertake five strategic actions, say the report鈥檚 authors 鈥� Wesley Spindler, Accenture鈥檚 global lead for Circular Economy, and E.J. Kenney, 麻豆原创鈥檚 SVP for the Consumer Products Industry.

鈥淎s we approach the midpoint of the Decade of Action, packaging 鈥� and in particular plastic packaging 鈥� continues to be a priority for consumer goods companies in their efforts to deliver both business and sustainability value,鈥� say the two authors in the introduction to the report. 鈥淧ackaging ensures safe delivery and consumption of essential products to billions of people every day. However, it has also generated a lot of waste and pollution. If circular packaging solutions do not start to scale, by 2050 there could be more plastic than fish in the ocean.鈥�

They note that CPG packaging is a tremendously difficult problem to solve given the complexity of the packaging value chain and the frequent lack of acknowledgment of a circular business case. Current regulations along with increased stakeholder pressure add urgency and reinforce how interconnected sustainability and business efforts have become.

鈥淧ackaging is a waste challenge, a climate challenge, and a human health challenge,鈥� the authors say while noting that the consumer goods industry is currently off track in addressing plastic packaging pollution. Packaging is the biggest contributor to plastic pollution and accounts for nearly 40% of global plastic demand that almost exclusively becomes waste.

Worryingly, they note that plastic commitments are falling flat and, like in most other industries, consumer goods companies lack end-to-end visibility of their packaging supply chain.

Among the European food and drink companies, two-thirds of pledges to go greener on plastic have failed or been dropped. At the same time, the Ellen MacArthur Foundation found that most of the signatory organizations to the UNEP Global Commitment representing 20% of all plastic packaging produced globally will 鈥渧ery likely鈥� not achieve their target of 100% reusable, recyclable, or compostable packaging by 2025, and that collective virgin plastic use of FMCG (fast-moving consumer goods) has also returned to 2018 levels.

But more optimistically they add, 鈥淲e know that these opportunities are there for consumer goods companies that seize them. There has never been a better time to act 鈥� at speed and at scale. [鈥 Drawing on our decades of experience collaborating for the success of our consumer goods clients and deep circular economy expertise, [鈥 we view circular economy as the 鈥楽wiss Army knife鈥� of solutions for this challenge, not only supporting better planetary outcomes, but also delivering significant business value.鈥�

The report, discussed by business leaders during the Global Summit, recommends that consumer goods company leaders address these challenges by undertaking five actions. They should embrace authenticity and transparency, reimagine packaging research and development (R&D), invest in infrastructure, expand and explore circular business models, and collaborate to scale.

Specifically, the authors say standardized sustainability reporting on plastics and the regulatory environment makes it impossible for companies to ignore the call to action. But before they can do so meaningfully, companies need to understand their actual impact 鈥� and be honest about it. Beyond regulations, to successfully implement a circular economy for plastics, companies must prioritize transparency and use data to authentically measure the real impact of new designs.

鈥淢eaningful action starts with authenticity and transparency to drive credible solutions with tangible impact. We must embrace a collective mindset of learning from each other, sharing what works and what doesn鈥檛,鈥� they say in the report.

In addition, they argue that our approach to design must change if we are to create new value through packaging innovation and move towards a future with less and less packaging. 鈥淭he future of packaging will extend the product鈥檚 definition, where, for example, the packaging itself becomes a part of the product, making choice and design of the related technologies and materials even more critical,鈥� they say.

Reimagining packaging R&D across the value chain through advanced design tools, smart packaging, and material innovation will step us forward. Coordinating investment with downstream stakeholders and expanding reuse and circular business models in a systemic way will foster the ecosystem change we need to see. The nature of this challenge makes a multi-stakeholder approach essential.

But implementing innovative solutions also requires infrastructure and community support. Consumer goods companies have historically left recycling responsibilities to the consumer, but society increasingly expects business to take an active role beyond the design and use of their packaging and to contribute to its collection, reuse, and recycling.

