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

Expansion 

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

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

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

IT priorities 

Colombina��identified��key areas in need of standardization, particularly finance and supply chain management, and recognized that a unified technology foundation was critical to sustaining growth and operational efficiency.  Security also��emerged��as a top priority, shaping many of the technology decisions that would follow.��

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

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 �鶹ԭ�� 

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

To��harmonize its operational data, Colombina integrated its cloud ERP with a broad ecosystem of �鶹ԭ�� solutions, including���鶹ԭ�� Fiori, �鶹ԭ�� SuccessFactors, �鶹ԭ�� Integrated Business Planning,���鶹ԭ�� Analytics Cloud, and���鶹ԭ�� Ariba,��among others.����

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 �鶹ԭ�� Cloud Application Services, which helps run, manage, and continuously optimize the company’s expanded �鶹ԭ�� landscape.��

Jaramillo also highlighted the value derived from engaging with the �鶹ԭ�� 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��utilization��of existing �鶹ԭ����investments��and maximizing the value of their licensed capabilities.��

He also��highlighted the��guidance provided around key strategic initiatives, including clean core, helping drive a sustainable and extensible ERP landscape; �鶹ԭ�� 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.��

Security benefits 

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

Colombina’s 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. �鶹ԭ�� 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��Joule��for �鶹ԭ�� SuccessFactors, Colombina is��preparing��to��activate��Joule Agents across its business and is implementing �鶹ԭ����Databricks for data models,��working with �鶹ԭ����Business Data Cloud��to build the right data foundation��for future��AI capabilities.��

It’s 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 �鶹ԭ��, 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, �鶹ԭ�� is bringing together 50 years of deep industry��expertise, leading AI engineering know-how, and customer-facing forward-deployed delivery capabilities in one organization��to combine forward-deployed engineering with strong productization capabilities.

This enables �鶹ԭ�� 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 �鶹ԭ��’s strategic direction, �鶹ԭ�� 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 �鶹ԭ��’s industry and process expertise across 26 industries; second, the richness of �鶹ԭ�� 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 “getting obsessed with the problems of our customers” and immersing �鶹ԭ��’s agentic AI developers in the challenges these customers face. “Working directly with customers, we will build, deploy, and scale Industry AI applications to deliver tangible business value for our customers,” 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 �鶹ԭ��’s platform and solution portfolio of high-value agentic solutions that are close to customer needs and current industry priorities.

Getting up close with customers

�鶹ԭ��’s 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 �鶹ԭ��’s 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 �鶹ԭ��, 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 �鶹ԭ�� from competitors.

�鶹ԭ��’s 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 �鶹ԭ��’s unique deep industry-specific knowledge, business AI platform, and knowledge graph, enabling tailored processes for customers. In addition, �鶹ԭ��’s approach is grounded in customers’ 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.

�鶹ԭ�� solves industry problems that generic AI—even if super powerful—cannot. 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—a marketing automation agent, a supply chain monitoring agent, an HR onboarding bot—and 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: “As 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.”

He added: “Many 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’s 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.”

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.

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

�鶹ԭ�� 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 �鶹ԭ�� CTO Philipp Herzig explained on stage at this year’s �鶹ԭ�� Sapphire event, �鶹ԭ�� AI Agent Hub is intended to provide a governance layer of record for the enterprise agent ecosystem. “Agents are everywhere,” he said. “Some are great, some are not, and almost no one has a consistent picture—no central governance, no clear view of what each agent does, whether it adds value or whether it adheres to your policies.”

He added: “�鶹ԭ�� 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—vendor-agnostic. [�鶹ԭ��] 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.”

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—and at greater scale—than 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—particularly those in finance and regulated sectors—who 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 �鶹ԭ�� SE, noted at the �鶹ԭ�� Sapphire Madrid event last month, many European customers operate in the public sector or other highly regulated industries. “Geopolitical risk is a growing concern,” he said. “What if sanctions suddenly block data flows across borders? Or if the latest LLMs can’t be deployed in certain regions?”

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

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—particularly 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 �鶹ԭ��’s 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 “code over concrete.” 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’s technology chief, noted: “Nobody can be competitive alone.”  

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’s real competitive advantage may lie in its treasure trove of operational data—a 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—the .

“Every motorcycle we sell comes with an experience,” he explains. “Customers 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.”

Many people in Colombia get around every day on motorcycles—often on ‘Boxer’ 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 . “Every motorcycle leaving our factories follows best quality practices,” he says. “And we pass that value onto our customers.”

In addition to Colombia, UMA operates in five countries in Central America: Guatemala, El Salvador, Costa Rica, Honduras, and Nicaragua. “We’re also in Venezuela, as well as Spain and Portugal,” Urrea Ospina says. “Across all these regions, we aim to make a positive impact on our customers with each of our brands and motorcycles.”

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“For us, our ‘Adventure’ project—the name we gave the �鶹ԭ�� project—was crucial to our expansion and growth,” he says. “We needed global models so we could expand faster and run more efficient, automated operations.”

Working with �鶹ԭ��, UMA established global models and automated operations across finance, production, and logistics, says Victor Bedoya Aristizabal, corporate solutions manager at Grupo UMA. “We 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.”

“Today, �鶹ԭ�� is a fundamental pillar for our processes from the start of the value chain to the end,” Bedoya Aristizabal says. “We utilize the full suite for production, pricing, finance, and warehouse management to deliver a superior product.”

“Taken together, these cross-cutting global modules have helped us evolve, save time, shorten implementations, and expand across regions,” Urrea Ospina says. “For example, in Colombia we’re implementing our spare parts warehouse with �鶹ԭ�� Extended Warehouse Management, �鶹ԭ��’s supply chain management application. What we’re learning in Colombia can be replicated in Central America. Standardizing these logistics modules makes operations much more efficient while still accounting for each country’s specific needs.”

He adds: “I believe that if we hadn’t prepared with �鶹ԭ�� and the technologies we have today, the strong growth we’ve 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—nearly doubling our output. Without �鶹ԭ��’s 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.”

“That ability to scale—both assembly volume and sales volume—has been driven by the Adventure project and everything we implemented with �鶹ԭ��,” he says. “I think it has significantly improved employees’ day-to-day work. And that’s where we need to take the organization: toward a data-driven company that makes better decisions. Before we implemented Adventure, a person’s day-to-day was mostly operational work.”

Urrea Ospina emphasizes that one of the main motivations UMA had for adopting �鶹ԭ�� Cloud ERP Private was to have concrete, real-time information—for example, knowing exactly the assembly cost of a motorcycle. “That is key for an organization,” he says. “Beyond that, another need was to remove the manual work that all the company’s areas had, working and operating completely by hand.”

Luis Orrego, production supervisor at Grupo UMA, agrees: “Instead of having many Excel files open with multiple sheets and trying to reconcile everything, we now consolidate the data in one place. With �鶹ԭ��, all the sheets and reports I used to present are now available in a single view. I don’t have to run multiple steps, and I can see all my indicators: capacity, materials, and line resources.”

Another motivation was UMA’s expansion plans to enter other regions and countries efficiently. “We wanted defined global models that we could replicate quickly with �鶹ԭ�� in the regions where we operate,” Urrea Ospina explains. “Those factors led us to undertake the �鶹ԭ�� project, which has been a highly strategic and very successful initiative.”

Implementing �鶹ԭ�� Cloud ERP Private has also had a profound impact on Urrea Ospina’s technology team. “It completely changed our roles and what we focused on,” 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’re going and what we can implement next for the business. Culturally, �鶹ԭ�� gave us confidence through information traceability, and it also gave us time to think. It opened the door to innovation—especially around analytics.”

David Aguirre is a media production specialist on the Multimedia Team for �鶹ԭ�� News.
Rana Hamzakadi is deputy head of the Multimedia Team for �鶹ԭ�� News.

