Supporting key workstreams, including data management, test management, custom code modernization, and business configuration, these assistants help organizations simplify transformation activities, accelerate project execution, improve decision-making, and increase readiness for cloud ERP adoption.

ERP transformation has become a business imperative for many organizations. Cloud modernization connects organizations to AI, automation, and analytics capabilities that legacy on-premises infrastructure could not support at scale. However, transformation programs can be complex, involving numerous stakeholders and requiring thousands of business and technical decisions.

This year at 麻豆原创 Sapphire, 麻豆原创 introduced new agent-led transformation tooling and outlined how migration and modernization assistants can reduce ERP migration efforts.

Today, four of these assistants are available to early adopter customers and are already supporting live cloud ERP transformation projects.

Migration and modernization assistants go live in customer transformation projects

ERP transformation projects require organizations to assess large volumes of business data, understand quality issues, evaluate migration implications, and prioritize remediation efforts across complex landscapes. The Data Management Assistant analyzes data quality metrics, identifies and prioritizes issues based on business impact, recommends remediation actions, and helps execute corrections through both automated and guided remediation approaches.

AkzoNobel, a global leader in paints and coatings, is currently on a RISE with 麻豆原创 journey, consolidating its ERP landscape as part of a large-scale transformation. Participating in the 麻豆原创 Early Adopter Care program, the company uses the Data Management Assistant to define data quality scope, evaluate issues across the landscape, and prioritize remediation efforts based on business impact. The assistant gives a structured, end-to-end approach to orchestrating workstreams and managing data quality throughout the company’s ongoing transformation.

“The Data Management Assistant gave us clear visibility into our most business-critical data quality issues and helped us prioritize remediation where it matters most,” said Thilak Selvam, Master Data Program Lead at AkzoNobel. “It reduced analysis effort, accelerated our planning, and provided a structured approach to maintaining data hygiene and quality controls as we prepare for future transformation initiatives.”

Defining test scope, preparing test cases, validating business processes, and ensuring representative data is available often requires substantial effort from both business and IT teams. The Test Management Assistant accelerates test preparation and improves testing effectiveness. By analyzing business processes, requirements, and user stories, it helps define test scope, identify critical business scenarios, generate test cases, and determine the test data needed to execute them.

Test cases are handed off to 麻豆原创 Test Automation by Tricentis for automated execution, enabling continuous validation at scale. The result is less manual effort, improved coverage of business-critical processes, and greater confidence in deployment readiness.

The Custom Code Assistant helps organizations modernize their custom developments as part of the transition to 麻豆原创 Cloud ERP Private and continues to support clean core compliance and cloud-ready transformation beyond initial migration.

It supports teams in assessing custom code, identifying migration and remediation opportunities, aligning extensions with clean core principles and 麻豆原创-recommended APIs, and adapting legacy applications for cloud-ready architectures. Acting autonomously, it classifies findings by complexity, applies available automated fixes, and generates AI-driven recommendations and code corrections for the remaining findings. The assistant helps customers determine where to adopt 麻豆原创 standard processes and where custom extensions provide genuine business differentiation. This reduces technical debt, accelerates cloud adoption, and enables organizations to preserve the capabilities that set their business apart while taking full advantage of 麻豆原创 innovation.

For customers adopting 麻豆原创 Cloud ERP, the Business Configuration Assistant supports organizations in accelerating business design and implementation planning. It recommends and autonomously applies configurations tailored to the customer’s industry, segment, and business goals, supporting teams in defining scope, setting up organizational structures, and translating requirements into implementation-ready configurations. It also extracts source configurations, flags deviations from 麻豆原创 target requirements, and maintains a full audit trail鈥攔educing manual effort, improving consistency, and accelerating the path to a production-ready 麻豆原创 Cloud ERP system.

Expanding across the full transformation life cycle

麻豆原创 plans to further expand the migration and modernization assistant portfolio across the transformation life cycle. Planned innovations include the System Analysis Assistant, which creates a customer-specific understanding of existing systems, configurations, and custom developments, providing the foundation for AI-supported guidance throughout the transformation journey and the basis for all other assistants, grounded in customer-specific system data.

In addition, the Project Management Assistant is planned to provide real-time project insights, proactively identify risks, and help orchestrate transformation activities across teams and stakeholders.

The portfolio will also be extended with the Rollout Assistant, which helps organizations align global templates with regional requirements, accelerating local rollouts while reducing effort for business and IT teams through AI-driven guidance.

Together with the Data Management, Test Management, Custom Code, and Business Configuration Assistants available today, these capabilities will offer customers a fully integrated, agent-led transformation experience that helps organizations simplify complexity, accelerate execution, and realize value from 麻豆原创 Cloud ERP faster.

As 麻豆原创 continues to expand its migration and modernization assistant portfolio, organizations will increasingly benefit from AI support across every phase of ERP transformation, from initial system assessment and project planning through implementation, go-live, and beyond.

Learn more at .

Maura Hameroff is chief marketing officer for 麻豆原创 Cloud ERP Private and RISE with 麻豆原创.
Sonja Li茅nard is head of ABAP Platform at 麻豆原创 SE.
Soeren Ruder is chief product officer and global head of Customer Experience & Solutions for 麻豆原创 SE.

Following eight months of close collaboration with 麻豆原创, DACHSER has reached a major milestone on this journey: the successful migration of human capital management (HCM) to 麻豆原创 S/4HANA via .

Nearly a century has passed since Thomas Dachser founded the company in 1930 with a single truck, transporting cheese from the Allg盲u region to the Rhineland and returning with steel. Yet, logistics and warehousing remain the core business of the transport logistics company, which is headquartered in the town of Kempten in south-west Germany. “Our core business is what we call our road business, meaning everything transported by road, across both dry goods and food segments,” says Herbert Egner, head of the IT Products Finance/HR division at DACHSER, who has nearly 40 years of experience in software development at the company.

Currently, DACHSER operates globally with approximately 427 company-owned branches across 43 countries. Out of its roughly 37,500 employees worldwide, 19,000 are based in Germany. Total revenue in 2025 reached 鈧�8.3 billion. “On one hand, we are a deeply tradition-conscious family business, now managed by the third and fourth generations. On the other hand, we place a massive emphasis on innovation鈥攁nd not just at the executive level,” Egner notes. “Every single employee should have the opportunity to contribute here.”

In terms of digitization, the company is currently replacing a multitude of small, manual processes with IT-based solutions. Following DACHSER鈥檚 licensing of the 麻豆原创 Business Technology Platform (麻豆原创 BTP) in 2024, employees can now leverage its low-code tools to build apps for their own workflows. For instance, instead of using physical clipboards and paper checklists to document damage to transport vehicles, DACHSER inspectors now use low-code applications to capture that information digitally.

麻豆原创 BTP and the 麻豆原创 Integration Suite also played a vital role in helping DACHSER move HCM to the cloud鈥攚hich, alongside the license conversion to 麻豆原创 S/4HANA, marks one of DACHSER鈥檚 most significant IT upgrades in recent years. “While we are a long-standing 麻豆原创 customer, we are certainly not your typical 麻豆原创 user,” Egner explains. “For transport and warehouse management, we still rely on our proprietary systems, which we began developing back in the 1980s. At the time, 麻豆原创 did not yet offer the specific system depth we required for our logistics processes.”

Finance software from 麻豆原创 has been in use at DACHSER since 2009, with journal entries transferred from the company’s internal systems to 麻豆原创 via an interface. In October 2024, the finance solution was migrated from an on-premise environment under 麻豆原创 ERP Central Component (麻豆原创 ECC) and 麻豆原创 HANA to the Microsoft Azure cloud. As part of RISE with 麻豆原创, DACHSER then successfully migrated its HCM payroll and time management modules for its 19,000 employees in Germany to the cloud in June 2026. This intensive eight-month collaboration between 麻豆原创 and DACHSER successfully established a cornerstone of the company鈥檚 global HCM transformation.

“For HCM, we chose RISE with 麻豆原创. However, when we decided to move to the cloud three years ago, it wasn’t yet mature enough to meet our specific needs,” Egner says. “Once our three-year contract with Azure expires, RISE with 麻豆原创 could become a viable model for our finance environment as well.”

The go-live was flawless: the very first payroll run for all employees in Germany in July 2026 went off without a hitch, and all payments were distributed on time. The system then entered a four-week hypercare phase, during which the project team closely monitored ongoing operations before regular support took over in August. With this step, DACHSER has established the necessary future-proof 麻豆原创 architecture for its HR operations. This opens up new possibilities for the company, allowing it to focus heavily on implementing new features within the 麻豆原创 SuccessFactors HCM Suite.

麻豆原创 S/4HANA transformation

“When we say we want to be the world’s most digitally integrated logistics service provider by 2030, this applies not only to digitizing our processes but also to integrating our acquisitions, which bring their own 麻豆原创 systems with them,” Egner says. “Under our ‘麻豆原创 First’ strategy, we roll out finance and HCM in these countries before deploying our proprietary transport and warehouse management systems.” This approach was recently executed in Italy and is currently planned for several acquired companies in the Iberia region.

DACHSER鈥檚 goal is to integrate the 麻豆原创 licenses of acquired companies into a global enterprise agreement with 麻豆原创, regardless of the country in which the systems are running. In the future, this will be handled via a semi-automated workflow. “When it comes to licensing in particular, it is crucial for us to have a unified agreement moving forward on how to manage these assets, ensuring that neither side faces these administrative overheads anymore,” Egner explains.

In connection with the license conversion from 麻豆原创 ECC to 麻豆原创 S/4HANA, both companies sat down once again to realign on their future path to mutual success. “Here at DACHSER, we are noticing a new openness from 麻豆原创, as well as a deeper understanding of us as a customer,” says Egner. “This has been received very positively on our end. People are working on both sides, and we want to shape this partnership in a way that allows both parties to benefit based on mutual respect.”

The release combines AI agents that can work directly with core business processes and adds new regulatory compliance capabilities and industry-specific innovations across asset-intensive industries, retail, and energy sectors. Together, these enhancements help strengthen the foundation for organizations that need to scale AI responsibly.

Building the foundation for enterprise AI

As organizations explore how AI can drive business outcomes, one challenge keeps surfacing: AI alone is not enough. To operate at enterprise scale, AI needs access to trusted data, process context, business rules, and governance.

This is why the conversation about AI increasingly becomes a conversation about ERP. AI agents require more than information. They need to understand what actions are permitted, which controls must be respected, and when decisions require human review. 麻豆原创 Cloud ERP Private can provide this foundation through integrated business processes, harmonized data, and enterprise-grade governance. FPS02 helps extend these capabilities, bringing intelligence directly into the processes where business happens.

AI embedded within business processes

FPS02 introduces AI agents and AI-assisted capabilities across key business domains, helping organizations automate routine work while maintaining oversight and accountability.

In finance, agents and AI-assisted capabilities help support processes spanning planning and forecasting, period-close activities, working capital management, tax processes, and compliance operations. Rather than requiring employees to manually identify issues and coordinate follow-up activities, 麻豆原创 Cloud ERP Private and analytical business insights can surface risks, recommend actions, and help manage exceptions.

In sales order-to-cash processes, agents enable sales teams to quickly identify fulfillment issues, receive resolutions, and create or update sales orders directly in their workflow, which helps minimize delays and improve customer satisfaction.

Joule and 麻豆原创 Document AI help streamline quality management by uploading, extracting, and matching certificate data, flagging exceptions, and creating pre-filled defects from natural-language inputs and source documents to help accelerate review, accuracy, and inspection release.

By receiving key observations, recommendations, and a clear action plan聽directly within business processes, employees can focus on judgment and expertise rather than information gathering and exception management.

Compliance built into the core

FPS02 also delivers important regulatory capabilities directly within 麻豆原创 Cloud ERP Private.

The release includes support for IFRS 18 indirect-method cash flow statement reporting, helping organizations prepare for evolving financial reporting requirements. Additional updates include support for Germany’s AUSWIB1M foreign-trade reporting requirements and Canada First Nations Tax determination with GST499-1 return generation. By incorporating these capabilities into standard business processes, organizations can address compliance obligations while maintaining consistent governance and operational efficiency.