Fortunately, the authors note the business model for circularity is growing stronger as companies step up their innovation and commitment. 鈥淪hifting 20% of plastic packaging to a reuse model is in fact a more than US$10 billion business opportunity and represents untapped potential for improving the consumer experience and increasing brand loyalty.鈥�

The report also argues that collaboration is one of the critical and necessary components for circular packaging to gain traction. 鈥淐onsumer goods companies can join forces with partners across the value chain 鈥� such as packaging suppliers, retailers, end consumers, waste managers, and recyclers 鈥� to meaningfully advance goals and to unlock shared risk and shared reward.鈥�

Even though consumer goods leaders face a growing mountain of regulatory challenges and complexity, they conclude that it鈥檚 clear that progress is possible, saying, 鈥淭here is a path forward to a sustainable packaging future.鈥�

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鈥淔ifty years ago 麻豆原创 built the first ERP system, 30 years ago we made real time a reality, and 10 years ago we entered the cloud,鈥� Saueressig said. 鈥淭oday, we are actually innovating together with all of you to redefine enterprise software and future-proof your business entering the era of AI. We’ve been alongside you, your businesses, and your industries with continuous improvement and continuous innovation.鈥�

To kick off the keynote and to showcase a series of demos, Saueressig and Mueller invited two 麻豆原创 colleagues, Lucy Alexander and Sangeetha Jayakumar, onto the 麻豆原创 Sapphire stage in Orlando, Florida. Before diving into the demos and a customer panel that included Topcon, the Women鈥檚 Tennis Association, Henkel, and Nestl茅, Saueressig and Mueller asked the two talents why they chose to work at 麻豆原创.

Alexander said she joined 麻豆原创 because the software industry is the place to have an impact. 鈥淛ust think: 麻豆原创 has helped to produce more smartphones than any smartphone manufacturer, connecting all of us. We’ve also helped to make and distribute more vaccines than anyone else during the pandemic. To me, that’s impact.鈥�

Jayakumar shared that she joined 麻豆原创 because of the company鈥檚 commitment to sustainability. She admires 麻豆原创鈥檚 aspiration toward a future with zero emissions, zero waste, and zero inequality. 鈥淭hat’s why I chose 麻豆原创.鈥�

麻豆原创鈥檚 raft of sustainability solutions for customers was the first of the innovations highlighted by Saueressig and Mueller. 麻豆原创 doubled down on its sustainability initiative in 2020 despite the pandemic, 鈥渂ecause we were, and still are, truly committed to it,鈥� Saueressig said.

The introduction earlier in the day of the green ledger for carbon accounting as part of the cloud ERP offerings RISE with 麻豆原创 and GROW with 麻豆原创 underscores the company鈥檚 continued commitment to enabling customers to truly measure their carbon footprints by moving from average carbon emissions to actuals. 鈥淲e all know that to get to a low-carbon future, you need end-to-end transparency and visibility across the entire supply chain,鈥� Saueressig said.

help turn those fragmented supply chains into collaborative sustainable networks. The launch of 麻豆原创 Business Network for Industries at 麻豆原创 Sapphire is also a key part of the company鈥檚 strategy. 鈥淲e are working on many industry-specific data networks, like Catena-X and Manufacturing-X,鈥� said Saueressig. 鈥淏ut all of these networks are only possible if processes and data are seamlessly integrated.鈥�

Picking up the theme, Mueller said that integration enables completely new possibilities such as synchronized planning, which is a closed loop between planning and execution. It is also automated and network aware.

鈥淥ur extended planning and analytics solutions span across financial planning, workforce planning, and demand planning,鈥� Mueller explained. This allows 麻豆原创 customers to see the impact of their decisions across all their lines of business, as well as planning more holistically.

To help companies extract and harmonize data from their 麻豆原创 and non-麻豆原创 systems, 麻豆原创 recently introduced .

鈥淲ith 麻豆原创 Datasphere, you can create a data model consuming data from different sources like 麻豆原创 S/4HANA Cloud and 麻豆原创 BW/4HANA, and non-麻豆原创 data sources like Google, BigQuery, and others,鈥� Sangeetha explained during her demo. She added that 麻豆原创 Datasphere has a great graphical modeling feature, helping to quickly create a data model with simple drag-and-drop functionality, which can then be visualized in a dashboard in 麻豆原创 Analytics Cloud.

Saueressig cited 麻豆原创 Datasphere as an example of how 麻豆原创 is opening up more than ever, which is why 麻豆原创 has seen the partnerships announced in this area, including Databricks, DataRobot, Collibra, and Confluent, and now Google Cloud. 鈥淲e truly believe in the democratization of data,鈥� he said.

Mueller noted that 麻豆原创 has also recently announced AI partnerships with Aleph Alpha, IBM, and Microsoft. 鈥淏ut our key differentiator for you is how we use those technologies and embed these AI capabilities to reimagine business processes across all 麻豆原创 solutions,鈥� he said.

鈥淭here’s no doubt 麻豆原创 is an AI company and 麻豆原创 AI is built into our systems that power your business,” Saueressig added. As of today, 麻豆原创 has delivered more than 130 embedded use cases of AI .