In his kickoff keynote at �鶹ԭ�� Sapphire Orlando, Florida, Klein and other �鶹ԭ�� Board members detailed how �鶹ԭ�� 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.

“Today I’m super proud to launch our new �鶹ԭ�� 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,” Klein said.

Enterprise AI is at an inflection point, Klein told his 30,000-strong in-person and virtual keynote audience, and �鶹ԭ�� 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 �鶹ԭ�� Sapphire, the message was clear: This isn’t a technology problem; it’s a context and execution problem.

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

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

�鶹ԭ��’s answer to this challenge begins with what Klein described as “the brain of every company: its ERP system.” For over 50 years, �鶹ԭ�� 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’s new vision, �鶹ԭ�� 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.

“We’re 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,” he told the audience. “Today we are very excited to show you the new �鶹ԭ�� and our vision for the Autonomous Enterprise.”

�鶹ԭ�� Business AI Platform

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

“The heart of this new platform is the rich context layer,” said Klein. “Here, 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 �鶹ԭ�� Domain Models. They have been trained on �鶹ԭ��’s code to even better understand the business logic of your company.”

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

Echoing Klein, �鶹ԭ�� 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. “It’s the place where you build, contextualize, reason, and govern AI,” 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. “Agents are only as powerful as the context they operate on,” he said. “Lacking context is the number one reason why enterprise AI projects fail to deliver value.”

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

The third tier is the governance layer, anchored by the new �鶹ԭ�� AI Agent Hub built on �鶹ԭ�� LeanIX. This provides a single command center to discover, manage, and govern all AI agents—�鶹ԭ�� and non-�鶹ԭ��. It will be generally available in Q3 and included in �鶹ԭ�� 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: “What I’m hearing from clients is a clear shift; they’re 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.”

�鶹ԭ�� Autonomous Suite

Building on the platform, �鶹ԭ�� Executive Board Member Muhammad Alam, �鶹ԭ�� Product & Engineering, announced the transformation of �鶹ԭ��’s SaaS application portfolio into the �鶹ԭ�� Autonomous Suite, described as the most significant evolution of �鶹ԭ��’s applications business in the company’s 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 �鶹ԭ�� AI Agent Hub.

“�鶹ԭ�� Autonomous Suite brings together the depth of our process expertise, semantically rich data, and built-in governance and compliance,” said Alam. “These 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.” 

“Underpinning the autonomous suite are out-of-the-box agents—hundreds of agents cutting across all core business processes,” he shared. “These 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.”

Turning to Joule itself, Muhammad said �鶹ԭ�� is fundamentally reimagining how users will interact with �鶹ԭ�� applications in the future.

“We 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,” he explained.

“Joule Work represents a massive step forward in super-charging the capabilities of Joule as we know it today,” Alam said. “With 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.”

Industry AI: H&M and Sector-Specific Transformation

During the keynote, �鶹ԭ�� 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 �鶹ԭ�� 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 Svanström, who discussed how the fashion retailer is embedding AI across its value chain. Built on RISE with �鶹ԭ��, �鶹ԭ�� Business Data Cloud, �鶹ԭ�� Commerce Cloud, and �鶹ԭ�� 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 �鶹ԭ�� and �鶹ԭ�� 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. “Moving to the Autonomous Enterprise requires serious change management. Adoption of AI goes hand-in-hand with business process change and end user enablement.”

To support customers on this journey, �鶹ԭ�� announced a comprehensive reset of its RISE with �鶹ԭ�� and �鶹ԭ�� GROW offerings. RISE with �鶹ԭ�� 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.  

�鶹ԭ�� 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 �鶹ԭ�� is evolving from being a software company to becoming a business AI company.

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

“We’ve been reinventing how businesses run for over 50 years, and now by infusing �鶹ԭ��’s ERP brain into the new �鶹ԭ�� Business AI Platform, we’re solving one of the biggest challenges businesses are facing today: how to turn AI into business value,” he said. “It’s the end of long negotiations, supply chain disruptions, financial blind spots, and the beginning of better: Welcome to the Autonomous Enterprise.”

Now, however, many economists and policymakers view AI as a potential catalyst for reversing that slowdown. AI—especially the rise of generative AI and AI agents—is 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—like Joule Agents from �鶹ԭ��—are 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—all 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 “long-tail” 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’s trajectory and the size of what has been called the “AI growth dividend.” 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’s 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’s 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 �鶹ԭ�� 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, �鶹ԭ��’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’s 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 �鶹ԭ�� customer since 2008, and while initially it was not very proactive with software upgrades, the company’s philosophy has changed over time. Today, Carol McMillan, Naturipe’s 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 �鶹ԭ�� S/4HANA in 2018, the company has undergone three upgrades, including .

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“We migrated to RISE with �鶹ԭ��, 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,” McMillan says.

She says it’s 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 �鶹ԭ��’s technology to prioritize its people and customers, improve workplace happiness, and give users a better experience. “We use technology to make sure that we’re running as optimally as possible,” she says. “We 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.”

Delivering the freshest, highest-quality products to customers 365 days a year requires constant agility—especially in a category influenced by weather variability and the complexity of a highly time-sensitive supply chain. “Berries have a very short shelf life, so getting the best quality to our customers as quickly as possible is essential,” 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 �鶹ԭ��.  McMillan also identifies the potential of AI and the adoption of tools like Joule to improve Naturipe’s 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—this while many brands are still optimizing for search engines and are quietly disappearing from the models driving the next generation of product discovery.

“Agentic commerce—shopping powered by AI agents acting on our behalf—represents a seismic shift in the marketplace,” McKinsey, the strategic management consultancy, noted in a . “It 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.”

This, as speakers and panelists at the NRF conference acknowledged, isn’t just an evolution of e-commerce; it’s 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, �鶹ԭ�� 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.

�鶹ԭ�� 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 �鶹ԭ�� Business Data Cloud that leverages data from across �鶹ԭ�� software and third-party systems to help provide accurate demand planning, improved forecast accuracy, and lower inventory costs to drive more seamless omnichannel engagements.

�鶹ԭ�� Customer Experience has also unveiled a recently that can be combined with the��, 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, �鶹ԭ�� 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 , “while most retail merchandising teams have invested in automation tools��and experimented with AI, 71% of merchants say that AI merchandising tools have had limited to no effect on their business so far.”

“The challenge,” McKinsey said, “often lies less in the technology than in how it’s 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’t at all or is only slightly prepared to scale AI across merchandising.”

Onstage at NRF, Andre Bechtold, president for �鶹ԭ�� 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.

“Retailers are operating in an environment defined by volatility—tariffs, margin pressure, supply chain disruption, and customers that expect real-time, hyper-personalized experiences everywhere,” Bechtold said during a discussion with Gymshark, the workout apparel retailer. “At the same time, boards and investors are asking a tougher question than ever before: what outcomes are we actually getting?”

“The challenge,” he said, “isn’t a lack of innovation. In fact, most retailers have plenty of tools, pilots, and point solutions. The real issue is that disconnected technology doesn’t translate into resilient growth. That’s why the conversation is shifting. It’s no longer about isolated AI use cases or shiny new features. It’s about whether AI and data are embedded across the business—connecting supply chains, finance, merchandising, and customer engagement—in ways leaders can trust.”

Echoing the same point, Thomas Saueressig, member of the Executive Board of �鶹ԭ�� 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. ��“As long as AI runs alongside the core business as an isolated project, the effects remain limited,” he said.

Recent geopolitical shifts and technological advancements have heightened the challenges for organizations responsible for society’s 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. �鶹ԭ�� pioneered the development of sovereign cloud services through its �鶹ԭ�� Sovereign��Cloud offerings, which address all four pillars of digital��sovereignty: data, operational, legal, and technical architecture.