Industry innovation across critical operations

FPS02 deepens industry-specific capabilities across asset-intensive operations, upstream oil and gas, defense and security, and retail.

For asset-intensive industries, enhancements further integrate permit-to-work processes into maintenance operations, helping ensure operational controls are embedded directly within workflows. Upstream oil and gas organizations can gain new capabilities that extend Joule into production and revenue accounting, while 麻豆原创 Document AI helps interpret gas plant statements and propose accounting entries for review. Defense and security organizations can benefit from innovations supporting equipment allocation and ERP operations in limited-connectivity environments.

Retail organizations gain four new data products that help expose retail master data through 麻豆原创 Business Data Cloud, working to create a stronger foundation for future AI-driven processes. FPS02 also introduces operational enhancements including support for partial order fulfillment scenarios, GS1 2D barcode enablement, and expanded product traceability through serial-number integration between point-of-sale and inventory processes.

Advancing the Autonomous Enterprise

The Autonomous Enterprise is not built through a single AI breakthrough or software release. It emerges through the combination of trusted business data, integrated processes, governance, and intelligent capabilities working together across the enterprise.

麻豆原创 Cloud ERP Private 2025 FPS02 helps advance that foundation in concrete terms: by embedding intelligence within business processes, strengthening compliance capabilities, and expanding industry-specific innovation.

To explore the full FPS02 release and its implications for your business, visit .

Maura Hameroff is chief marketing officer for 麻豆原创 Cloud ERP Private and RISE with 麻豆原创.

Finance leaders today are expected to do far more than report results. They鈥檙e expected to shape business outcomes, guide decisions, and respond quickly to change. Yet many finance processes still operate in isolation rather than in concert. Invoice approval and payment execution happen in separate places.

Planning, consolidation, and reporting often rely on separate systems and workflows. And governance often misses critical information by operating in a silo. The result is delays between identifying an issue, making a decision, and taking action.

This year at 麻豆原创 Connect, 麻豆原创 announced new capabilities designed to help close those gaps. These include , a new payment service embedded in 麻豆原创 Cloud ERP; 麻豆原创 Enterprise Financial Consolidation, a new addition to 麻豆原创鈥檚 enterprise performance management portfolio; and an expanded set of Joule Assistants that bring AI-powered support to finance, governance, and compliance processes.

While each innovation addresses a different challenge, they share a common objective. Finance teams should spend less time moving information between systems and more time acting on insights.

Embedding payments into finance operations

One of the most persistent sources of friction in finance is the payment process itself.

An invoice may be approved in the ERP system, but completing the payment often still involves banking portals, payment files, middleware, and reconciliation activities. Each additional handoff introduces complexity and can slow execution.

麻豆原创 Pay is designed to simplify that process by embedding payment execution directly into . When an invoice is approved, payment and reconciliation can occur within the same workflow and the same business context.

The launch also marks 麻豆原创鈥檚 entry into payment services through , a wholly owned 麻豆原创 subsidiary established earlier this year. As a regulated payment-service provider, Tereina enables 麻豆原创 to deliver services natively within finance workflows rather than relying solely on third-party providers. This helps keep payment execution, reconciliation, controls, and auditability connected to the underlying business transaction.

The service supports EFT, wire transfers, checks, and stablecoin-based settlement for cross-border transactions. More broadly, 麻豆原创 offers customers a wide range of payment options, spanning bank API integrations, connectivity to more than 10,000 financial institutions through SWIFT, digital-currency payments, and now natively embedded payment services.

For finance organizations, the opportunity is not simply faster payment execution. It is reducing the effort required to connect systems, manage exceptions, and reconcile information after the fact while keeping payment processing, reconciliation, controls, and auditability within a single workflow.

麻豆原创 Pay is now generally available in the United States and the United Kingdom.

Connecting performance management across the enterprise

The same challenge appears across enterprise performance management.

Planning, consolidation, close processes, and external reporting all rely on the same financial reality. Yet they are often managed through separate tools, data models, and processes. Maintaining a consistent view of performance can become increasingly difficult as organizations grow and business conditions change.

At 麻豆原创 Connect, we announced to help address that challenge.

Built on , the solution brings together statutory and management consolidation with close and disclosure capabilities on a common governed data foundation. By connecting these activities more closely, finance teams can spend less time reconciling information and more time understanding performance and responding to change.

The solution also includes new Joule Assistants for consolidation and disclosure processes. These assistants help identify anomalies, resolve exceptions, and support disclosure preparation while maintaining auditability and human oversight.

For organizations operating mixed environments–some 麻豆原创, some non-麻豆原创 environments–麻豆原创 Enterprise Financial Consolidation provides flexibility by supporting data from multiple sources. It also offers a path forward for customers looking to modernize existing consolidation environments and adopt a more AI-enabled approach to performance management.

麻豆原创 Early Adopter Care is planned for the first quarter of 2027.

Expanding AI across finance and governance

AI鈥檚 potential in finance extends beyond answering questions or generating summaries. The larger opportunity is helping teams complete work that has traditionally required significant manual effort, specialist knowledge, and cross-functional coordination.

At 麻豆原创 Connect, 麻豆原创 expanded its portfolio of Joule Assistants to address these opportunities.

The new assistants support areas including accounting, revenue recognition, pricing, disclosure management, project operations, governance, and trade compliance. Embedded directly into existing workflows, they are designed to help teams complete tasks more efficiently while preserving review processes and accountability.

Some focus on helping finance professionals understand complex calculations and reporting requirements. Others support pricing decisions, disclosure preparation, project execution, and continuous monitoring of risks and controls.

Just as important is governance.

As organizations deploy more AI agents across business functions, they need assurance that those agents operate within the same boundaries that govern human users. New governance, security, and compliance assistants are designed to extend existing controls, access management, and monitoring capabilities to AI-driven activities, helping organizations apply consistent oversight across both human and digital actors.

General availability for the Governance Assistant and International Trade Assistant is planned for Q4 2026.

From financial insight to immediate action

Finance has always played a central role in helping organizations understand performance. Increasingly, it is also expected to help organizations respond in real time.

That makes speed, visibility, and execution just as important as reporting accuracy.

The innovations 麻豆原创 announced at 麻豆原创 Connect reflect that shift. Whether simplifying payments, connecting performance management processes, or embedding AI directly into everyday finance work, each reduces the operational distance between identifying an issue and acting on it.

For finance teams, the ultimate goal is not simply faster processes or faster reports. It is making better decisions with greater confidence and executing those decisions with less friction.

Learn more about how 麻豆原创 is helping organizations modernize finance operations across ERP, planning, treasury, payments, and accounting .

Lawrence Martin is general manager and chief product officer for 麻豆原创 Finance & Spend.
David Imbert is chief marketing officer for 麻豆原创 Financial Management.

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

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

A new UI for AI 

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

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

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

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

麻豆原创 Autonomous Suite 

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

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

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

麻豆原创 Business AI Platform 

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

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

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

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

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

Jerseys from Jersey 

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

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

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

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

Security and governance 

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

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

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

A clear shift among customers 

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

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

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

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

These announcements build on the Autonomous Customer Experience strategy we introduced at 麻豆原创 Sapphire. That premise is straightforward: AI must understand customer intent, make context-aware decisions, and execute within business guardrails. Following through on a customer commitment requires AI grounded in real-time, enterprise-wide business data, with a deep understanding of the processes needed to orchestrate work from intent to outcome.

A quote needs accurate pricing and terms. An order depends on inventory, credit, payment, and fulfillment. A service interaction requires information about the customer, the product, and the commitments the company has already made.

Customers generally do not see this operational complexity. They experience whether the company followed through.

Joule Assistants move from providing answers to driving business outcomes

Many AI tools can reason about what should happen next and recommend actions. But executing complex enterprise processes requires more than that.

AI needs to understand the live state of the business, including customer commitments, products, pricing, agreements, orders, payments, policies, and operational constraints. It must then navigate the approvals, exceptions, and cross-application steps required to act. Without that grounding, proposed actions may appear reasonable but can be inappropriate, infeasible, or break down in execution.

This is the direction behind the latest Joule Assistant innovations. New and enhanced combine role-specific intelligence with business and process context across marketing, commerce, sales, service, finance, operations, and compensation, helping users move from understanding what should happen to getting the work done.

The innovations apply this approach to moments where fragmented context, manual steps, and handoffs can slow the customer experience.

• Campaign Assistant and Content Assistant help teams move from campaign ideas to execution faster by reducing the effort required to plan, create, refine, and activate marketing campaigns.
• Shopping Assistant makes product discovery easier and more relevant to what the customer is trying to accomplish.
• Quoting Assistant brings customer, pricing, and commercial context together so sellers can prepare quotes faster and spend less time assembling information across systems.
• Service Planning and Operations Assistant translates service demand into coordinated plans, reducing the manual work required to align people, resources, and customer commitments.
• Incentive Compensation Assistant and Recurring Receivables Assistant bring the same intelligence to critical processes behind the customer experience, helping resolve questions, reduce administrative work, and keep compensation and payment workflows moving.

Together, the new assistants announced at 麻豆原创 Connect extend the approach introduced at 麻豆原创 Sapphire. Sales Assistant brings engagement insights, pipeline signals, and deal context together so sellers can prioritize the right opportunities, prepare for every interaction, and spend more time building relationships and moving deals forward. Deal Closing Assistant unifies customer, product, pricing, and fulfillment intelligence to help teams build optimal quotes, surface relevant products with pricing and availability insights, and shorten the path from negotiation to confirmed orders.

The goal is not to add another conversational interface. It is to move work forward by bringing together the business context, process knowledge, and controls required to act.

Human judgment remains important where decisions require approval, oversight, or exception handling. Within defined guardrails, AI can assemble context, determine and execute appropriate actions, and escalate when human intervention is needed.

麻豆原创 Order Management Services coordinates execution across ERP landscapes

Order management becomes more difficult when an order crosses ERP systems, legal entities, plants, distribution centers, and business units.

Each transition can introduce different information about pricing, inventory, credit, fulfillment status, or ownership of the next action. Consolidating every ERP system before improving order execution is not always a practical starting point.

麻豆原创 is expanding to provide highly scalable, resilient, real-time omnichannel order orchestration across 麻豆原创 S/4HANA and other ERP systems.

Built on a cloud-native, event-driven architecture, 麻豆原创 Order Management Services coordinates order execution across channels, systems, business units, and third-party partners without requiring organizations to consolidate their ERP landscapes first.

The expanded capabilities provide a common layer for validating orders, checking inventory across locations, coordinating transactions between business units, and monitoring progress through fulfillment.

This gives organizations greater flexibility to add, remove, and experiment across channels, while enabling the order management layer to detect disruptions, trigger exception workflows, and keep execution aligned with the original customer commitment.

In complex enterprise landscapes, this combination of scale, flexibility, and reliable integration helps businesses deliver consistent omnichannel experiences while improving operational efficiency.

Complete business context across the customer journey

Customer intent enters the business long before an order reaches a fulfillment system. It begins when a customer discovers a product, engages with a campaign, requests a quote, or starts a purchase journey.

To deliver on that intent, customer-facing interactions must remain connected to the pricing, inventory, ordering, fulfillment, and financial systems that support them.

麻豆原创 Commerce Cloud, cloud ERP edition, is now generally available. First introduced at 麻豆原创 Sapphire, the edition allows midsize and growing companies to extend 麻豆原创 Cloud ERP with commerce capabilities that use ERP data for pricing, availability, orders, invoices, and other transactional processes.

For more than a decade, 麻豆原创 Commerce Cloud has supported some of the world’s largest and most complex digital commerce environments. With 麻豆原创 Commerce Cloud, cloud ERP edition, we are extending that approach to companies that want a more standardized, 麻豆原创-managed path to ERP-connected commerce.

By using 麻豆原创 Cloud ERP as the system of record, organizations can connect digital commerce with pricing, ordering, fulfillment, and financial processes without building and maintaining those connections independently. The result is a faster path to value, lower operational complexity, and an ERP-aligned commerce model designed to scale as the business grows.