For example, 麻豆原创 systems processed 40 million invoices automatically last year and generated savings of more than $366 million for customers. Now, generative AI is coming on top and will have widespread implications for a myriad of functions such as job descriptions, interview questions, product descriptions, and queries for analytics. 麻豆原创 is already working on more than 80 use cases for generative AI.

麻豆原创 is differentiating in the AI sphere, because its models are trained on years of business data, and also responsible and trustworthy, Saueressig said.

After demonstrating with Alexander and Jayakumar how AI and natural language processing might be integrated into 麻豆原创 Analytics, Saueressig predicted that AI 鈥渨ill be infused everywhere and enable totally new capabilities in our products.鈥�

Mueller then demonstrated the use of generative AI for development. Currently, he noted, many 麻豆原创 customers use standardized APIs to build future-proof extensions. 鈥淏ut imagine this,鈥� he told the audience. “What if instead of coding myself, I could simply describe what I want, and 麻豆原创 will take care of it? Wouldn’t that be cool? And we are actually making this a reality with generative AI.鈥�

But the power of AI actually goes far beyond efficiency, according to Saueressig, who suggested we could also use AI to reshape the experience between humans and machines: 鈥淚t’s a duet, not a duel.鈥�

The keynote also revolved around how 麻豆原创 has modernized its user interfaces and how it has used collaboration to streamline applications. It was shown how it is possible to improve and automate business processes using 麻豆原创 Signavio solutions and how 麻豆原创 Build and 麻豆原创 Integration Suite can bridge the gap between business and IT.

鈥溌槎乖� enables enterprise automation because we know that you are under a lot of pressure when it comes to efficiency in your organizations and with that you can continuously identify and improve processes,鈥� Mueller said.

During the customer panel, participants explained all the different ways they are using 麻豆原创 to innovate and future-proof their businesses. Then Mueller and Saueressig summed up the key innovations that had been discussed.

鈥淭o summarize all these innovations, we enable risk resilient supply chains,鈥� Saueressig said. 鈥淲e connect your business to a broader network. We help you plan across the business. We infuse AI across the whole portfolio of 麻豆原创 and we want to provide you with a new intuitive user experience and collaboration capabilities, all enabled by our leading .鈥�

鈥淲hen we work together, we will conquer any mountain,鈥� Klein said in a speech that began and ended with climbing metaphors and was punctuated with customer stories, demos, and new product announcements.

麻豆原创 Chief Marketing & Solutions Officer Julia White joined Klein from the Orlando show floor during the keynote to highlight 麻豆原创鈥檚 groundbreaking supply chain and sustainability initiatives, enterprise-wide automation, as well as how 麻豆原创 solutions answer the challenges that senior business leaders across all industries face.

Microsoft, Unilever, Pfizer, Schneider Electric, and Google Cloud were among the big-name partners and customers that appeared on stage or via video during the event. In addition, the keynote featured a recorded video message from John Kerry, United States Special Presidential Envoy for Climate, about how we can solve the climate crisis together.

Klein and White framed the keynote around how the CIO and their key business stakeholders — like the chief people officer, chief commercial officer, and CFO — respond to the challenges they each face, and how 麻豆原创 solutions are helping solve those challenges.

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Klein told the audience in Orlando and those joining virtually: 鈥淐limbing the highest mountain requires a strong team and, let’s face it, the same is true for transforming businesses. It takes a strong team between the business, IT, and 麻豆原创… If we are in this together as one team, we will conquer any mountain.鈥�

麻豆原创鈥檚 vision is focused on the needs to build resilient supply chains, to become an agile intelligent enterprise, and to run a sustainable business, Klein explained. 鈥淲e deliver on this vision through our cloud portfolio.鈥�听

Early in his keynote, Klein said 麻豆原创 will double down on its AI strategy because of the tremendous impact AI will have on our private and business lives. For 50 years, he noted, 麻豆原创 software has been running the world’s most material and workforce-intensive business processes: 鈥淭his is why we are convinced that embedding AI in 麻豆原创 software will deliver enormous value for your business.鈥�

鈥�Today we have already embedded AI in many of our applications that are being used by over 20,000 customers,鈥� he said, 鈥溌槎乖� AI is built for business.鈥�

As an example, he noted that in 麻豆原创鈥檚 finance solution, AI helps to predict and safeguard financial performance by analyzing a company鈥檚 pipelines, workforce, and other profit and loss drivers.