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Recently, �鶹ԭ�� has built on this leadership by launching new sovereign cloud initiatives and partnerships designed to accelerate Europe’s digital transformation through secure, scalable,��AI-driven��sovereign��cloud solutions that protect data and intellectual property.

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

With these and other offerings, �鶹ԭ�� 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’re entering a new era, according to �鶹ԭ�� Executive Board Member Muhammad Alam, in charge of �鶹ԭ�� Product & Engineering: “the era of agentic AI, where AI moves from being just a tool to becoming your trusted teammate.”

Joined on stage by �鶹ԭ�� CTO Philipp Herzig and Michael Ameling, president of �鶹ԭ�� Business Technology Platform, Alam set the stage during the kick-off keynote, saying: “As developers, you are not on the sidelines of this AI revolution. You are the revolution. And we are here to supercharge you for what’s next.”

Supercharging developers

Together they dismissed suggestions that AI will replace developers. “The truth is that developers aren’t going away,” Alam said. “They 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?”

Ameling, Alam, and Herzig outlined �鶹ԭ��’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 �鶹ԭ�� ecosystem.

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

“As developers, you don’t just code anymore,” Alam said. “You also design intelligent workflows and supervise AI agents to shape real business outcomes.” To help developers do this, �鶹ԭ��’s strategy centers on empowering them with applications, connecting them with data, and supercharging them with AI.

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�鶹ԭ�� BTP is the foundation for AI agents

All this runs on �鶹ԭ�� Business Technology Platform (�鶹ԭ�� BTP), which serves as the foundation for building and managing AI agents—both �鶹ԭ�� built and custom developed. While �鶹ԭ�� 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 �鶹ԭ�� is continuing to make �鶹ԭ�� more open. As part of that, he announced �鶹ԭ�� Snowflake, which brings the full data and AI capabilities of Snowflake as a solution extension to �鶹ԭ�� Business Data Cloud (�鶹ԭ�� BDC). This partnership is exactly what joint customers have been asking for, Alam shared.

Second, he said �鶹ԭ�� 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. “Today, you’ll hear about creating custom Joule Agents using low-code and pro-code tools with agent builder in Joule Studio as part of �鶹ԭ�� Build” Alam said.

“We’re also standardizing AI agent interoperability with the agent-to-agent protocol, allowing your agents to collaborate securely across ecosystems,” he added.

Third, he announced �鶹ԭ��’s first foundation model built specifically for structured business data: �鶹ԭ�� RPT-1, pronounced “�鶹ԭ�� Rapid One.” “Our 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,” Alam said.

“In short, we’re embracing an open ecosystem, supercharging agents with deep process and data context, and giving you the tools to amplify AI and agents,” 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.

�鶹ԭ�� BDC and Snowflake

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

Ameling also positioned �鶹ԭ�� HANA Cloud as “the database AI was looking for.” With �鶹ԭ�� HANA Cloud and �鶹ԭ�� BDC, �鶹ԭ�� provides the best business data fabric to help address these challenges, he said. “Without �鶹ԭ�� 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 �鶹ԭ�� HANA Cloud, we have all these powerful engines in one integrated, multi-model database.”

Building on this, Herzig emphasized that every business requires a strong data foundation because “AI 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 �鶹ԭ��’s out-of-the-box AI capabilities and build your own experiences deeply contextualized in your business processes and data.”

�鶹ԭ�� pioneers a tabular foundation model

Herzig then explained that �鶹ԭ�� 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, “We still had to go back to good old machine learning …to train what we call ‘narrow’ AI models that are specifically made for each [business] task. Therefore, you really had to train a hell of a lot of models.” For example, to solve 10 predictive tasks across 10 different entities like company codes or plants would require training 100 different models.

“What 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,” he said. That’s what �鶹ԭ�� RPT-1 is. “We believe �鶹ԭ�� RPT-1 is the most capable predictive foundation model that’s out there today,” 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 �鶹ԭ�� CTO also emphasized that the company is committed to providing developers with the most context-rich agentic platform. He noted that �鶹ԭ�� 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 �鶹ԭ�� 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… [�鶹ԭ��] Joule for Developers enables vibe coding experiences to make intent-based development simple and intuitive.”

�鶹ԭ�� 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 �鶹ԭ�� 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.

�鶹ԭ�� 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 �鶹ԭ�� is bringing to life robots that understand the what, when, and how based on live business context. “This is how we’re really imagining the future, right? Humans and robots working in harmony through Joule, through AI,” Herzig said.

Quantum computing

Looking to the future, Herzig ended the keynote by talking about another “compute paradigm that is still hard to seize”: quantum computing. While he made it clear that �鶹ԭ�� is not building a quantum computer, �鶹ԭ�� is teaming up with quantum hardware leaders, like IBM—whose Director of Research and IBM Fellow Jay Gambetta joined via video—to help evaluate quantum computing for business processes and applications.

“We believe quantum will join classical and AI compute in your stack, and we’re embedding it into the processes and apps you’re already using, so it just shows up in the workflows of your enterprise,” Herzig said. “And of course, with the cloud, we scale it all. Now, �鶹ԭ�� has got you covered, and you’ve got your business covered.”

“We are an agricultural company,” she continued, “but 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.”

Trulieve has been an �鶹ԭ�� customer since 2020. It initially chose �鶹ԭ�� because its legacy system couldn’t keep up with the company’s growth and demand. “We needed to leverage and the scale it gave us just to be able to keep up with sales,” Zimmerman explained. Today, Trulieve’s �鶹ԭ�� portfolio also includes �鶹ԭ�� SuccessFactors solutions and �鶹ԭ�� 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. “We 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,” Zimmerman said.

That’s 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.

“Obviously we want to continue that growth,” Zimmerman said. The biggest catalyst for growth is when states legalize recreational marijuana use, which opens up the entire market for Trulieve’s hand-grown marijuana products. “The big focus for us is scalability and stability in our solutions to make sure we are able to support that growth,” she said.

“�鶹ԭ�� enables us to have more insight into our growth and manage production better than any other system that’s out there,” Zimmerman said.  And since Trulieve is a publicly traded company, running �鶹ԭ�� S/4HANA also helps ensure that Trulieve’s 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—the company’s customer data platform combines data from multiple applications, enabling it to market more effectively to its customers and make operational decisions. “That 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.”

She also believes that the AI tools �鶹ԭ�� is embedding in its solutions will deliver real benefits: “I 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.” 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’s 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.

“This environment is incredibly dynamic, so that means that tomorrow we could get legislation that opens up cannabis to the entire country,” she said. “When 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.”

�鶹ԭ�� technology, she said, provides the scalability and flexibility, together with the data, the company’s leaders need to make the best decision in real time.

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Against the backdrop of the event theme—”Connect Everything, Achieve Anything: Agents, Data, and the Business Suite”—they set out �鶹ԭ��’s vision for how �鶹ԭ�� Business Suite, which combines AI, data, and applications, can transform enterprises and deliver unprecedented business value to customers despite global macroeconomic uncertainties. 

Unique times

“We are living in very unique times,” Alam said at the start of the keynote. “Unique in terms of the unpredictability we face from a geopolitical and macroeconomic perspective, and also unique in terms of the advancement in AI and the potential that carries for all of us.”  

He added, “Even the most significant challenges can be responded to, navigated, and—when approached the right way—turned into opportunities. And that’s exactly where �鶹ԭ�� comes in. Because the best way to face uncertainty is with confidence that you can see what’s happening across your business and your network.” 

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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’s business uncertainties to that of co-piloting a modern jet. 

“AI 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,” Asam said. He also warned that standing on the sidelines of technological progress is “a sure recipe for falling behind in competition.”  

“As in prior tech supercycles, the entire competitive playing field is being completely reshuffled,” he said.