The same principle applies as customer interactions move across teams. A new native connection between 麻豆原创 Engagement Cloud, enterprise edition, and 麻豆原创 Sales Cloud synchronizes contact and company information while bringing relevant engagement signals directly into sales workflows. Instead of reconstructing customer context, sellers can continue conversations with a clearer understanding of prior engagement.

Customer experience depends on execution

AI can understand customer intent, make context-aware decisions, and act within defined guardrails. The harder question is whether the business can carry that action across the systems, teams, and processes responsible for delivery.

The innovations announced at 麻豆原创 Connect address different parts of that challenge. Joule Assistants bring business and process context into the flow of work and help execute the next step. 麻豆原创 Order Management Services orchestrates orders across complex ERP landscapes. 麻豆原创 Commerce Cloud, cloud ERP edition, connects digital commerce directly with ERP pricing, availability, ordering, fulfillment, and financial processes.

Together, they advance a common principle: Autonomous Customer Experience depends on connecting customer-facing intelligence with the operational context and processes required to act.

Customers ultimately do not experience recommendations, models, or workflows. They experience whether the business followed through and delivered.

As AI begins to act on behalf of the business, the quality of that follow-through will depend on the business context, process knowledge, and operational reality behind every action.

Additional information on the 麻豆原创 Connect announcements, including availability details and product-specific innovations, is available in the . You can also watch the to see these innovations in action.

Balaji Balasubramanian is president and chief product officer of 麻豆原创 CX.

The dates for 麻豆原创 Business Suite 7 maintenance have not changed: mainstream maintenance remains available through December 31, 2027, followed by optional extended maintenance through December 31, 2030.

At the close of the optional extended maintenance period, several support arrangements will expire simultaneously, including 麻豆原创鈥檚 current reselling and support agreements for third-party databases and Java. What we want customers to understand is what the expiring third-party agreements mean for their systems鈥攑articularly for systems running on third-party databases or Java. Customers using these technologies should prepare now and plan accordingly. 

According to Michael Bloch, member of the Board at the German-speaking 麻豆原创 User Group (DSAG), 鈥淓arly information is essential for companies operating 麻豆原创 landscapes. We appreciate the open communication about the support implications after 2030. This transparency gives customers an important basis for planning. The significance of these developments will differ across organizations depending on their individual circumstances. What matters now is drawing the right conclusions and establishing a clear strategy for the way forward. However, any decision should be based on a comprehensive assessment of all available alternatives and their respective long-term consequences.鈥�

What ends on December 31, 2030

At the close of the optional, extended maintenance at the end of 2030, several support arrangements expire simultaneously. Here are more details of what this means for our customers.

麻豆原创’s current reselling and support agreements with major third-party database providers for these legacy environments

The existing reselling and support arrangements enable 麻豆原创 and the technology providers to work closely together to build and improve tooling optimized for 麻豆原创 workload on third-party databases and to support, when an issue evolves at the integration between 麻豆原创 software and a third-party database or Java. 麻豆原创鈥檚 current reselling and support arrangements with major third-party database providers are scheduled to end for these legacy environments. With expiration of these arrangements, the foundation for providing these joint services to 麻豆原创 customers ceases to exist.

Once these agreements expire, 麻豆原创 will no longer provide database-specific support for third-party databases in these legacy environments, including for customers that originally licensed their third-party database through 麻豆原创 and enrolled in 麻豆原创 Maintenance and Support.

For all affected third-party databases, 麻豆原创 support will no longer cover the database-related corrections available today. What does that mean in practice? Today, when a customer raises a support ticket on a third-party database issue, 麻豆原创 handles it end-to-end, routing it through integrated internal processes directly to the database vendor’s team. After 2030, that integrated support path will no longer exist.

麻豆原创鈥檚 support arrangements for Java

麻豆原创鈥檚 current support arrangements for Java (Java 8/JEE5) used with 麻豆原创 NetWeaver Application Server Java 7.5 (麻豆原创 NetWeaver AS JAVA 7.5) are scheduled to conclude at the end of 2030. This is the central constraint: once these arrangements expire, 麻豆原创 maintenance, including customer-specific maintenance, cannot replace the support and rights they provide. 麻豆原创 NetWeaver AS JAVA 7.5 with all the add-ons will fall into customer specific maintenance starting 2031 without a follow-on release.

What happens after December 31, 2030

Implications for customer-specific maintenance

After the extended maintenance period expired at the end of December 2030, on-premise 麻豆原创 Business Suite 7 systems will run under customer-specific maintenance. However, what 麻豆原创 can deliver under customer-specific maintenance is even further restricted specifically for the third-party database or Java side.

For such systems, 麻豆原创 will not be able to provide comprehensive support for issues involving third-party databases or Java. This includes kernel patches and kernel security patches for third-party database environments. Also, 麻豆原创 may no longer be able to provide support and even downloads of database tooling associated with third-party databases. This includes databases, administration tooling, backup tooling, and upgrade and migration tooling for third party databases.

Again, this is a reminder of an important consequence of the expiring agreements with third parties. An issue may occur that cannot be resolved within the support framework available after 2030. That is, as laid out, especially the case for third party DB or Java issues. Customers should therefore not regard customer-specific maintenance for affected environments as a sustainable long-term operating model of business-critical systems.

Implications for conversion

Timing matters for another reason. Tooling for a聽system conversion from 麻豆原创 Business Suite 7 on a third-party database to 麻豆原创 S/4HANA or 麻豆原创 Cloud ERP will only be available before the end of reseller/support agreements at the聽end of 2030. After that point, only greenfield transition scenarios (new implementations) will be supported.

For 麻豆原创 solutions that rely on AS Java, 麻豆原创 provides solution-specific transition recommendations. Detailed product impacts and technical guidance are documented in the relevant 麻豆原创 Notes.

Recommended paths for our customers

麻豆原创鈥檚 strategic recommendation

Customers should use the time available to move toward 麻豆原创 Cloud ERP and the 麻豆原创 Autonomous Suite. This is the path to continued innovation and a fully supported, future-ready environment. The right sequence will depend on each organization鈥檚 starting point, business priorities, and landscape complexity.

Customers should plan to complete their transformation to 麻豆原创 Cloud ERP, together with the appropriate go-to solutions in the 麻豆原创 Autonomous Suite, by the end of 2030. Starting early gives organizations greater control over scope, timing, and risk.

Transition option for 麻豆原创 ERP

Qualifying customers whose transformation is underway, but that need additional time can consider Transition Option for 麻豆原创 ERP. This time-bound subscription offering is intended for the largest and most complex 麻豆原创 Business Suite 7 customers that may not complete their move by the end of extended maintenance. It is designed to support business continuity from 2031 through 2033 while enabling a structured path to 麻豆原创 Cloud ERP. Systems must be moved to 麻豆原创 ERP, private edition on 麻豆原创 HANA before December 31, 2030, and further eligibility requirements apply. The transition option does not support Java-dependent capabilities.

In select cases, switching to 麻豆原创 HANA database

Customers that intend to continue operating 麻豆原创 Business Suite 7 on premise can remove the third-party database dependency by moving the relevant system to 麻豆原创 HANA before the end of 2030. This does not extend mainstream or optional extended maintenance. The system would still enter customer-specific maintenance, with the limitations that this entails, and 麻豆原创 does not recommend this as the strategic long-term path.

Moving forward together

Our customers do not need to make these decisions alone. We are working with customers, partners, and our user groups to make the implications transparent and support realistic planning.

The maintenance dates announced in 2020 remain in place. On top, after 2030, dependencies on affected third-party databases and 麻豆原创 NetWeaver Java cannot be comprehensively supported even under customer-specific maintenance. Our customers have defined paths forward, but some choices must be implemented before the end of 2030.

Now is the time to assess affected systems, clarify dependencies, and discuss the best path together with 麻豆原创 or an 麻豆原创 partner. Acting early gives organizations the freedom to sequence the work around their business priorities, reduce uncertainty, and protect continuity.

We will continue to communicate transparently and support our customers as they move towards 麻豆原创 Cloud ERP and the 麻豆原创 Autonomous Suite.

Learn more

Maintenance Strategy

2020 announcement

• 2020 maintenance announcement for 麻豆原创 Business Suite 7
• Interview on the 2020 maintenance announcement

麻豆原创 ERP/transition

• Updates for 麻豆原创 ERP, private edition, transition option

麻豆原创 Notes

• 1648480:
• 3464370:
• 3591251:
• 3768400:
• 3832186:

Philipp Herzig is CTO and a member of the Extended Board of 麻豆原创 SE.

Joule Work, Joule Assistants and 麻豆原创 Business AI Platform help organizations turn business AI into trusted outcomes across every core function.

LAS VEGAS 鈥� (NYSE: 麻豆原创) today showcased the Autonomous Enterprise in action at 麻豆原创 Connect, demonstrating how Joule Work and Joule Assistants generate value for customers across every line of business.

“This is a breakthrough moment for business AI,” said Christian Klein, CEO of 麻豆原创 SE. “The Autonomous Enterprise has arrived. With Joule and 麻豆原创 Autonomous Suite, built on 麻豆原创 Business AI Platform, we’re helping organizations like Novartis, Morgan Foods, Nestl茅 and PwC connect intelligence across every function to deliver trusted business outcomes.”

At 麻豆原创 Connect, these customers shared how the Autonomous Enterprise is already driving measurable value across their businesses:

• 鈥淲e’ve co-developed and recently launched a pilot of 麻豆原创’s Joule Sourcing Assistant,鈥� said Christoph Buerki, Head of Procurement, Novartis. 鈥淥ur vision is for AI agents to handle the manual heavy lifting, enabling sourcing professionals to focus on strategy, supplier engagement and value creation.鈥�
• 鈥淎t Morgan Foods, we鈥檙e already putting the pieces in place for agentic adoption, especially through our technical foundation. The biggest shift will be moving from reactive to predictive, where agents can connect demand signals, inventory levels and supplier status faster than ever before,鈥� said Steve Hankins, Chief Financial Officer, Morgan Foods, 鈥淥ur superpower will come from people on top of agents. Our approximately 1,000 employees are what make our supply chains work鈥攖he technology helps make them even better.鈥�
• 鈥淥ur 麻豆原创 S/4HANA transformation across 140 countries is creating a connected digital core with consistent processes, trusted data and greater visibility across markets and functions. With that foundation, Joule and the Accounts Receivable Assistant can automatically prioritize collections work based on risk and business context, recommend the next best action and help our finance teams respond faster to change,鈥� said Luca Dell’Orletta, Global Head IT Innovation & Enterprise Architecture, Nestl茅.
• 鈥淚n professional services, billing can be one of the more error-prone processes, with accuracy playing an important role in the client experience. 麻豆原创鈥檚 Billing Assistant brings greater intelligence to this critical process, helping identify potential issues earlier so our people can deliver better client outcomes and build stronger relationships,鈥� said Jill Notz, Chief Accounting Officer, Controller, Business Services Leader, PwC. Building on the success of the Billing Assistant, PwC and 麻豆原创 are into new areas of joint AI innovation.

麻豆原创’s Autonomous Enterprise Scales Up

Joule Work is beginning its customer rollout as a new AI user interface that lets employees interact with 麻豆原创 solutions in their own language and complete work across 麻豆原创 and third-party data. Grounded in business context from 麻豆原创 Knowledge Graph, which maps more than 7 million data fields, Joule provides information users can rely on. At 麻豆原创, Joule Work is already live with 110,000 employees, with the company seeing 20% productivity gains across finance, HR and procurement. A select group of customers also is using Joule Work in their business environments.