鈥淲e have delivered many AI use cases that boost business process automation and increase productivity by another 15%. Now we see the incredible potential to take AI to the next level,鈥� he said. 鈥�With generative AI, we will increase the productivity of every end user by changing the way people work with our software. For example, our software will be able to answer any business-related question and recommend actions to improve your company’s performance.鈥�

Klein noted that 麻豆原创 has already increased its own R&D investment to develop additional AI use cases and is also entering technology partnerships to expand its AI offerings, including the generative AI partnership announced earlier this week with Microsoft.听

After a demo showing how embedding generative AI into 麻豆原创 SuccessFactors software can enhance recruiting, ongoing learning, and the re-skilling and upskilling of the workforce, White, speaking from the 麻豆原创 Sapphire show floor, spoke with Aaron Rajan, global vice president of Customer Experience Technology at Unilever, about how the company is working with 麻豆原创 to address the growing demands for sustainable vanilla ice cream.

鈥淭hanks to the integration across 麻豆原创 Ariba, 麻豆原创 Business Network, and 麻豆原创 S/4HANA Cloud, we can see a full view of the supplier’s performance metrics — including cost, reliability, and sustainability — making an informed decision not only on supply chain fit, but also on carbon impact,鈥� White said.听

Expanding on the business network theme, Klein noted that it is more critical than ever to not only connect one company with another, but to bring entire industries together, because each industry has its unique challenges and requirements. He also unveiled the new offering 麻豆原创 Business Network for Industry.

To demonstrate the power of the network, Klein cited the life sciences industry. 麻豆原创 has 80 of the largest customers already in the network, with more than 255,000 trading partners managing over $200 billion in commerce every year. He welcomed Lidia Fonseca, chief digital and technology officer at Pfizer, to the stage to explain the value of 麻豆原创 Business Network.

Klein then described the management of a company鈥檚 overall carbon footprint as another key pillar for the success: 鈥淚n addition to the top and the bottom line, consumers, your employees, investors, and auditors, they all want to support enterprises that care about the planet. Today, CFOs and chief sustainability officers need to ensure compliance with 20 times more climate regulations than they had in the past.鈥�

But he noted that hardly any enterprise has a comprehensive view of greenhouse gas emissions. 鈥淭he 麻豆原创 sustainability portfolio will enable you to record, report, and act on actuals, not on averages, based on a green ledger — including scope three.鈥�听

To explore this message, 麻豆原创 CFO Dominik Asam spoke in a prerecorded video with Hilary Maxson, CFO of Schneider Electric, about the challenges CFOs face with carbon accounting and sustainability disclosure. Additionally, White detailed a new set of 麻豆原创 innovations to track and manage emissions, as well as a new green ledger that will work with 麻豆原创鈥檚 cloud ERP to “provide natively integrated financial and environmental decision making at the required point in time.”

After introducing John Kerry鈥檚 video message to attendees, White added, 鈥淲e can meet the climate challenge with a potent combination of technologies, partners in government, and all of you.鈥� Klein then turned to the crucial role that data plays in running enterprises today and the recent launch of 麻豆原创 Datasphere, which enables customers to bring together and harmonize 麻豆原创 and non-麻豆原创 data sources.听

After White and Klein explained how 麻豆原创 Signavio software enables end-to-end business process automation and the unique benefits of RISE with 麻豆原创 and the GROW with 麻豆原创 offering, which targets mid-market customers moving to 麻豆原创 cloud ERP, Klein wrapped up the keynote with an invitation to those in Orlando: 鈥�Today we have seen that conquering the mountains we face requires the wide use of technology and one team. And we invite you to experience the full capabilities of these innovations for yourselves over the next few days.

“As the famous climber once said, ‘Better we raise our skill than lower the climb.’ At 麻豆原创, we are not lowering the climb, we are raising the skills for every role in every line of business to future-proof your business for whatever mountain you need to climb next.鈥�

Over 1.3 million Nigerians have been displaced by the floods, which have killed at least 600 people, destroyed more than 200,000 homes, and hit 32 out of the country鈥檚 36 states. The floods are the worst for more than a decade and have wiped out crops, disrupted drinking water supplies, and turned capital city Lagos into an island surrounded by floodwaters.

Speaking last month during the International Monetary Fund and World Bank Annual Meetings in Washington, DC, Mai Farid of the fund’s African department warned about the impact of the floods, which have also hit Cameroon and Chad, on transport, food production, and prices.

Farid noted that Nigeria is part of the most food-insecure region, the region most vulnerable to climate change and yet the least prepared. She urged the government to invest in infrastructure and technology to help prevent and mitigate the impact of floods and other climate-related natural disasters in the future: “Rebuilding better is something that countries need to take into account since climate change is not going anywhere and is inevitable.鈥�

Nigeria is Africa鈥檚 most populous country and largest economy. Even before the latest flood, it听 faced rising food insecurity as a combination of a mostly informal agriculture sector and growing population puts pressure on the country鈥檚 food resources. According to the , food insecurity increased from six percent of the Nigerian population in 2007 to 13.4% in 2017.