New products

Building on this theme, Alam noted that while uncertainty is real and isn’t going away, it can be successfully navigated and turned into opportunities. To help customers achieve this, he announced several new and enhanced �鶹ԭ�� products. 

Among them, �鶹ԭ�� Supply Chain Orchestration is an AI-native application that uses a network knowledge graph to analyze real-time signals across a company’s 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.   “Think of it like a GPS in your car which selects an alternative route to avoid traffic or tolls,” Alam explained. In addition, he announced a major update to the �鶹ԭ�� Ariba solutions for source-to-pay suite, positioning �鶹ԭ�� Ariba as the most modern platform in the industry and the only truly AI-native source-to-pay solution—all built on �鶹ԭ�� Business Technology Platform.

The human-AI partnership opportunity 

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

“At �鶹ԭ��, we know firsthand that AI is everywhere, shattering norms and transforming the workforce,” Vargiu-Breuer said. “And we as �鶹ԭ�� are boldly steering this shift, as requirements for our workforce are simply changing really fast.”  

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

Role-based AI assistants

Echoing this human-centric approach, Alam noted, “Everyone is talking about agents—billions of agents—and 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.” 

Reflecting this, he said �鶹ԭ�� 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. “Today, 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.”   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. “Over time, we will continue to make this assistant even smarter by adding more agents and capabilities—all designed to make the person in this role more effective.”

Deep research and new intelligent applications

“While efficiency and automation carry potential for great value for the organization, AI’s 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,” said Alam. To address this challenge, �鶹ԭ�� 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 �鶹ԭ�� Business Data Cloud Intelligent Applications and an enterprise wide, multi-stakeholder engagement orchestration solution in �鶹ԭ�� Engagement Cloud, Alam closed out the keynote by reminding his audience: “To create exponential value and to reach the global maxima for your enterprise, the whole matters.  And that’s 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.” 

�鶹ԭ�� Business Suite delivers unprecedented value

The unmatched value of �鶹ԭ�� 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 �鶹ԭ�� Educate to Employ initiative is set up as a digital pathway through Youth Agency Marketplace (YOMA), a public-private-youth ecosystem from UNICEF’s Generation Unlimited. The program aims to address this challenge and enable young people’s 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. “In South Africa there’s not a lot of opportunities when it comes to the employment sector,” 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’s 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. “I faced a lot of challenges trying to apply for jobs,” he said. “It’s very tough for young people like me.”

Shange is not alone. “In 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,” said Nadi Albino, deputy director at UNICEF’s 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’s Generational Unlimited, which offers opportunities for young people to learn, earn, and create impact. On his pathway to employment, Shange was introduced to �鶹ԭ�� Educate to Employ, an initiative delivered to YOMA through the implementing partner Umuzi. The curriculum for �鶹ԭ�� 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 �鶹ԭ�� Educate to Employ.

“�鶹ԭ�� 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 �鶹ԭ�� ecosystem,” explained Eugene Ho who leads �鶹ԭ��’s global CSR flagship skilling programs targeted at youths in need. “Through its tailored curriculum, the initiative has successfully helped candidates with only high-school qualifications.”

“The �鶹ԭ�� Educate to Employ initiative provides young people with the tools, skills, and resources that they need to get employed or to employ,” Albino added in an interview with �鶹ԭ��. “We have to go back to making sure that these education systems work and that they work in tandem with where the world is going.”

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

�鶹ԭ�� CEO Christian Klein is the chair of the Generation Unlimited Board.  

“The 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.”

Shange’s journey with YOMA and �鶹ԭ�� Educate to Employ started in the living room of his grandmother’s house, a place where community has always taken center stage. “I 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.”

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.

“I 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.”

Today, �鶹ԭ�� 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 �鶹ԭ�� 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 “sovereign” 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 �鶹ԭ��, have responded by providing highly secure sovereign cloud services.

But in recent months the debate over digital sovereignty has widened. As Hayete Gallot, Google’s president of Customer Experience, recently noted, “Sovereignty 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.”

The EU has proposed spending €20 billion to build five “gigafactories” 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. “The hardware train has left [the station],” he said. Together with other senior �鶹ԭ�� 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, �鶹ԭ�� 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 �鶹ԭ�� National Security Services (�鶹ԭ�� NS2).

Sovereign cloud customers

The �鶹ԭ�� Sovereign Cloud organization already counts more than 170 customers globally and has plans to invest a further €2 billion over the next decade to expand regional coverage. For example, �鶹ԭ�� 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., �鶹ԭ�� 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’s digital strengths: “A new, European-defined concept of sovereignty is necessary, one that relies on self-determination rather than self-sufficiency.” He also cautioned that digital sovereignty “is not an end in itself” and called for “profound change” to industry business models.

These models “need to be rethought, processes digitized, and AI used in a targeted manner for more innovation, for greater efficiency, for sustainability,” he added. 

Martin Merz, president �鶹ԭ�� Sovereign Cloud, agrees. “The debate around digital sovereignty in Europe has gone on too long with too many buzzwords and too little substance,” he said. “We’ve 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.”

“When it comes to highly sensitive data, �鶹ԭ�� Sovereign Cloud comes in,” Merz continued. “It’s purpose-built to protect the most sensitive, security-critical data, enabling the highest level of protection and operational autonomy, without slowing down innovation.”

Locally hosted AI

Underscoring this shift in the data sovereignty debate, many �鶹ԭ�� customers are now talking about sovereign AI or what �鶹ԭ�� calls “locally hosted AI.” To help facilitate this, �鶹ԭ�� 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. “Starting 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 �鶹ԭ��,” 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. “Their data will remain local, trusted, compliant, and secure, and seamlessly integrate with �鶹ԭ�� Business AI capabilities without compromising on performance, governance, or privacy,” 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 �鶹ԭ�� has formed a strategic partnership with and to accelerate AI adoption across Europe.

“Together, we’re building the future of enterprise AI – secure, local, and smart,” Herzig said.

The dressings were so well loved, customers could be seen leaving the restaurant with bottles of their favorites. By 1955, the restaurant’s 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’s Chief Information Officer, was brought onboard in December 2018 by Marzetti’s CEO, Dave Ciezinski, who had worked with Durbin previously at Heinz. Durbin was charged with replacing Marzetti’s legacy green-screen PRISM software, which had become outdated, with a modern ERP system.

After a competitive bidding process, �鶹ԭ�� was chosen as the new ERP system. Durbin says �鶹ԭ�� 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—support which he said “created a lot of tailwind” for a project they saw as crucial to ensure the company’s future success.

“The CEO and the board were clear that they wanted the ‘A players’ for the project, creating a dream team to ensure its success,” 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 �鶹ԭ�� 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—one of about 16 facilities overall—onto �鶹ԭ�� from a technical perspective. “This allowed us to kick the tires and make sure the functionality worked,” 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.��For example, wave one covered finance, trade, procurement, and customer support—“everything touching the customer,” Durbin said, adding that waves two, three, and four went pretty much as planned. “We chose to split wave four in two to de-risk it because it contained two large facilities,” 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.��

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, “allowed us to keep the clean core so we now do most of our reporting and analytics on the Microsoft platform.” ��

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, “so the democratization is underway,” he said while acknowledging that those employees in operations “are going to need some help.”

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.��“In addition to projects like AP automation, we are also very excited to see what AI capabilities �鶹ԭ�� will be adding to its products,” Durbin said.

Looking back at the Project Ascent, he highlighted the importance of having a fully-staffed organizational change management team for �鶹ԭ�� 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—some of whom had never used a computer mouse—adapt to the new system.

“The amount of work involved in training people on how to interact with �鶹ԭ�� was a lot bigger than we thought because how technology has changed,” Durbin said, adding that another challenge has been recruitment. “As COVID-19 started to ebb and people were starting to go back into their jobs—and this condition still persists today—a lot of factories and manufacturing businesses have had difficulty hiring hourly workers again.”