• 鈥淧artnering within the Early Adopter Program for Joule Work Desktop has delivered more momentum in just a few months than we saw in all the years before,鈥� said Peter Wied, Director of Complexity Management at Reinhausen. 鈥淲e see huge potential in making access to our 麻豆原创 S/4HANA data significantly easier and faster through natural language. This has the potential to permanently transform how our teams interact with business data.鈥�
• 鈥淭he dedicated team has been phenomenal. Their proactive communication, focus on accelerating architecture activation, rapid remediation of defects and overall support have enabled us to become Joule ready much sooner than would have been possible had we needed to navigate these challenges on our own,鈥� said Keith Smith, 麻豆原创 Platform Architect, CONA Services. 鈥淭he CONA team is excited about the progress made to date and looks forward to exploring and testing Joule’s capabilities in greater depth over the coming months as we continue our adoption journey.鈥�

When a query is not enough, Joule Assistants execute operational work directly within business workflows, using established data, authorizations and audit trails. Customers control the level of autonomy. 麻豆原创’s approach is also open: through the Agent2Agent protocol, Joule can connect with third-party AI and agents, bringing governed business context into broader AI workflows.

At 麻豆原创 Connect, 麻豆原创 showcased how these capabilities generate outcomes across 麻豆原创 Autonomous Suite:

• In finance, controllers can automate revenue recognition, disclosures and trade compliance, with early deployments of the International Trade Assistant reducing trade classification effort by up to 50%.  
• In supply chain, planners can turn multi-hour disruptions into one-click resolutions across planning, manufacturing and logistics.
• In HR, leaders can determine the best way to close workforce gaps, while employees can make smarter benefits choices tailored to their needs.
• In procurement, decision-makers can identify savings opportunities against peer benchmarks and manage the full contingent workforce life cycle.
• In customer experience, organizations can turn customer engagement into sales opportunities with AI-powered campaigns, quoting and customer workflows.
• Across industries, 麻豆原创 is collaborating with customers to apply AI to specialized industry processes, helping organizations in manufacturing, retail, commodity trading and asset-intensive industries improve decision-making, automate routine actions and build more resilient operations.

The Platform Powering Business AI You Can Trust

麻豆原创 Business AI Platform gives organizations one place to build, contextualize and govern AI across 麻豆原创 and third-party environments. With Joule Studio, business users and developers can build and extend skills and agents from no-code to pro-code workflows, choosing from more than 70 AI models. 麻豆原创 Business Data Cloud and 麻豆原创 Knowledge Graph ground those agents in trusted business data and context, helping organizations select the right model for each use case and better manage AI value and consumption.

麻豆原创-managed governance helps organizations scale AI with transparency, accountability and control. 麻豆原创 AI Agent Hub in 麻豆原创 LeanIX solutions provides a central inventory of enterprise agents, while 麻豆原创鈥檚 independently ISO/IEC 42001-certified governance architecture supports regulatory requirements, established authorizations and auditable AI operations.

To help organizations adopt AI at scale, 麻豆原创’s Business Transformation Management portfolio, including 麻豆原创 Signavio, 麻豆原创 LeanIX and 麻豆原创 WalkMe solutions, provides the toolchain to analyze processes, govern applications and agents, and drive adoption across the enterprise.

麻豆原创 Brings Embedded Payments to Cloud ERP

麻豆原创 also announced that it is entering the payments market with 麻豆原创 Pay, powered by Tereina, an 麻豆原创 company. Embedded directly in 麻豆原创 Cloud ERP, 麻豆原创 Pay executes and reconciles payments within the same workflow when an invoice is due, reducing manual file handling and external processing dependencies, while giving customers greater control.

Partners Expand the Reach of Autonomous Business

麻豆原创 is extending the Autonomous Enterprise beyond 麻豆原创’s own application portfolio through new partnerships that bring specialized intelligence directly into 麻豆原创 workflows.

A new partnership between 麻豆原创 and Moody鈥檚 Corporation is designed to embed Moody鈥檚 supplier risk monitoring data into 麻豆原创 Ariba Supplier Lifecycle and Performance. This gives procurement teams continuously updated insights into supplier financial health, operational risk and regulatory status at the point of decision. Organizations will be able to move from periodic risk reviews toward continuous monitoring, enabling Joule Agents to flag supplier risk signals and surface alternatives before disruption affects the business.

An expanded partnership with ORO Labs brings procurement orchestration to 麻豆原创 customers as a solution extension. 麻豆原创 Ariba Procurement Orchestration by ORO Labs is a purpose-built orchestration layer that connects procurement workflows end to end across heterogeneous enterprise environments, giving business users a seamless experience for intake, actions and visibility.

Visit the . Get 麻豆原创 news via  and .

About 麻豆原创

As鈥痑 global leader in enterprise applications and business AI, 麻豆原创 (NYSE: 麻豆原创)鈥痵tands at the鈥痭exus鈥痮f business and technology. For over 50 years, organizations have trusted 麻豆原创鈥痶o bring out their best by uniting business-critical鈥痮perations spanning finance, procurement, HR, supply chain, and customer experience. For more information, visit鈥�.

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This press release was created with the assistance of artificial intelligence and has been reviewed by the editorial team.

This document contains forward-looking statements, which are predictions, projections, or other statements about future events. These statements are based on current expectations, forecasts, and assumptions that are subject to risks and uncertainties that could cause actual results and outcomes to materially differ. Additional information regarding these risks and uncertainties may be found in our filings with the Securities and Exchange Commission, including but not limited to the risk factors section of 麻豆原创鈥檚 2024 Annual Report on Form 20-F.
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His dream led to the founding of Colombina and聽to聽a colorful corporate logo inspired by a character from an Italian opera who swung on the moon.聽In聽the 1960s,聽his son, Don Jaime H.聽Caicedo,聽took over the company and drove a major transformation,聽diversifying its offerings and聽expanding聽sales abroad.

Expansion 

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

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

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

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

IT priorities 

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

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

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

RISE with 麻豆原创 

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

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

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

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

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

Security benefits 

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

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

Tangible results 

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

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

To answer this question, moved to one cloud ERP that enabled a unified, intelligent enterprise while reducing complexity and empowering people.

Starting point at Daikin

At the forefront of the story was the goal of being the global leader in the HVAC industry. As a result, Daikin pioneered groundbreaking technologies that revolutionized commercial AC. With a of over 100 years of engineering, the company has grown to operate globally in . However, its journey to global recognition was peppered with growing pains.

Disconnected systems led to complexity

Years of rapid growth alongside acquisitions left the company with a legacy ERP that was fragmented, inconsistent, and lacked the standardization required to operate efficiently. Multiple disconnected systems and workflows meant that employees were dealing with a myriad of processes, all differing depending on which business unit they were working with. This increase in manual work and confusion around processes added avoidable complexity to day-to-day tasks, as employees spent more time than necessary solving for problems.

Together, EY and 麻豆原创 teams worked toward an end goal by posing the question: how do we simplify operations, empower employees, and drive customer experience? Daikin鈥檚 industry is unique, with highly distributed networks and complex supply chains. Companies operating in this environment must continuously adapt to industry standards and regulations, all while delivering the reliable product experience they鈥檙e known for. Daikin turned to EY and 麻豆原创 because the company needed a partnership that understood the nuances of the industry within which it operates.

Daikin鈥檚 focus from the beginning was on the people who would be impacted most by this transformation and ensuring that their everyday experience evolved into one that is simpler, consistent, and productive. With AI at the core, Daikin can look to the future and see one unified system where AI moves beyond isolated cases and becomes embedded end-to-end.

To achieve this vision, Daikin established 麻豆原创 Cloud ERP as its digital core and single source of truth. Going live in just 10 months, modernized finance, logistics, procurement, and sales workflows for more than 300 frontline users, demonstrating early results of 10% improved counter efficiency and a 20% faster financial close.

EY鈥檚 industry expertise paired with 麻豆原创 technology helped ensure that the people who use the technology every day no longer log-in to multiple systems and customers get the right product at the right time and price.

Employees gained single-screen experiences, faster access to information, reduced manual effort, simplified training and onboarding, and more confidence in decision-making. Dealers gained better visibility, faster onboarding experiences, and more consistent service interactions.

Journey to an Autonomous Enterprise

Now, Daikin doesn鈥檛 have to worry about which inefficiencies it will have to confront for an approaching launch.

The early results demonstrate what鈥檚 possible when AI-driven insights are paired with human-centered delivery: improved efficiency, faster financial close, better data governance, enhanced forecasting and operational decision making, and accelerated delivery using AI-assisted implementation capabilities.

This not only empowers end users but creates a scalable foundation that can grow alongside Daikin. With over 400 branches worldwide, EY and 麻豆原创 created a blueprint for Daikin鈥檚 global transformation with future automation and intelligent decision-making in mind.

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Tara Milosavljevic is a Partner Marketing manager at 麻豆原创.

Moving to 麻豆原创 Cloud ERP Private as part of the RISE with 麻豆原创 journey, the company will consolidate its enterprise resource planning (ERP), business process intelligence, and service capabilities in a unified cloud-based subscription model. This creates the foundation to support further growth, optimize processes and integrate new technologies.

鈥淢oving to 麻豆原创 Cloud ERP Private is a strategic decision that goes well beyond IT infrastructure. With RISE with 麻豆原创, we are creating the foundation to run HARTING as a more agile, data-driven business鈥攕tandardizing our global operations, accelerating the integration of new technologies and unlocking the potential of AI across our processes. This contract marks a pivotal step in how we intend to grow and compete over the next decade,鈥� said Philip Harting, CEO, HARTING Technology Group.

麻豆原创 Cloud ERP Private will enable HARTING to transition to a future-proof, scalable and innovation-driven ERP environment. Cloud transformation will allow HARTING to consistently automate and standardize operations and infrastructure, direct IT resources toward value-adding topics and innovation, and continuously benefit from updates and new functionalities. At the same time, RISE with 麻豆原创 opens additional potential in the area of artificial intelligence and data-driven business models, with integrated AI functionalities and new automation options enabling faster, more substantiated data-based decisions. As a long-standing consulting partner, NTT DATA Business Solutions AG will accompany HARTING on its transformation path.

鈥淚ndustrial companies are under real pressure to move faster, operate leaner and integrate AI into their core processes as a present-day advantage. HARTING’s move to 麻豆原创 Cloud ERP Private with RISE with 麻豆原创 reflects exactly the kind of decisive, long-term thinking that separates technology leaders from those who wait, and positions them to scale efficiently and respond to market change with confidence,鈥� said Dirk Haeussermann, Managing Director, 麻豆原创 Germany.

Visit the . Get 麻豆原创 news via  and .

Media Contact:
Mariana Guerrero, +1 786 255 6334, mariana.guerrero@sap.com, ET
麻豆原创 麻豆原创 Room; press@sap.com

Top image courtesy HARTING Technology Group

This document contains forward-looking statements, which are predictions, projections, or other statements about future events. These statements are based on current expectations, forecasts, and assumptions that are subject to risks and uncertainties that could cause actual results and outcomes to materially differ.  Additional information regarding these risks and uncertainties may be found in our filings with the Securities and Exchange Commission, including but not limited to the risk factors section of 麻豆原创鈥檚 2025 Annual Report on Form 20-F.
漏 2026 麻豆原创 SE. All rights reserved.
麻豆原创 and other 麻豆原创 products and services mentioned herein as well as their respective logos are trademarks or registered trademarks of 麻豆原创 SE in Germany and other countries. Please see for additional trademark information and notices.

The hand-crafted stringing on the face of the racket, the customized design, the packaging and distribution, and the systems that enable each touchpoint are all part of a global supply chain that ensures the racket gets from the warehouse into the gear bag of the world No. 5 exactly when he needs it.

That journey鈥攆rom raw materials and global suppliers through manufacturing, warehousing, customs, and last-mile delivery鈥攊s a story. And 麻豆原创 helps power it.

The carefully curated racket, along with Wilson鈥檚 shoes, shirt, cap, and shorts de Minaur chooses to wear as he competes at the highest level, are just a few of the thousands of products Wilson manufactures and delivers to athletes and customers around the world.

Behind each product is an interconnected global operation spanning manufacturing, warehousing, retail, e-commerce, and B2B channels and a digital foundation that helps Wilson keep it all moving seamlessly.