The agriculture sector is the largest contributor to the Nigerian economy and听. However, according to the United Nation (UN) Food and Agriculture Organization, food production in Nigeria is undermined by a number of factors, among them poor planting material and insufficient use of fertilizer, which leads to a growing reliance on food imports.

To help address these issues and support smallholder, the Convention on Business Integrity鈥檚 for-profit arm Innovations Limited, or CBiIL, chose the solution to support 850,000 small maize producers and integrate them into the agricultural value chains.

While West Africa, like Africa as a whole, is still heavily dependent on agriculture, it is home to some of the world鈥檚 fastest growing mega cities like Lagos, so urbanization and the associated environmental issues are top of mind, particularly among young adults.

The region also has a reputation for leap-frogging old technology — first mobile technology and now with cloud computing. In Nigeria itself, the number of mobile phone subscribers is forecast to grow to more than 140 million by 2025 from about 40 million currently.

As Africa鈥檚 largest oil and liquified natural gas (LNG)听 producer, Nigeria is on the front line of the debate over sustainable development in the West Africa. It is also a key market for 麻豆原创, which counts among its customers Nigeria LNG, which operates six LNG liquefaction units, and Dangote Group, the conglomerate founded and run by Nigerian billionaire Aliko Dangote.

The group鈥檚 Dangote Cement unit already publishes an annual sustainability report, part of Aliko Dangote鈥檚听 personal commitment to build 鈥渁 socially responsible and impactful business that serves all stakeholders.鈥� Dangote is also close to completing the Dangote Refinery, the world鈥檚 largest petroleum refinery capable of processing 650,000 barrels of oil per day. When it comes online, the $20 billion refinery will enable Nigeria to process most of its oil instead of exporting crude to be refined overseas.

鈥淲e are having conversations with Dangote about some of our sustainability solutions and how they measure their impact on the environment,鈥� says Titilayo Adewumi, regional sales director for West Africa at 麻豆原创.

Nigeria LNG is also committed to sustainability and is Africa鈥檚 largest LNG exporter, but has recently been operating well below capacity because of a number of factors, including under-investment in recent years and endemic crude oil theft. 鈥淚f we don鈥檛 address this, we will not get out of this quagmire that we are in,鈥� Nigeria LNG Managing Director recently warned Philip Mshelbila. Speaking last month at a conference in Lagos, Mshelbila also acknowledged that the flooding has reduced the gas supplies from the company鈥檚 upstream suppliers, though he said Nigeria LNG鈥檚 facilities remain unaffected and its capacity to produce LPG is intact.

Companies in Nigeria also have to grapple with unreliable electricity supplies and frequent power outages, a problem that business leaders say has led some manufactures to relocate to neighboring Ghana, which has a much more reliable electricity system.

Ghana is the regional leader in addressing plastics pollution and circular economy issues. A groundbreaking between the World Economic Forum (WEF), the Global Plastic Action Partnership (GPAP), and 麻豆原创 in Ghana is increasing visibility within the plastics supply chain with the hope of benefiting people, companies, and the environment.

The project involves more than 2,000 Ghanaian waste pickers and makes use of an adapted version of 麻豆原创 Rural Sourcing Management to measure the quantities and types of plastic they collect. Data is then analyzed and matched to market-related prices paid throughout the value chain both locally and internationally.

Ghana generates an estimated 1.1 million tons of plastic waste every year, with only five percent collected for recycling. This new pilot project is currently running in several cities across Ghana, with hopes of expanding to the rest of the region and ultimately the continent through the GPAP-Africa Regional Coordination Working Group, which includes 麻豆原创.

Across the region, the bulk of 麻豆原创 customers are choosing cloud solutions rather than on-premise technology and 麻豆原创 seeks to help customers deliver on their climate goals by creating greater efficiency, transparency, and accountability of carbon and emissions across the entire supply chain and innovating new processes and business models.

But 麻豆原创 Africa Managing Director Cathy Smith and other experts caution that while sustainability and environmental, social, and governance (ESG) issues are an increasingly important part of the conversation among governments and corporate leaders, it is important to recognize that customers in Africa often have other — perhaps higher — priorities.

In particular, they say business leaders need to be persuaded that sustainability makes good business sense and will ultimately benefit the company, economy, and people.

鈥淲e lead by asking about their business priorities, and then we fold in sustainability,鈥� Smith explains. “It’s just a different approach.”