“Some 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,” he said. “So, 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.”

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.

“It all started in 2018, when we decided to have an analytics system and a clean core �鶹ԭ�� 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,” he said.

Gonzalez explained that this is particularly important in a nation like Argentina because prices are extremely volatile. “It’s important for us to have that information readily available because Argentina is a highly inflationary country, where prices change really quickly,” he said. For example, during the COVID-19 pandemic Vital sometimes had to change 20,000 product prices in less than a day, “so we have to do all of that analysis really fast.”

Vital was a long-time �鶹ԭ�� 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 �鶹ԭ�� [S/4HANA] is we were used to using �鶹ԭ��,” says Gonzalez. “But 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, �鶹ԭ�� included, and another three.”

Ultimately, he said Vital decided on �鶹ԭ�� 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 “integrated 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.”

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 “are not influenced by what a person wants, but by what the data is telling them to do.”

Because all the company’s 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. “We can change our pricing policy based on reception of goods and new purchase orders and adopt new pricing in real time,” 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. “We negotiated with our suppliers; we made offers and made predictions of how it would work out and it turned into a real savings — that’s what technology is doing for our company.”

Just as importantly, Gonzalez said Vital now works with one version of the truth. “In 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.”

“The technology has really advanced how our users in the company experience data and decision making,” 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. “All our applications are cloud-ready, and we maintain a clean core, so we can upgrade really fast,” said Gonzalez, who expects to be ready to make that the move by the end of the year. ��

The Vital CIO and CTO is also looking to AI to help the company’s employees make even better purchase and pricing decisions. “We don’t see AI as replacing our personnel or people in the industry,” he said. “We see it at enhancement, we see it as turbocharging our system and making the data more reliable and useful.”

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

“A lot of companies regard their data as really private and don’t share it with everyone in the company,” he noted. “We 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.”

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 “bring out your best.”

Uncertainty

“All of us face one problem – every company, no matter which industry or geography. And that problem is uncertainty,” said Klein. “Uncertainty about trade disruption, about new regulatory requirements, and about how AI will transform my business and impact my workforce.”

�鶹ԭ�� can’t take away macroeconomic uncertainty, he said, “But you have my commitment that we will help your business become more resilient and more agile – especially in times like these. We will help you bring out your best.”

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Flywheel effect

�鶹ԭ�� can do this by utilizing what Klein and other senior �鶹ԭ�� executives called the “flywheel effect,” explaining that in physics this is about bringing individual elements together to create new energy.

“The first element of the �鶹ԭ�� flywheel is our applications,” Klein explained. “Not 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 �鶹ԭ�� does.”

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

�鶹ԭ�� Business Suite

“Then we make the flywheel spin by infusing AI back into the apps, which run your company,” 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 �鶹ԭ�� Business Suite and AI.

Expanding the flywheel theme, Muhammad Alam, member of the Executive Board of �鶹ԭ�� SE leading �鶹ԭ�� Product and Engineering, noted that the demo highlighted how the flywheel of apps, data, and AI is critical to the company’s 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’t 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. “In fact,” Alam said, “We 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.”

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. “Enabling this in a disparate, disconnected landscape is close to impossible,” he said.

The only real solution is to move to a best of breed as a suite, or what �鶹ԭ�� calls “suite-as-a- service,” Alam told the audience. “The new SaaS is what will allow you to take advantage of the flywheel effect.”

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

This is what the �鶹ԭ�� Business Suite offers.

�鶹ԭ�� Business Data Cloud

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

Klein also announced the expansion of business data analysis capabilities in �鶹ԭ�� Business Data Cloud through a new partnership with Palantir, while Alam unveiled a new partnership with Adobe to develop an intelligent application on �鶹ԭ�� Business Data Cloud that combines �鶹ԭ�� 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 �鶹ԭ��, also made a series of AI-related announcements. “At �鶹ԭ��, our goal is to make every end user 30 percent more productive,” said Klein.

Joule

To achieve this goal, �鶹ԭ�� is enabling end users to use human language to interact with Joule, �鶹ԭ��’s 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.

“Today we are proud to announce that we are making Joule available to you everywhere and giving you answers on everything,” the �鶹ԭ�� CEO said. By combining Joule with WalkMe, the adoption platform acquired by �鶹ԭ�� last year, Joule becomes an omnipresent, always-on, proactive, and personalized AI assistant.

“No matter in which app the end user is working, �鶹ԭ�� or non-�鶹ԭ��, Joule will be everywhere,” Klein said.

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

Business AI

During his keynote section, Herzig highlighted the progress made with �鶹ԭ�� Business AI. “We 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,” he said. “We also introduced Joule for developers and Joule for consultants, helping tens of thousands of people every day to achieve more.”

Herzig said �鶹ԭ�� 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 �鶹ԭ�� 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.

“Our AI strategy is super simple, it’s really about three things,” Herzig said. “Joule as the new UI in the age of AI, its Joule Agents to reimagine business processes and AI Foundation on �鶹ԭ�� BTP, which is becoming the operating system for AI.”

Joule Agents

While Joule transforms the experience layer, Herzig said, Joule Agents are transforming the business process layer, “reimagining business processes from the ground up.” Instead of designing enterprise apps around the principle of “insight-to-action,” Joule Agents streamline decision-making through reasoning and action.

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

To control and govern these agents, Herzig announced the launch of AI agent hub in �鶹ԭ�� LeanIX. “�鶹ԭ�� 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,” he said.

Among other innovations, Herzig announced that �鶹ԭ�� 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.

�鶹ԭ�� runs �鶹ԭ��

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

“With Joule, our developers, consultants, and HR are seeing strong efficiency benefits today. Across �鶹ԭ��, we track several hundreds of millions in AI-powered efficiency gains committed to our budget.”

Steinhaeuser also discussed the benefits of �鶹ԭ�� Business Data Cloud, noting, “Earlier this year, we became customer zero of �鶹ԭ�� 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.” Next up, he said, we are excited to go live with the first set of intelligent applications, starting with People Intelligence.

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

Summary

Summing up the keynote messages, Christian Klein said: “Together we have seen how the �鶹ԭ�� 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.”

“Let 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 – especially in times of uncertainty – so that you can run your business in sheer harmony.”

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, �鶹ԭ��’s global vice president of Retail Solution Management, said.

“There is a tremendous market out there for retailers to utilize AI and improve their business processes,” she said during an open theater session at the �鶹ԭ�� booth during the show.

Over two days, retailers who came to the �鶹ԭ�� 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 �鶹ԭ�� tailored specifically to the retail sector can help them become more efficient and serve their customers better.

�鶹ԭ�� 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.”

�鶹ԭ�� also announced plans to bolster its retail offerings with two new tools—a 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.

�鶹ԭ�� S/4HANA Cloud Public Edition retail, fashion, and vertical business is available immediately, while the shopping assistant, which is based on��, �鶹ԭ��’s unified copilot, will be released during the first half of 2025.��

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’s ERP system, users can discover specific information, like the current availability of stock.

The new loyalty management application takes data from �鶹ԭ�� 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, “as areas where retailers can start consuming AI.” She also expects retailers to be early adopters of AI tools to help with their pricing strategies and to use generative AI copilots, including �鶹ԭ��’s offering, to ask questions and get answers immediately—about inventory for example—wherever they are.

While it’s still early days in terms of adoption, almost every retailer presenting in the �鶹ԭ�� 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 �鶹ԭ��’s retail team made it clear at the NRF show that �鶹ԭ�� 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. “We have had the challenges of most industries in the last years,” he says. “My job is to help Roca leverage technology to support the different strategic objectives of the company, which are growth, innovation, operational excellence, and sustainability.”