Powering a global sporting goods business

Wilson is a global leader in sports equipment and apparel, with a legacy of more than a century of innovation across tennis, basketball, baseball, golf, and other sports. From developing high-performance equipment for the world鈥檚 best athletes to creating products for players at every level, Wilson combines deep sporting expertise, innovation, and craftsmanship to help athletes perform at their best.

For almost two decades, Wilson has trusted 麻豆原创 to run its global operations, connecting hundreds of employees across finance, sales, logistics, warehousing, and other critical retail functions.

Wilson’s 麻豆原创 landscape spans core enterprise resource planning (ERP), supply chain management, data and analytics, procurement, travel, global trade, integration and enterprise architecture. Its current environment includes 麻豆原创 ERP Central Component (麻豆原创 ECC), 麻豆原创 Analytics Cloud, 麻豆原创 Datasphere, , and 麻豆原创 Business Technology Platform, as well as 麻豆原创 Ariba, 麻豆原创 Concur, and 麻豆原创 LeanIX solutions, among others.

And Wilson’s 麻豆原创 digital transformation is continuing. The company is preparing for a major 麻豆原创 S/4HANA transformation beginning in 2027, which will unlock new capabilities across areas such as extended warehouse management (EWM), transportation, quality, and omnichannel operations. As part of its 麻豆原创 S/4HANA journey, Wilson uses Joule to assist with code conversion marking the beginning of introducing into its business operations

One connected foundation for a connected customer experience

Beyond professional athletes such as de Minaur that choose to utilize Wilson to perform on and off the court, Wilson’s global customers interact with the company in many ways鈥攖hrough retail stores, e-commerce, and B2B channels. Behind those experiences is a complex network of products, inventory, orders, warehouses, and business processes that need to work together.

Built for the pace of sport

The world of professional sports moves quickly. A tennis match can turn in a matter of seconds. Consumer goods organizations like Wilson run an equally dynamic and demanding global operation: designing, manufacturing, moving, and selling products to customers and athletes around the world.

A major event, such as a Grand Slam or a Wilson ambassador winning a tournament, can bring heightened demand for the products athletes use and fans want to buy. This requires Wilson to coordinate inventory, production, warehouses, retailers, and e-commerce across markets and respond quickly as demand changes. 麻豆原创 solutions such as 麻豆原创 Extended Warehouse Management, 麻豆原创 Global Trade Services, 麻豆原创 Concur and 麻豆原创 Ariba provide Wilson with the digital foundation to run smarter, operate faster, and respond to the ever-changing demands running a global retail business

This September in New York fans will see Alex de Minaur compete with his trusted Wilson racket and adorn his new customized Wilson kit. What they won鈥檛 see is the integrated ecosystem and the multifaceted journey behind every single racket, every pair of shoes, every piece of apparel鈥攁nd the 麻豆原创 technology powering it.

Tennis is a game of preparation. When I walk onto the court, every detail matters鈥攆rom how the racket feels in my hand to the kit I’m wearing. Knowing that Wilson and the technology behind their business makes sure everything is ready exactly when I need it, that’s the kind of confidence that lets me focus on competing at my best.

Alex de Minaur

Whether it鈥檚 a game of tennis or the demands of a global business, success depends on having everything working in harmony. With 麻豆原创, Wilson can perform at its best.

And on the court, Alex de Minaur knows he can trust that everything is in place when the moment matters most.

Now, agentic AI could fundamentally change that equation, creating a different model for 麻豆原创 transformation: one built around faster delivery, lower costs, and greater customer self-sufficiency.

That was the central argument put forward during a recent examining what its participants described as 鈥渄eshoring,鈥� which uses AI agents to rethink work that organizations previously distributed between expensive onshore resources and lower-cost offshore teams.

For Stuart Browne, founder and CEO of , an independent 麻豆原创 consultancy that spent the past seven years helping companies chart their journeys from 麻豆原创 ECC to 麻豆原创 S/4HANA, the opportunity starts with questioning assumptions the industry has accumulated over decades.

鈥淭he only way we deliver this in the future is by changing the way we鈥檝e delivered it in the past,鈥� he said. 鈥淪o we鈥檝e got to find new ways of accelerating the migration, and I think AI is probably the best bet for that.鈥�

Why not faster, better, and cheaper?

The traditional technology transformation triangle says organizations might have projects that are faster, better, or cheaper, but generally only two of the three.

Browne challenged that premise by drawing an analogy to NASA鈥檚 鈥渇aster, better, cheaper鈥� approach to missions. He argued that 麻豆原创 transformations should similarly reconsider the assumption that improving one dimension requires sacrificing another.

鈥淲hy can鈥檛 you choose all three of these things?鈥� he asked.

That question becomes increasingly relevant as companies confront the remaining volume of 麻豆原创 S/4HANA migrations while simultaneously dealing with economic pressure, scarce 麻豆原创 skills, and the complexity of global transformation programs.

Ranjeet Panicker, senior vice president and head of Business Transformation at 麻豆原创, framed the challenge around the complete life cycle of an 麻豆原创 project, from initial discovery and analysis through design, build, and ultimately run.

At every stage, customers are asking the same questions: How can the project be completed faster? How can it cost less? How can my organization extract more value from the investment?

From offshoring to 鈥渄别蝉丑辞谤颈苍驳鈥�

For decades, mechanisms for reducing delivery costs have been moving work offshore. The economics were relatively straightforward as certain activities were moved to locations where labor costs are lower.

Browne argued that those savings can obscure another problem. While offshore resources may cost less, distributing work between offshore and onshore teams can increase the overall volume of work through handoffs, communication issues, rework, and coordination.

Agentic AI introduces another possibility. Instead of asking where human labor should be located, organizations ask whether some of that labor needs to be performed manually at all.

鈥淲hy can we not reduce the volume of work and reduce the cost of work?鈥� Browne asked.

That question led to the concept of deshoring鈥攔eplacing portions of location-based delivery with AI agents capable of performing or accelerating specific 麻豆原创 transformation activities.

After analyzing roughly 180 typical activities involved in an 麻豆原创 ECC to 麻豆原创 S/4HANA migration, Browne鈥檚 research concluded that AI could potentially produce about a 60% cost reduction by compressing effort and allowing tasks previously requiring highly experienced people to be performed by less experienced workers augmented by AI.

Some of the most attractive candidates are highly skilled activities that consume significant amounts of time, including writing functional and technical specifications, performing fit-gap analysis, and analyzing custom code.

鈥淚f your run rate is a million a month,鈥� Browne noted, 鈥渆liminating months from a program can dramatically change its economics.鈥�

The 80% solution with humans handling the last mile

AI may be capable of producing what Browne characterizes as an 80% solution within hours. It means experienced people review, challenge, and refine that work rather than spend time manually producing everything from scratch.

鈥淲hat AI produces shouldn鈥檛 be fully trusted without review,鈥� he said. None of this means eliminating experienced 麻豆原创 professionals. Instead, the emerging model redistributes where their expertise is applied.

The objective is not autonomous transformation. It accelerates the majority of the work while concentrating human expertise on the 鈥渇inal mile鈥� that includes judgment, validation, design decisions, and other activities where experience adds the most value.

Custom code could be an early breakthrough

One area where Browne believes AI is already producing significant change is custom code analysis. Early 麻豆原创 S/4HANA migrations often focused on getting existing customizations into the new environment and then determining how to remediate them. Agentic AI creates another option that determines whether the customization needs to exist at all.

According to Browne, AI can now analyze an entire custom code base, reverse engineer functional specifications, and determine whether the same business requirement can instead be met using standard 麻豆原创 functionality.

Rather than migrating large amounts of legacy customization and addressing it later, customers could potentially understand their custom-code landscape and identify opportunities for fit-to-standard before even selecting a systems integrator.

鈥淵ou can actually plan the fit-to-standard of your custom code before your SI’s have even been appointed,鈥� Browne said.

The implication is significant because customers have already paid for standard 麻豆原创 capabilities that may eliminate the need for some custom functionality while creating an environment that is simpler to maintain and upgrade.

麻豆原创 is building agents across the transformation life cycle

Panicker sees similar opportunities emerging across the broader 麻豆原创 implementation life cycle.

The terminology of onshore and offshore itself may eventually become less relevant, he argued, because organizations will increasingly think about transformation work in terms of skills rather than locations. AI-led skills can be delivered through assistants and agents and applied across different stages of a cloud transformation.

麻豆原创 is targeting areas including system analysis, data management, custom code, configuration, testing, rollout, and project management.

Panicker described an assistant as a collection of agents supporting a particular topic area.

A system-analysis capability can examine the overall transition. Data-management capabilities can address data quality. Custom-code agents can support analysis, recommendations, and, in some scenarios, automated remediation. Configuration assistants can evaluate current and target states, while testing agents can help automate test scripts.

According to Panicker, these capabilities are connected with 麻豆原创 Cloud ALM running on 麻豆原创 Business Technology Platform, along with a data and knowledge foundation designed to provide the customer-specific context agents need. 麻豆原创鈥檚 overall objective, he said, is to reduce transformation effort by approximately 35%.

Testing could become the next frontier

Testing can consume substantial amounts of time, particularly in industries with security, compliance, or validation requirements. AI raises a more complicated question: How much of that testing can organizations eventually delegate to agents?

鈥淚f I can get the code to get remediated by an agent,鈥� Panicker said, 鈥渃an I allow an agent to do the testing and accept the testing?鈥�

The answer will determine where humans remain directly involved in transformation workflows. Customers must decide not only if an agent can perform a task, but whether they have enough confidence in the agent鈥檚 knowledge, context, and guardrails to delegate responsibility for the outcome.

Context separates useful agents from hype

麻豆原创 programs generate enormous amounts of organization-specific information around architecture decisions, risk registers, test scripts, requirements, and other artifacts that evolve throughout a transformation.

Browne believes connecting AI to this continuously changing body of knowledge will be essential. 鈥淭he ability to converse not with a static LLM, but to converse with that world as well, I think is what will make good agents even better,鈥� he said.

Organizations may therefore need to rethink not only how they perform 麻豆原创 work, but how they capture information. Programs traditionally run across Excel, Word, PowerPoint, SharePoint, and other repositories may increasingly need AI-native knowledge environments capable of providing agents with usable business and system context.

鈥淭hat鈥檚 where I think this will be won or lost,鈥� Browne said.

AI could also change who holds the knowledge

Perhaps one of the biggest changes involves something less technical: who possesses expertise. 麻豆原创 implementations have traditionally depended heavily on experienced consultants and systems integrators. Customers frequently lack comparable knowledge, creating an imbalance that can make it difficult to challenge recommendations or independently evaluate major design decisions.

Browne believes someone with only six months of 麻豆原创 experience could potentially move up the knowledge curve in weeks in ways that previously might have taken years.

Panicker agreed that access to knowledge is becoming far less constrained.

His own experience at 麻豆原创 was initially concentrated in technical roles. Learning the business context surrounding that expertise often required finding someone willing to explain it. AI potentially allows professionals to move outside those traditional 鈥渟wim lanes.鈥�

Challenging the accepted 麻豆原创 timeline

麻豆原创 customers and consultants have grown accustomed to transformations, migrations, and upgrades taking a certain number of months or years. Those timelines have become assumptions embedded into planning.

Both Browne and Panicker believe those assumptions now deserve to be challenged.

鈥淚t鈥檚 about compressing the time that these tasks make and connecting the decision-makers to be able to make better decisions more quickly,鈥� Browne said.

Panicker similarly argued that organizations should stop accepting conventional project durations without asking what AI capabilities have been introduced to shorten them. 鈥淲hy can鈥檛 we do this sooner?鈥� he asked.

For Browne, the shift is already underway: 鈥淚鈥檓 not suggesting for one moment that we can press a button and deliver a whole program. Complexities around testing, change management, and design decisions remain.鈥� But he believes customers should stop treating agentic transformation as something waiting over the horizon. 鈥淭hat world is here now,鈥� he said.

Panicker鈥檚 message was equally straightforward: don鈥檛 wait on the sidelines: 鈥淟ean in, be curious about the technology. Ultimately, the sooner you can get to the outcome that you鈥檙e driving from a business standpoint, the more value you can bring.

Between technical deployment and actual adoption, there is often a gap. What is needed goes beyond tools鈥攊t requires enablement, communication, and organizational change management that puts people first. Experiences from 麻豆原创 customers show how this can succeed.

Global transformation, local anchoring as a guiding principle

Dulaan Punsag-Odefey cites a number that immediately makes the challenge tangible: 265. That is how many key users serve as change ambassadors at Hapag-Lloyd, distributed across six regions worldwide. The shipping company is one of the five largest in the world and is in the midst of an 麻豆原创 S/4HANA Finance transformation. The “Fast Forward” program affects 4,000 麻豆原创 users in more than 140 countries.

Punsag-Odefey, organizational change management (OCM) lead at Hapag-Lloyd, explains: “Change management is anchored in our program as a strategic enabler. Not as an add-on, but as a core element.”

In practice, this means the 265 ambassadors translate global standards into local language and local practice. Controllers are expected to evolve into business partners who no longer just produce Excel spreadsheets but deliver decision-ready recommendations for sales and operations. The message to the workforce is “It will be different, but better.”

How a federal agency demonstrates effective change management

That transformation can succeed without following the textbook is demonstrated by the Bundesanstalt f眉r Post und Telekommunikation (BAnst PT), Germany’s Federal Agency for Post and Telecommunications. The agency implemented 麻豆原创 S/4HANA in just one year: greenfield, public cloud, 1,000 affected users, go-live on January 1, 2026. In parallel, the organization moved to a new administration building with a new-work concept.

Simone Kunze, specialist in the 麻豆原创 Service Center at BAnst PT, knows the phrases that come up in every organization: “Is there an official directive for this?” or “Standard won’t work for us.” What helped was honest communication and direct moderation within business units instead of token feedback sessions.

A fit-to-standard approach replaced legacy custom solutions. Key users were developed from project experts who had already built depth through workshops, user stories, and test cases. The investment in support paid off: after go-live, dozens of thank you e-mails came in regarding the new 麻豆原创 travel expense management and Fiori apps, and survey response rates exceeded 70%.

Thilo Menges from the Medical University of Lusatia (MuL) takes this one step further. His project has a unique starting point: with 3.6 billion euros in funding, an entirely new organization is being built from scratch, including 麻豆原创 technologies. Menges makes a point that many organizations do not state this clearly: “For me, change management is an investment protection measure. This is an organizational project, and people need support in change processes.”

Change management in his project accounts for 4.3% of the total budget鈥攖he largest single line item in the 麻豆原创 contract.

麻豆原创鈥檚 change management framework with its six dimensions, which MuL follows, is integrated into the 麻豆原创 Activate methodology. Particularly important are early assessments, target-group-specific communication, and the identification of trusted multipliers rather than a blanket approach.

What was also highlighted: learning does not end at go-live. Tools like WalkMe enable context-sensitive support in the flow of work, especially for infrequent processes. Enabling the organization to independently maintain and evolve these systems is critical for sustained success.

The organizations mentioned above are supported by change management consultants from 麻豆原创. More information is available .

From shadow AI to structured integration at KIT

While BAnst PT and Hapag-Lloyd are primarily transforming 麻豆原创 system landscapes, the Karlsruhe Institute of Technology (KIT) faces a different question: how do you get 25,000 students and 10,000 employees to use AI responsibly, instead of each person experimenting on their own in the shadows?

In 18 months, KIT made the journey from uncontrolled AI usage to an AI toolbox with governance rules. Rather than issuing bans, KIT focuses on enablement.

Andreas Sexauer from the Center for Technology-Enhanced Learning at KIT describes the approach as follows: a mandatory qualification module covers foundational knowledge and legal aspects before students and faculty gain access to the AI toolbox. In parallel, use case workshops run across departments, from leadership teams to the legal department. After the teaching rollout in April 2025, 31 didactic chatbots were created in the first seven days. Faculty configure them directly in the learning management system for their respective courses.

KIT also takes a pragmatic approach to costs: after initially providing free access, a budget cap per person per month was introduced.

What research confirms

Whether shipping company, federal agency, or university, all customers report similar patterns. Prof. Dr. Renate Osterchrist from the Munich University of Applied Sciences provides the scientific foundation: she analyzed 119 studies on the effectiveness of change interventions, examining six intervention fields: communication, support, involvement, reinforcement, social influence, and coercion. Key effectiveness factors in change include:

• Dialogue formats are more effective than one-way communication.
• Coaching for managers improves not only their leadership capability but also measurably enhances implementation competence. Coaching and peer exchange are also very beneficial for employees.
• The dimension of coercion had been under-researched until now: clarity in messaging about what behavior is expected proves helpful. Manipulation and political maneuvering, on the other hand, reduce commitment.
• The frequently cited claim that 70% of all change projects fail is not supported by current data.
• The statement “Honestly, I have never experienced a change where there was too much communication” further underscores the important role of communication.

When AI agents enter the picture, change becomes even more critical

What happens when not only new systems are introduced but AI agents take over parts of the work? This is precisely the question that arose when Joule Studio 2.0 was demonstrated live at the forum. With this solution, 麻豆原创 customers can create AI agents that access their business context: 麻豆原创 Knowledge Graph, process models, and domain knowledge. The agents are code-based and transparent. Developers describe the desired outcome in natural language; Joule Studio can generate the specification and executable code. Both no-code and pro-code approaches are possible.

The discussions that followed amongst 麻豆原创 customers and partners made clear that the change management described above will be essential here. When agents take over tasks, roles change, responsibilities shift, and the way humans and machines collaborate is transformed.

A full documentation of the 麻豆原创 Learning and Adoption Forum 2026, including videos, slides, and a chatbot, is .

Thomas Jenewein is business development manager for AI, Transformation, & Adoption Services at 麻豆原创.

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Salling Group, northern Europe鈥檚 largest retailer, shares how a modern 麻豆原创 landscape is helping support more than 2,100 stores across six countries

Learn how 麻豆原创 S/4HANA Cloud, RISE with 麻豆原创, and a strong supply chain foundation are helping the company improve efficiency, support employees, and better serve customers. Read the article.

The company鈥檚 history goes back more than 100 years, and what began as a small textile shop in Aarhus, Denmark, is now an international retailer with 鈧�12 billion in revenue.

麻豆原创 has supported Salling Group for over 20 years and is central to its operations, said Alan Jensen, CIO and executive vice president at Salling Group. Recently, the company has modernized its ERP system to 麻豆原创 S/4HANA Cloud via RISE with 麻豆原创.

With this cloud-based infrastructure in place, the retailer is ready to begin its AI transformation.

Improving everyday life

Salling Group鈥檚 reason for introducing AI is threefold: improve customer experience, simplify for employees, and boost operational efficiency. 鈥淲e want to make everyday life better for our customers by having the right product for the right price every time they need it,鈥� Jensen said. 鈥淲e also want to make every day better for our employees, so the tools and systems they work with are intuitive and easy to use.鈥� This aligns with the company鈥檚 purpose to improve everyday life for customers, colleagues, and the communities it is a part of.

The company views AI as a key enabler, focusing on how to turn AI into real business value for customers, employees, and the company overall. One such area where AI will have real impact on the retailer is logistics, Jensen said. Currently, Salling Group uses in its 29 distribution centers. The application helps manage high volumes of goods and run sustainable, risk-resilient operations via digitalized warehouse processes in the cloud. For Salling Group, this means on-time delivery to stores and efficient supply chain operations.

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What鈥檚 next

Salling Group is using 麻豆原创 solutions and AI to modernize its retail operations end-to-end, with a clear emphasis on customer experience, employee productivity, and supply chain excellence鈥攚hile ensuring new technologies deliver tangible business outcomes.

When it comes to 麻豆原创, Jensen is looking forward to seeing how the Autonomous Enterprise will further Salling Group鈥檚 success with AI.

鈥淭he Autonomous Enterprise looks very exciting,鈥� Jensen said. 鈥淭here is definitely a lot in how we can improve the way we run our business every day, so we need to be curious and see how we can use it.鈥�

鈥淲e started by fixing the basics,鈥� said Siani, Transformation and Technology director at Ipiranga, one of Brazil鈥檚 largest fuel distributors.

Ipiranga operates almost 6,000 service stations nationwide. Headquartered in Rio de Janeiro, the company has more than 6,200 B2B customers and 1,500 convenience stores. Ipiranga generates $120.7 billion in revenue, yet despite its size and market leadership, the company faced a critical problem: repeated project failures.

Working on the root cause

鈥淏efore we could start investing in new technology, we needed to take a good look at why some of our initiatives were not generating the expected value for the business,鈥� Siani said, speaking at the TAC Insights conference for in Toulouse. 鈥淲e needed a rigorous RCA.鈥�

RCA, or root cause analysis, is a structured approach to problem-solving that focuses on identifying the underlying causes of issues rather than just addressing surface-level symptoms.

鈥淚nstead of making new investments, we decided to dig deeper and identify the causes,鈥� she explained. 鈥淲hen we examined the company鈥檚 history, RCA confirmed that the high level of customization was limiting our ability to deliver at the required speed. Our inability to adopt the best technologies and functional best practices was directly impacting the company鈥檚 ability to evolve and drive business growth.鈥�

Speaking the language

From the outset, the Technology team recognized that the case for the ERP transformation rested on demonstrating how inconsistent processes and the lack of standardized best practices hindered the organization’s ability to respond quickly and remain competitive in the market.

鈥淲hen we went to the Board to secure the budget for the digital transformation, we didn鈥檛 start by talking about technology,鈥� Sian sharedi. 鈥淲e started by discussing what the business needed to achieve its strategic objectives faster. Then, we listed the obstacles preventing that progress along with the technology capabilities required to remove those barriers.鈥�

By translating technical challenges and opportunities into business language, Siani helped Ipiranga鈥檚 leadership understand that innovation without a strong foundation would not take the business to the level of efficiency required.

鈥淏y identifying these root causes, we were able to avoid a common trap,鈥� she explained. 鈥淚nstead of investing in new technology without fixing the foundation, we shifted our strategy. We refocused on聽 tools to process integration, governance, and operational discipline.鈥�

Getting approval for a big investment

Ipiranga partnered with 麻豆原创 to assess critical processes across operations, finance, and commercial operations.

“麻豆原创 brought in business experts to pinpoint how a heavily customized ERP system was slowing decision-making and limiting visibility and innovation,” Siani said. Rather than focusing on 麻豆原创 functionalities, they asked fundamental business questions: What does your financial process look like? How does your order-to-cash process work?”

Armed with these insights and a clear understanding of what was slowing decision-making, Siani returned to the board with a clear message: “Fix the foundation, or transformation will fail.”

As a result, she got approval to implement a new ERP system, driven by business value and ROI. What ensued was a massive integration effort, with a targeted go-live scheduled for December 31, 2026.

With support from Accenture and 麻豆原创, Ipiranga adopted a clean core strategy, ensuring minimal customization and long-term scalability. Overall, 104 legacy systems were analyzed, 64 systems will be integrated and 40 decommissioned, and over 750 interfaces are being built. Of course, all developments had to pass strict governance gates to guarantee the clean core.

People driving change

Technology may enable transformation, but people make it successful. Over 350 professionals from a variety of business and technical teams are involved in the ongoing project. Crucially, leadership played a direct role. With executive sponsorship and transparent communication, resistance to change has been minimal.

鈥淲e were careful not to impose change, but to explain the impacts clearly and discuss them with a multidisciplinary team,鈥� said the IT expert, who is also a rowing champion. 鈥淲e made sure to prepare teams early and embed change management at every phase.鈥�

The team prioritized initiatives with the highest return on investment (ROI) and paused non-essential projects. They also selected world-class partners鈥攊ncluding Accenture as the implementation partner and Amazon Web Services (AWS) as the hyperscaler鈥攖o help ensure a high-quality, successful transformation.

The company鈥檚 transformation is now in the middle of a critical milestone (SIT1). The expected ROI is over $40 million, but more importantly, the company has built something far more valuable than a new system.