Global Supply Chain

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

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Nieuwland says technology helps by giving Roca greater visibility into its supply chain. “Everybody 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,” he says. “And this enhanced visibility allows us to optimize the whole value chain and to take the right decisions.”

�鶹ԭ�� is the backbone of the company’s application landscape, he says: “We perform our core processes, which include order processing, reordering planning, and many others via �鶹ԭ�� 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.”

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

Long-Term Partnership

Nieuwland says Roca Group chose �鶹ԭ�� to be its technology partner because of its long-term relationship with �鶹ԭ�� and because �鶹ԭ�� is a leader in many of the solutions Roca needed. “We have a long history of collaboration and have been successful. […] We trust the technology, the digital supply chain solution, [and] the business network solution. We like to work with leading solutions – we trust them.”

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

He adds that the integration of �鶹ԭ��’s generative AI copilot into �鶹ԭ��’s cloud ERP will also fuel innovation and productivity. “We think there is huge potential to increase our productivity,” he says. More generally, he says �鶹ԭ��’s 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’s goal is to deliver “the best bathroom experience for customers worldwide.”

Asked what other manufacturers can learn from Roca’s experience, he says: “It’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.”

­­­“We are a local club in Bavaria, but have fans around the globe,” says Stefan Mennerich, the club’s 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’s digital and media platforms are very important because fans expect to be able to interact with their club wherever they are. “They want to send us their feedback and they want to receive feedback.”

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Fans Are Everything

The fans are at the center of everything FC Bayern does, Mennerich confirms: “Our 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 — with everything.”

He says the club chose �鶹ԭ�� as its technology partner for several reasons, including the fact that FC Bayern has different businesses. “We have ticketing, we have merchandising, we have fan experience, we have digital platforms, and �鶹ԭ�� is able to deliver the best solutions for all these areas.”

He also cites �鶹ԭ��’s commitment to continuously develop its cloud-based platforms and says this makes the digital experience “better and better every day.”

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

“We have around 50,000 transactions every match day in the Allianz Arena, and we use �鶹ԭ�� Customer Checkout for that,” Mennerich explains. “Fans can buy their merchandise articles, they can buy food or beverages, they can walk into our restaurants and pay there with �鶹ԭ�� Customer Checkout.”

Separately, �鶹ԭ�� 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 �鶹ԭ�� tools for its employees. For example, the AI-infused �鶹ԭ�� 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.

“We 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.”

He believes that embedding artificial intelligence capabilities in �鶹ԭ�� 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.

“Our 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,” he says. “We 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.”

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 �鶹ԭ��, even midsize companies with broad business activities like FC Bayern can cover all the bases and be able to be competitive.

“I think what we are good at is meeting fan expectations via digital platforms,” he says. For that, interactive communication is very important. “You 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.”

“This year is a very special Sapphire,” Klein said. “We are entering a new phase of AI, with endless possibilities for us all.”  

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 “Bring Out Your Best,” this year’s event theme.

Delivering on an AI Promise

Klein emphasized how �鶹ԭ�� 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 �鶹ԭ�� applications.

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

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

AI Momentum

Building on �鶹ԭ��’s 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 “truly differentiated employee experience.”

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

“The business AI innovations we’re announcing will not only change how people work with �鶹ԭ�� solutions, but how people work overall,” 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 �鶹ԭ��’s 6-million-strong consultant and developer community to accelerate projects by 30% and implement �鶹ԭ�� solutions faster than ever before.

During his keynote he described business AI as being “an inflection point” and added, “Today’s 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’s fast-moving business landscape.”

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“�鶹ԭ�� is the only tech company who can infuse AI capabilities right into your business processes and workflows,” he said, saluting the achievements of the 40,000 �鶹ԭ�� employees in the Product Development organization.

Shout Out to �鶹ԭ�� Developers

“No other tech company can offer a more powerful platform to transform enterprises to rewrite how business is run.” �鶹ԭ�� developers have transformed �鶹ԭ��’s portfolio “from 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.”

“We promised this to you, and we delivered,” Klein told audiences online and the 14,000 customers and partners attending �鶹ԭ�� Sapphire in person this week in Orlando. “Now 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.”

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

Joule: Key to Higher Productivity

He predicted that Joule will also become the biggest productivity engine for every �鶹ԭ�� 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 �鶹ԭ�� products will be 20% more productive.

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

Klein wrapped up the keynote by emphasizing that �鶹ԭ�� does not view AI as an end in itself, but rather as a tool to help the world run better and improve people’s lives. “You 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.”

Paul Saunders, head of Product Strategy and chief evangelist of Cloud ERP for �鶹ԭ�� S/4HANA put it this way during a : “Trust is not the engine oil, it’s the essence of business.”

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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 �鶹ԭ��’s commitment to relevant, reliable, and responsible business AI all the more crucial.

“The relationship between �鶹ԭ�� and our customers for the longest time was transactional,” he says. But the shift to the cloud has changed that. From the customer’s 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 �鶹ԭ��’s advantage. He acknowledges that �鶹ԭ�� is sometimes considered to be “a little bit old fashioned,” but also thought of as “incredibly reliable and trustworthy.” 

In such a fast-changing and unpredictable environment — one in which many experts, including Saunders, predict that at least one big brand name company will be in the news “for doing something terrible with AI” — �鶹ԭ��’s 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. “If you go to any CEO or CFO, they will tell you they only care about three things: revenue, cost, and risk. That’s it.”

Ultimately, he says, “Everything we do has to show the business value.” 

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. “When we were farming cassava, bananas, and coffee, we were affected by monkeys. They came and destroyed our crops,” 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. “Our living conditions where bad,” she remembers. She and her family lived in a makeshift timber house. “In 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. “When a day starts, some of my family members help me with the pruning,” she says. “The others go to the plantation and do other activities.”

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’re 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, �鶹ԭ�� has worked to create applications that help smallholder farmers in developing nations, primarily across Africa, enhance food production.

David Balironda, KOPGT’s general manager, explains that the trust’s system is based on �鶹ԭ�� 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.

�鶹ԭ�� cloud technology also enables KOPGT to ensure that the oil palm planting meets the most stringent sustainability guidelines set by Uganda’s National Environmental Authority. “We 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,” says Fredrick Sulwe, KOPGT’s finance and administration manager.

As part of KOPGT’s 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. “Restoration of those areas – the lake buffer zones – is key,” 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. “As we increase household income, we must keep an environment that is free of any distortion by the project,” explains Sulwe.

The KOPGT system allows the farmers to input information about their crops using the lead farmer’s 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. “That means when I go to the bank to get a loan, I’m sure of the size of my lot,” explains Berna.

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

Better Information

She also credits the system with making her a better and more informed oil palm farmer. “At the end of the month I get an SMS that shows how much I have harvested from my lot,” 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.

“Oil palm has not only impacted my life, but also the community,” she says. “There 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. “I have started to achieve some of them,” she says. “Now, because I have a permanent house, I am able to sleep well, my children no longer get sick, and I’m sure that the winds won’t take my house.”

“Now, 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,” she adds. And although she doesn’t 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. “What 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.”

Berna’s 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 – compared to one or two seasonal harvests – 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’s 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’s authors – Wesley Spindler, Accenture’s global lead for Circular Economy, and E.J. Kenney, �鶹ԭ��’s SVP for the Consumer Products Industry.

“As we approach the midpoint of the Decade of Action, packaging – and in particular plastic packaging – continues to be a priority for consumer goods companies in their efforts to deliver both business and sustainability value,” say the two authors in the introduction to the report. “Packaging 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.”

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.

“Packaging is a waste challenge, a climate challenge, and a human health challenge,” 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 “very likely” 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, “We know that these opportunities are there for consumer goods companies that seize them. There has never been a better time to act – at speed and at scale. […] Drawing on our decades of experience collaborating for the success of our consumer goods clients and deep circular economy expertise, […] we view circular economy as the ‘Swiss Army knife’ of solutions for this challenge, not only supporting better planetary outcomes, but also delivering significant business value.”