鈥淲e will have a solid operational foundation, integrated, scalable ,and efficient processes, and a culture that understands how transformation goes beyond technology. Technology is simply the path,鈥� Siani said.

Ipiranga鈥檚 journey offers a powerful reminder that digital transformation is not about tools; it鈥檚 about assertive fundamentals. RCA can reveal issues technology alone cannot fix. It demonstrates that preparation is as important as execution, and that clean core strategies reduce long-term complexity.

“In effect, the path to successful transformation doesn鈥檛 start with innovation. It starts with clarity, discipline, clear goals that together determine the correct technology,鈥� Siani concluded.

Managing logistics operations has become increasingly challenging in recent years. The coronavirus pandemic and its repercussions caused unprecedented disruption across global supply chains, and today, hostilities in the Strait of Hormuz are severely hindering shipping traffic.

In situations like these, the only option many companies have to protect their manufacturing and delivery timelines from delays and uncertainties is to carry larger inventories. This inevitably leads to higher costs.

Now, a combination of container tracking technology and real-time data is revolutionizing supply chain visibility, enabling businesses to keep their inventories at efficient levels. Hapag-Lloyd, the world’s fifth-largest shipping company, provides live position data for its containers. 麻豆原创 uses this information in its ERP systems and 麻豆原创 Business Network Global Track and Trace cloud solution, connecting it to the shipment and material data that is stored there. Which means that, as well as being an 麻豆原创 customer, Hapag-Lloyd is an 麻豆原创 supplier and partner, too.

Karsten Schmidt, director and product owner of the Live Position and Track & Trace tools at Hapag-Lloyd, and Sven York Pohl, chief expert for Digital Adoption at 麻豆原创 SE, discuss how the collaboration between the companies began, how it is benefiting users already, and what opportunities lie ahead.

Q: Tracking technology has advanced rapidly in recent years. What sparked the wave of innovation we鈥檝e seen here?

Pohl: During the coronavirus pandemic, we experienced serious delays in the movement of goods and materials. And we realized that logistics processes need to be much more transparent.

Schmidt: Until recently, we could only track certain milestone events in sea shipping, such as a container arriving at a port or being loaded onto a ship. We knew when a container had been loaded onto a ship or when it left the Port of Hamburg, but if it failed to arrive in Munich as planned, we had no way of knowing what had happened to it.

Q: So how do you track containers today?

Schmidt: After the pandemic, we decided to equip all our dry containers with IoT tracking devices that continuously transmit location data. By mid-2024, we had fitted these devices to 90% of our container fleet. Since then, we have been able to track more than 2 million containers worldwide and provide position data every 15 minutes for shipments on land鈥攁nd every six hours for shipments by sea. This means that our customers can check the precise location of 鈥渢heir鈥� containers online in real time.

Q: How did the collaboration between Hapag-Lloyd and 麻豆原创 begin?

Pohl: I was involved in an 麻豆原创 transformation project at Hapag-Lloyd, which meant I had frequent meetings with Karsten. We realized early on that position data had immense potential, both for Hapag-Lloyd as a shipping company and for its customers. If you know exactly when an intermediate product will arrive, or how many days late it will be, you can plan your downstream production steps with pinpoint precision. And this obviously works best if position data is visible not only on a separate website, but also in the applications you use to manage your production and other business processes. So Karsten and I began discussing how we could feed position data into 麻豆原创 ERP systems.

Q: Which 麻豆原创 applications use this data?

Pohl: The 麻豆原创 Business Network Global Track and Trace cloud solution offers companies transparent shipment information in real time along the entire supply chain. And it enables this data to be embedded natively in back-end systems. Which means, for example, that you can integrate automated alerts directly into 麻豆原创 S/4HANA that show where a container is currently located. The data can also be leveraged in 麻豆原创鈥檚 cloud-based supply chain collaboration platform, 麻豆原创 Business Network for Logistics, to seamlessly connect shippers with logistics services providers and carriers. And, aside from ensuring visibility, real-time data such as that provided by Hapag-Lloyd maximizes supply chain security and drives sustainability by enabling businesses to track materials from their source to the finished product.

Q: Who benefits most from Hapag-Lloyd’s tracking data?

Schmidt: Logistics managers, definitely. Because they need precise information about where their containers are located and when they will arrive. The tracking data also provides insights into how sustainable a transportation chain is. Warehouse planners benefit too, because they can keep inventory levels as low as possible, without them dropping too low. And as well as enabling carriers to plan their routes with maximum efficiency, tracking data can also help streamline and optimize payment processes.

Q: Would you say that the current conflict in the Middle East has highlighted the value鈥攁nd necessity鈥攐f using tracking technology to plan shipping routes?

Schmidt: Absolutely. A huge number of containers have been transported from the Persian Gulf across Saudi Arabia to the Red Sea port of Jeddah to be shipped on from there. Our container tracking solution keeps me constantly updated on the land route I have chosen and on where my container is currently located.

Q: What happens if the container is held up somewhere? How does the system help?

Schmidt: That鈥檚 what we鈥檙e working on right now. Usually, when customers want to know where their container is, they call our customer service number. But with 15,000 containers held up in the Persian Gulf, we were unable to handle the sheer volume of inquiries we received by phone. So we gave all our customers access to our live positioning service, even those who had not booked it. The solution we implemented to deal with this exceptional situation showed us the potential that was there going forward to simplify our customers鈥� processes鈥攁nd our own.

Pohl: Looking ahead, 麻豆原创 users will be able to ask their software what options they have when shipments get held up, and what alternative modes of transportation are available to them.

Schmidt: If, for example, a ship is delayed and misses its scheduled rail connection, the system will provide a predictive service, telling the user whether onward transportation by truck is possible and how much longer the journey will then take.

Pohl: We will also use Joule, the flagship AI brand that is built into 麻豆原创鈥檚 cloud portfolio, for this service, so that users will be able to ask AI to suggest specific actions.

Schmidt: Obviously, when goods are transported over long distances, and especially by sea, you can never rule out delays entirely. But what we can do is remove that feeling of helplessness and of having no room to maneuver when events occur that are out of my control.

Top image via Hapag-Lloyd

Those investments are critical. But they weren鈥檛 the finish line. They were the foundation. And today, they鈥檙e paying off in new ways as organizations adopt AI to drive measurable business outcomes.

But there鈥檚 another part of that foundation which is becoming just as important: data. The organizations best positioned to compound their value from AI are those that have invested in data foundations that give AI the trusted business context it needs to reason, recommend, and act.

Now, in conversations with customers across the Americas and around the world, I鈥檓 seeing a new pattern emerge. The discussion is shifting from where AI can be applied to what happens when intelligence becomes embedded into the core of how the business operates.

While every transformation is different, three common shifts keep coming up.

1. From AI use cases to intelligent business processes

The first wave of AI adoption focused on proving value. Organizations identified high-impact use cases, delivered measurable results, and built confidence that AI could make a difference.

That work isn鈥檛 finished. But increasingly, customers are asking how intelligence can become part of the business processes employees use every day. We鈥檙e already beginning to see what this looks like in practice.

For example, HR Path Brazil, a Brazilian company specializing in recruiting and managing talent for international firms, is using Joule embedded in 麻豆原创 SuccessFactors HCM to automate routine HR interactions. It is helping employees find the information they need faster while allowing HR teams to focus on more strategic work. The company has reported a seven percent reduction in standard HR support cases and two hours of聽HR support workload eliminated each week, which quickly adds up.聽It鈥檚 one example of how embedded and connected AI is becoming part of how work gets done.

2. From measuring AI use to measuring the business outcomes it creates

One of the biggest changes I鈥檓 seeing is how organizations define success. ROI is becoming a given and that is reflected in the data, especially in Oxford Economics research out just this week. It showed that organizations investing in AI expect to see an average return of 21% this year but increasing to 38% in two years. And as agentic AI continues scaling, it is projected to deliver $17.6 million in returns, more than quadrupling last year鈥檚 estimates (US$4.3 million).

This is allowing organizations to focus more on business outcomes from their AI. They are asking questions like can we shorten cycle times? Can we improve decision-making? Can we free employees to spend more time creating value? Can we become more resilient and responsive as a business?

This is an important shift because it changes the conversation from implementing technology to improving how the business performs.

3. From systems of record to the new operating system for the enterprise

The third shift is the one I believe will have the greatest long-term impact. For decades, enterprise software primarily captured transactions, standardized processes, and automated routine work. Now it鈥檚 beginning to help organizations anticipate change, recommend actions, coordinate work across functions, and increasingly execute routine decisions with human oversight.

That鈥檚 why I believe the Autonomous Enterprise represents more than the next phase of automation. It represents a new operating model for business.

Instead of people spending time connecting information across finance, supply chain, procurement, HR, and customer operations before deciding what to do next, intelligent systems can increasingly provide context, surface recommendations, orchestrate work, and help teams execute.

People remain firmly in control. But they鈥檙e supported by enterprise software that is becoming an active participant in how the business operates and executes, not simply a system that records what already happened.

Where we go from here

The organizations creating the greatest long-term advantage won鈥檛 just be the ones deploying the largest number of AI use cases. They鈥檒l be the ones that use those early successes to rethink how work gets done across the enterprise.

The journey to the Autonomous Enterprise won鈥檛 happen overnight, and it won鈥檛 replace the need for strong leadership, governance, or talented people. If anything, those become even more important.

We鈥檒l likely look back on today鈥檚 AI projects much the same way we now look back on the early days of cloud transformation; not as the destination, but as the foundation for a fundamentally new way of operating and innovating continuously.

The true winners from this shift will be the ones who continuously become more intelligent, more adaptive, and ultimately more autonomous.

Jan Gilg is a member of the Extended Board of 麻豆原创 SE and global president of Customer Success & Americas.

That was the takeaway from a between 麻豆原创 CFO Dominik Asam and 麻豆原创 Fioneer CEO Matthias Tomann. Their conversation touched on topics like the future of , the role of AI, and the growing importance of integrated enterprise platforms.

For decades, banks and insurers have built operating models around regulatory fragmentation, country-specific requirements, layered systems, and continuous workaround solutions. As a result, the industry is running on patchwork architecture that is expensive to maintain, slow to change, and fundamentally misaligned with how AI works.

Partnership built for financial services innovation

Since joining forces in 2021, 麻豆原创 and 麻豆原创 Fioneer have significantly expanded their joint capabilities for the financial services sector. As Tomann highlighted in the conversation, the partnership has already delivered substantial momentum for 麻豆原创 Fioneer:

• R&D investment increased by 120%
• Annual software sales more than doubled
• Major customers successfully transitioned to 麻豆原创 Cloud ERP
• The platform evolved into a richer, more scalable, and highly capable ecosystem

Together, the companies are combining 麻豆原创鈥檚 trusted cloud and data infrastructure with 麻豆原创 Fioneer鈥檚 deep financial services expertise to help institutions simplify operations, modernize core systems, and prepare for the AI-driven future.聽

Executives from both companies will be exploring these critical topics further at their annual which is now open for registration.

AI is not the starting point, data integration is

Everyone wants AI, but AI can only create value from integrated data, real-time access, and standardized processes. But most financial institutions still operate on the opposite: fragmented foundations. That reality will define the winners over the next five years.

The organizations that succeed will not be the ones experimenting with the most models. They will be the ones that establish unified, trusted, real-time enterprise data with strong governance. That is the real competitive advantage.

But even that is only part of the story. The next phase is not just about using AI to analyze better; it is about AI executing work.

We are now seeing a fundamental shift: from systems that store and report information to systems that act on that information in real time, orchestrating end-to-end processes across the business. This marks the transition to the Autonomous Enterprise, 麻豆原创鈥檚 vision for the future of business where AI does not just support decisions but increasingly drives execution, within clearly defined guardrails.

Financial services can no longer afford 鈥減atchwork architecture鈥�

This shift makes one thing clear: The traditional approach to building IT landscapes is no longer viable.