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 – 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.

“Meaningful 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’t,” 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. “The future of packaging will extend the product’s 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,” 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. “Shifting 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.”

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

Even though consumer goods leaders face a growing mountain of regulatory challenges and complexity, they conclude that it’s clear that progress is possible, saying, “There is a path forward to a sustainable packaging future.”

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“Fifty years ago �鶹ԭ�� built the first ERP system, 30 years ago we made real time a reality, and 10 years ago we entered the cloud,” Saueressig said. “Today, 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.”

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

Alexander said she joined �鶹ԭ�� because the software industry is the place to have an impact. “Just think: �鶹ԭ�� 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.”

Jayakumar shared that she joined �鶹ԭ�� because of the company’s commitment to sustainability. She admires �鶹ԭ��’s aspiration toward a future with zero emissions, zero waste, and zero inequality. “That’s why I chose �鶹ԭ��.”

�鶹ԭ��’s raft of sustainability solutions for customers was the first of the innovations highlighted by Saueressig and Mueller. �鶹ԭ�� doubled down on its sustainability initiative in 2020 despite the pandemic, “because we were, and still are, truly committed to it,” Saueressig said.

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

help turn those fragmented supply chains into collaborative sustainable networks. The launch of �鶹ԭ�� Business Network for Industries at �鶹ԭ�� Sapphire is also a key part of the company’s strategy. “We are working on many industry-specific data networks, like Catena-X and Manufacturing-X,” said Saueressig. “But all of these networks are only possible if processes and data are seamlessly integrated.”

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.

“Our extended planning and analytics solutions span across financial planning, workforce planning, and demand planning,” Mueller explained. This allows �鶹ԭ�� 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 �鶹ԭ�� and non-�鶹ԭ�� systems, �鶹ԭ�� recently introduced .

“With �鶹ԭ�� Datasphere, you can create a data model consuming data from different sources like �鶹ԭ�� S/4HANA Cloud and �鶹ԭ�� BW/4HANA, and non-�鶹ԭ�� data sources like Google, BigQuery, and others,” Sangeetha explained during her demo. She added that �鶹ԭ�� 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 �鶹ԭ�� Analytics Cloud.

Saueressig cited �鶹ԭ�� Datasphere as an example of how �鶹ԭ�� is opening up more than ever, which is why �鶹ԭ�� has seen the partnerships announced in this area, including Databricks, DataRobot, Collibra, and Confluent, and now Google Cloud. “We truly believe in the democratization of data,” he said.

Mueller noted that �鶹ԭ�� has also recently announced AI partnerships with Aleph Alpha, IBM, and Microsoft. “But our key differentiator for you is how we use those technologies and embed these AI capabilities to reimagine business processes across all �鶹ԭ�� solutions,” he said.

“There’s no doubt �鶹ԭ�� is an AI company and �鶹ԭ�� AI is built into our systems that power your business,” Saueressig added. As of today, �鶹ԭ�� has delivered more than 130 embedded use cases of AI .

For example, �鶹ԭ�� 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. �鶹ԭ�� is already working on more than 80 use cases for generative AI.

�鶹ԭ�� 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 �鶹ԭ�� Analytics, Saueressig predicted that AI “will be infused everywhere and enable totally new capabilities in our products.”

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

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: “It’s a duet, not a duel.”

The keynote also revolved around how �鶹ԭ�� 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 �鶹ԭ�� Signavio solutions and how �鶹ԭ�� Build and �鶹ԭ�� Integration Suite can bridge the gap between business and IT.

“�鶹ԭ�� 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,” Mueller said.

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

“To summarize all these innovations, we enable risk resilient supply chains,” Saueressig said. “We connect your business to a broader network. We help you plan across the business. We infuse AI across the whole portfolio of �鶹ԭ�� and we want to provide you with a new intuitive user experience and collaboration capabilities, all enabled by our leading .”

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

�鶹ԭ�� Chief Marketing & Solutions Officer Julia White joined Klein from the Orlando show floor during the keynote to highlight �鶹ԭ��’s groundbreaking supply chain and sustainability initiatives, enterprise-wide automation, as well as how �鶹ԭ�� 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 �鶹ԭ�� solutions are helping solve those challenges.

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Klein told the audience in Orlando and those joining virtually: “Climbing 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 �鶹ԭ��… If we are in this together as one team, we will conquer any mountain.”

�鶹ԭ��’s 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. “We deliver on this vision through our cloud portfolio.”��

Early in his keynote, Klein said �鶹ԭ�� 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, �鶹ԭ�� software has been running the world’s most material and workforce-intensive business processes: “This is why we are convinced that embedding AI in �鶹ԭ�� software will deliver enormous value for your business.”

“Today we have already embedded AI in many of our applications that are being used by over 20,000 customers,” he said, “�鶹ԭ�� AI is built for business.”

As an example, he noted that in �鶹ԭ��’s finance solution, AI helps to predict and safeguard financial performance by analyzing a company’s pipelines, workforce, and other profit and loss drivers.

“We 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,” he said. “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.”

Klein noted that �鶹ԭ�� 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.��

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

“Thanks to the integration across �鶹ԭ�� Ariba, �鶹ԭ�� Business Network, and �鶹ԭ�� 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,” White said.��

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 �鶹ԭ�� Business Network for Industry.

To demonstrate the power of the network, Klein cited the life sciences industry. �鶹ԭ�� 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 �鶹ԭ�� Business Network.

Klein then described the management of a company’s overall carbon footprint as another key pillar for the success: “In 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.”

But he noted that hardly any enterprise has a comprehensive view of greenhouse gas emissions. “The �鶹ԭ�� sustainability portfolio will enable you to record, report, and act on actuals, not on averages, based on a green ledger — including scope three.”��

To explore this message, �鶹ԭ�� 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 �鶹ԭ�� innovations to track and manage emissions, as well as a new green ledger that will work with �鶹ԭ��’s cloud ERP to “provide natively integrated financial and environmental decision making at the required point in time.”

After introducing John Kerry’s video message to attendees, White added, “We can meet the climate challenge with a potent combination of technologies, partners in government, and all of you.” Klein then turned to the crucial role that data plays in running enterprises today and the recent launch of �鶹ԭ�� Datasphere, which enables customers to bring together and harmonize �鶹ԭ�� and non-�鶹ԭ�� data sources.��

After White and Klein explained how �鶹ԭ�� Signavio software enables end-to-end business process automation and the unique benefits of RISE with �鶹ԭ�� and the GROW with �鶹ԭ�� offering, which targets mid-market customers moving to �鶹ԭ�� cloud ERP, Klein wrapped up the keynote with an invitation to those in Orlando: “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 �鶹ԭ��, 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.”

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’s 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.”

Nigeria is Africa’s most populous country and largest economy. Even before the latest flood, it�� faced rising food insecurity as a combination of a mostly informal agriculture sector and growing population puts pressure on the country’s 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��. 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’s 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’s 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’s largest oil and liquified natural gas (LNG)�� producer, Nigeria is on the front line of the debate over sustainable development in the West Africa. It is also a key market for �鶹ԭ��, 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’s Dangote Cement unit already publishes an annual sustainability report, part of Aliko Dangote’s�� personal commitment to build “a socially responsible and impactful business that serves all stakeholders.” Dangote is also close to completing the Dangote Refinery, the world’s 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.

“We are having conversations with Dangote about some of our sustainability solutions and how they measure their impact on the environment,” says Titilayo Adewumi, regional sales director for West Africa at �鶹ԭ��.

Nigeria LNG is also committed to sustainability and is Africa’s 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. “If we don’t address this, we will not get out of this quagmire that we are in,” 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’s upstream suppliers, though he said Nigeria LNG’s 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 �鶹ԭ�� 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 �鶹ԭ�� 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 �鶹ԭ��.

Across the region, the bulk of �鶹ԭ�� customers are choosing cloud solutions rather than on-premise technology and �鶹ԭ�� 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 �鶹ԭ�� 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.

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

Business and technology leaders attending the recent �鶹ԭ�� Signavio Business Process Transformation Forum in Orlando, Florida were told that simply paying lip service to BPM is not enough.

“Business process is the DNA of any enterprise,” said Darwin Deano, a McKinsey partner and panelist . “You can talk about data and insights and all you want and you can talk about metrics, but what drives all of that is the business process.”

That’s particularly important today because, as �鶹ԭ�� Signavio Co-General Manager Gero Decker noted during his keynote, “We are living in a period of constant and extreme change.” The unexpected has become part of the expected and to succeed in this volatile environment, companies need to be innovative and excite customers and detect potential risks and priorities for improvements — all while being able to change things on the go, faster than ever.

Deano and fellow panelist Mathias Kirchmer, founder and co-CEO of consulting company BPM-D and affiliated faculty at the University of Pennsylvania, also had strong views on the relationship between business processes and innovation. Asked by Colleen Speer, senior vice president of Global Go-to-Market for �鶹ԭ�� Signavio, who chaired the panel, whether there was a danger that BPM might stifle innovation, Deano said: “Nothing could be further from the truth.

“A structured approach to process management provides a robust foundation for innovation and actually drives the full value of innovation,” he said. “Innovation without process management is service level and does not have a true north. So in my mind, it’s actually a requirement to drive innovation with process management.”

Kirchmer was in full agreement. In principle, he said, there are two ways that process management drives innovation. Many of the new digital native companies like eBay and Amazon have been founded based on new business processes. “To invent those processes in a systematic way, process management plays a key role,” he said; for example, by operationalizing design thinking.

“So process management enables process innovation, but process management also helps to improve the performance of your innovation process. That’s the second way BPM really drives innovation.”

During the forum, speakers also discussed how �鶹ԭ�� Signavio gives business experts visibility into all business processes and potential bottlenecks, and provides suggestions for improvement based on industry benchmarks and best practices. Organizations benefit from having a detailed understanding of their business processes, which they can then optimize with agility to succeed and thrive.

More generally, Kirchmer described BPM as “the management discipline that moves strategy into people and technology-based execution and does that fast and reliably.” At the end of the day, he told the audience, “it creates the transparency necessary to take fast, but well informed decisions and set the necessary actions.”

For any transformation, especially digital transformations, that discipline is key for two reasons, Kirchmer said. “First, every transformation delivers the value at the end through new and enhanced processes. To make that happen, you need the discipline of process management. Second, such a transformation is normally not just a project that ends at a certain point. It is a real journey, and the discipline of process management helps to navigate through that journey.”

Traditionally business process management has been about making business processes better, said Kirchmer, but he noted that in recent years the impact has become much broader. “In the last five or six years, I get almost more requests to talk about process standardization and harmonization than just about process improvement.”

“Process management can play a key role in identifying the right degree of standardization. It also plays a key role in prioritization — figuring out what are the high-impact processes and which of those are of a low maturity level — and process management not only helps during the project, but afterwards in value realization and in keeping those processes on track.”

Finally, Kirchmer noted that integrated process and data governance have become very important and a key component of the discipline of process management.

Echoing the same sentiments, Deano added that although business process optimization is viewed as the piecemeal application of technology, it is much broader than that. Implementing business process management means taking “an end-to-end holistic look at what is the true essence of the business,” he said. “That includes the end-to-end process knowledge, and it includes the alignment to the operating model required to actually execute that process because ultimately you can design the best process, but if you are not organized for success, it’s not going to yield the benefits you want.

“When positioning process management in an organization, it is important not just to discuss the required tools and techniques, but to stress the outcomes, the value it delivers,” said Kirchmer. “I always give the example if somebody asks you for the time, you don’t explain how the watch functions. You just tell them the time. And when you position process management at an executive level and you want to get people excited, you need to get them excited about what value it really brings – the quality, the efficiency, the agility, compliance and innovation.”

“To focus on outcomes and value, that is a very important first step to establish the discipline of process management,” he said.

She says her dream is to enable her children to be educated and become successful in life, benefitting both her and the community – one of 87 rural villages in West Africa’s Ivory Coast where farmers work with Cajooma SAS, the of Cashew Coast.

When she joined the village cooperative that Cashew Coast helped set up, the company trained her and taught her how to pick the best-quality cashews in order to fetch the highest prices.

Oyala has worked with Cashew Coast, a leading producer and distributor of high-quality cashew nuts for the past two years. Before that she worked alone. Now she works with other women in small groups, and that makes it easier to work. “I was alone, now we are working together,” she says.

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Video by Rana Hamzakadi and Matt Dillman

Ivory Coast is one of the world’s largest producers of cashew nuts, thanks to farmers like Oyala who, together with her fellow plot owners and farmers, pick the yellow and orange cashew fruit off the forest floor. Once harvested, the farmers must separate the nuts from the fruit they grow.

Unlike other companies that ship the raw nuts out of the country for processing, Cashew Coast process their nuts within Ivory Coast, lowering the carbon footprint. Nuts go directly from local farmers to Cashew Coast’s central warehouse in Bouaké to be sorted, weighed, and bagged before being sent to Cashew Coast’s organic factory in Azaguié for processing.

Until recently, Cashew Coast kept paper-based records of the farm-side of the process, but as the industry grew it became more and more difficult to keep track of the data and analyze it. Cashew Coast executives turned to �鶹ԭ�� for help when they realized that they needed a more advanced system to track the cashews from farm to processing plant — and eventually to table.

Joel Bagbila, Cashew Coast’s farmer integration director, explains that the company also has a loftier ambition. “Our mission is to be the first country worldwide in terms of production and quality,” he says.

To help achieve this goal, Cashew Coast chose to implement , an industry cloud solution built on the �鶹ԭ�� Business Technology Platform, at its Cajooma SAS branch. Cashew Coast’s digital transformation journey provides immediate benefits to the farmers, including more transparent prices, and enables the company to control quality and make much more timely decisions.

In the future it will also enable retailers to gain traceability and visibility into the origin of the cashew nuts and provide transparency to their consumers – connecting farmers and consumers in a profitable and sustainable value chain.

“Today, for a customer, it’s important to know where the product he or she is ready to buy, is coming from,” says Achta Cherif, head of quality at Cashew Coast. “Having this information enables the customer to make his/her choice. This is important for us, as well.”

Cashew Coast executives say they chose �鶹ԭ��’s cloud technology because it offered a number of key advantages. “We wanted the best in class, and we wanted to deal with the developer team as opposed to a third-party integrator – which �鶹ԭ�� Rural Sourcing Management offers,” says Salma Seetaroo, co-founder and CEO of Cashew Coast.

She says the implementation went surprisingly smoothly. “The �鶹ԭ�� implementation team were flexible and quick to understand our need – they were a bunch of millennials who loved working on a project like ours. And it was just great fun and I never expected it to be as smooth.”

�鶹ԭ�� is now remotely training two recent graduate recruits at Cashew Coast – Technology Manager Mohamed Traoré and Sales and Sustainability Manager Rose Koffi – to continue phase 2 of the �鶹ԭ�� Rural Sourcing Management implementation. Going forward, Salma explains, the company wants to bring more traceability to agricultural products in Ivory Coast with �鶹ԭ�� technology.

So, the next time you grab a handful of cashew nuts, consider this: there is a good chance they started their journey in the Ivory Coast and just maybe were picked up from the forest floor by Oyala or one of her friends.