For years, many financial institutions solved problems incrementally鈥攁nother point solution, another integration layer, another workaround. But eventually every workaround becomes technical debt and integration is the single largest IT cost category.

Tomann made clear during the conversation that the emphasis must be on simplification rather than adding more complexity.

What 麻豆原创 and 麻豆原创 Fioneer are driving is not another modernization cycle. It is a structural shift toward comprehensive, integrated platforms and AI driven processes that replace fragmentation, not sit on top of it.

The result is a scalable financial services platform where core banking, lending, reporting, insurance, and analytics operate within an integrated architecture instead of disconnected silos.

Real-time finance is becoming a strategic requirement

Real-time capability is becoming foundational to competitiveness鈥攚hether it鈥檚 risk management, regulatory reporting, customer experience, fraud prevention, treasury operations, or AI-driven decision making.

Institutions that can act on integrated data instantly will have a major advantage over those still moving information between disconnected systems overnight. With integrated data and AI embedded in core processes, finance is moving toward continuous financial intelligence:

• Forecasting becomes dynamic and always up to date
• Risk is detected and assessed in real time
• Closing processes become increasingly automated
• Decisions are guided by AI based on live business context

Increasingly, AI assistants and agents take over execution of finance processes, from planning and risk management to invoicing and financial close, under strict governance. The role of finance shifts from reporting on the business to steering the business in real time.

AI will reward those who simplify

One of the most striking statements from Asam during the discussion is that 麻豆原创 is already seeing 10x performance improvements from AI-driven process improvements. But it also highlights something many organizations still underestimate: just how much AI rewards those who standardize.

The more fragmented the processes and data structures are, the harder it becomes to operationalize AI at scale. In contrast, organizations with standardized platforms, harmonized data, and integrated workflows will accelerate much faster.

That is why modernization conversations today are no longer simply 鈥淚T projects.鈥� They are business strategy discussions.

Future of financial services will be built on trust, scale, and intelligence

Financial services organizations are operating in an increasingly complex geopolitical and regulatory environment. Infrastructure decisions are no longer just about performance and cost, they are about compliance, security, operational resilience, and national requirements.

This is why scalable, enterprise-grade cloud platforms are becoming so critical.

The institutions that thrive in the next era of financial services will be the ones that can combine trusted data, integrated operations, AI-enabled processes, scalable infrastructure, and regulatory resilience into a single operating model.

The future of financial services will not be defined by isolated AI experiments. It will be defined by who can build the most intelligent, connected, and adaptable enterprise foundation for what comes next.

.

Kris Kowal, Banking Industry Leader at 麻豆原创.
Falk Rieker, Financial Services Industry Leader at 麻豆原创.

Anyone who is looking for a prime example of how migration to the cloud can do far more than just simplification and standardization should take a closer look at Swarovski. The legendary manufacturer of precision-cut crystals, jewelry, and watches鈥攚ith its origins in Wattens, in the Austrian region of Tyrol鈥攈as transformed its IT landscape from a cost factor into a strategic tool for a digital future.

The transformation was guided by Lea Sonderegger, serving in a dual role as CDO and CIO at Swarovski, with such great success that she was awarded the special 鈥淐loud Excellence鈥� prize in the large enterprise category at the CIO of the Year ceremony held by CIO Magazine last October.

The judging panel found her brownfield approach to be especially praiseworthy: Swarovski employees use but continue to use the familiar processes and databases. A complete redesign of these processes in parallel to the migration would have been too risky and cost-intensive. It would have also resulted in a much longer project duration, Sonderegger is convinced.

25,000 tests with 600 participants

The brownfield implementation was carefully executed. Preparations took two years and involved more than 600 participants performing around 25,000 tests. Two dress rehearsals with strict governance ensured that every function and every data point was ready for the migration.

Sonderegger and her colleagues reserved a 66-hour conversion window for the go-live on April 20, 2026. During this period, all global IT processes at Swarovski were paused. During the subsequent sensitive hypercare phase, 24×7 support ensured that any issues that arose could be dealt with quickly. Thanks to these measures, the transition was seamless. After the conversion window closed, all processes resumed without problems.聽

Simplification and standardization ensure consistent data

Despite the large effort involved, this migration was merely the first step. While the switch to 麻豆原创 Cloud ERP Private created the technical foundation, it鈥檚 the subsequent investments that deliver additional added value. These investments concentrate on the incremental reduction of complexity through consolidation of fragmented solutions, the reassessment of user-specific code, and the harmonization of data鈥攁ll with the overall goal of creating a more coherent, easier-to-handle ERP landscape.

To achieve this, Sonderegger and her team are replacing user-specific applications with 麻豆原创 standard solutions step by step and only leaving custom developments in place where they offer clear advantages. 鈥淭he combination of simplification and a return-to-standard solutions improves data consistency, provides for robust, reliable processes, and, ultimately, makes our entire organization more agile,鈥� Sonderegger says.

Cloud technology is not an end in itself

By integrating key functions such as finance, supply chain management, retail, and e-commerce鈥攁nd enabling their combined use in the cloud鈥斅槎乖� Cloud ERP Private provides for reliable processes and consistent data quality all while enabling customer experiences on a wide variety of front-end solutions on this side of the ERP system.

麻豆原创 Cloud ERP Private manages a diverse product range at Swarovski across different regions and price points and integrates with the planning results provided by other 麻豆原创 and non-麻豆原创 systems.

鈥淚n all of these activities, cloud technology is never an end in itself, but rather a lever for improving efficiency, resilience, and innovative capabilities,鈥� Sonderegger says. This determination is especially important to her.

It鈥檚 not an IT project, it鈥檚 a business transformation

Ultimately, Sonderegger and her team succeeded in executing the project on time and on budget because its scope was clearly defined, and strict discipline in change management prevented mission creep. In addition, the company benefited from the experience of its implementation partner, 麻豆原创 Consulting, and its unrestricted access to 麻豆原创 expertise.

The example of Swarovski proves that even an essential, unavoidable migration can and should do much more than just avoid risks and cut maintenance costs. The implementation of 麻豆原创 Cloud ERP Private was imperative here, because 麻豆原创 ERP Central Component (麻豆原创 ECC) had reached the end of its lifecycle.

And the implementation is showing the luxury goods manufacturer the way to the future because everyone involved in the process didn鈥檛 just consider it to be an IT project but, above all, a business transformation from day one. One that involved hundreds of experts from different fields and that enjoyed full management support from the beginning.

AI-driven demand forecasts optimize warehouse stocks

Artificial intelligence is also playing a key role in this implementation, with 麻豆原创 Cloud ERP Private as the operational backbone of an AI ecosystem that can deliver reliable, real-time data and robust, standardized transaction processes.

Swarovski doesn鈥檛 use artificial intelligence as a standalone technology, but instead as an integrated capability that complements business processes across all functions. The company is already using AI for demand forecasting, for example, and then uses the results to optimize warehouse stock levels across regions, with the aim of improving the customer experience.

And the AI agent factory initiative enables the development of AI agents that link 麻豆原创 Cloud ERP Private data with data from non-麻豆原创 systems, always with the objective of 鈥渁utomating repetitive tasks, supporting decision-making, and boosting productivity along the entire value chain,鈥� Sonderegger emphasizes.

Top image courtesy of Swarovski

At the center of that effort sits a deceptively complex challenge: understanding, in real time, which revenue and cost factors are driving or eroding gross margin across a highly diversified business. For years, answering that question meant manual reporting, delayed insights, and finance teams spending valuable time on data gathering rather than analysis.

That鈥檚 now changing, thanks to a co-innovation initiative developed together with 麻豆原创 and Numen, a global 麻豆原创 partner specializing in digital transformation and enterprise software implementation.

From manual reporting to proactive decision intelligence

The project鈥檚 goal was to replace a labor-intensive gross margin analysis process with a generative AI application embedded directly into Natura &Co’s financial workflows. Built on 麻豆原创 Business AI Platform, 麻豆原创’s unified foundation integrating business technology, data, and AI capabilities, the application connects directly to data in 麻豆原创 S/4HANA to provide finance teams with automated insights and narrative recommendations in real time, without the need for manual data pulls or offline reporting.

The application enables users to explore revenue, cost, and margin drivers interactively, identifying at a glance which elements are protecting or eroding margin performance across markets and product lines. Crucially, human oversight remains central to the design: the AI application generates insights, while finance professionals retain full control over interpretation and decisions.

鈥淭he implementation of gross margin analysis using AI in 麻豆原创 S/4HANA marked an inflection point in the analytical capability of our finance area,” said Rog茅rio Dias Garcia, tech manager, ERP Latam, Natura &Co. “We overcame delays and raised the standard of insights by integrating margin analysis from 麻豆原创 S/4HANA with a large language model connected via the 麻豆原创 AI Core layer. This architecture allowed us to provide, in an agile, secure, and completely anonymous manner, a stratified and precise view of gross margin offenders and protectors鈥攄iscriminating exactly which revenue or cost elements were driving market performance.鈥�

A collaborative architecture for scalable AI adoption

Natura &Co鈥檚 application derived from a prototype 麻豆原创 partner Numen created in early 2024 at 麻豆原创鈥檚 global on business AI, leveraging the generative AI capabilities of聽麻豆原创 Business AI Platform. The solution was designed and developed through close collaboration between Natura &Co, Numen, and 麻豆原创. From the outset, the approach was to align AI adoption with concrete business priorities, ensuring the application would be scalable and production-ready rather than a standalone prototype.

Numen brought deep 麻豆原创 implementation expertise to the project, combining knowledge of 麻豆原创 S/4HANA architecture with hands-on experience in building solutions on 麻豆原创 Business AI Platform. The technology stack鈥斅槎乖� S/4HANA, 麻豆原创 AI Core, 麻豆原创 Fiori, and 麻豆原创 Business Technology Platform鈥攑rovided the secure, integrated foundation needed to connect financial data with generative AI capabilities in an enterprise context.

鈥溌槎乖� enabled the transformation by providing the technological foundation and expert support,鈥� said Carlos Aravechia, head of Data Design & Intelligence at Numen.

The success of the project has validated a broader conviction at Natura &Co: that generative AI, embedded directly in ERP workflows, can fundamentally reposition finance from a transactional function to a strategic business partner.

A blueprint for other businesses

The Natura &Co project demonstrates a pattern that other organizations can replicate, particularly those running 麻豆原创 S/4HANA. The combination of structured ERP data with the contextual reasoning capabilities of large language models creates a foundation for decision intelligence that goes well beyond traditional business intelligence tools.

The project was built within a six-month co-innovation sprint and went live in August 2025. It is currently in use across Natura &Co鈥檚 Equador operations.

Looking ahead, Natura &Co is already planning the next phase: integrating Joule Agents to further automate the extraction of standard analytical content and deepen the AI-driven optimization of financial processes.

鈥淭he success of this initiative validates the transformative potential of embedded AI within our ERP,鈥� Dias Garcia noted. 鈥淲e are now ready to move forward鈥攄eepening these insights and integrating the capability of Joule Agents to maximize the extraction of standard content and further optimize our business decisions.鈥�

For 麻豆原创 customers evaluating how to move from AI experimentation to AI in production, the Natura &Co project offers a concrete, replicable model: start with a high-value, well-defined business process, embed AI directly into existing workflows, and build in human oversight from the start.

WALLDORF 鈥� (NYSE: 麻豆原创) and IBM today announced that global enterprises JYSK, GBM, DIFARE Group and Plastilene Group have selected 麻豆原创 Cloud ERP Private solutions on to modernize enterprise resource planning (ERP) workloads in secure, reliable and scalable cloud environments.

Spanning retail, technology services, pharmaceutical and manufacturing, these clients are among the tens of thousands of businesses that run 麻豆原创 landscapes on IBM Power servers.

According to a from the IBM Institute for Business Value (IBV), modernizing ERP workloads is essential for driving AI adoption and business growth, with companies embedding AI into ERP systems achieving up to 27% higher ROI. Leveraging 麻豆原创 Cloud ERP Private on IBM technology can support customers as they scale on-premises ERP environments to the cloud and accelerate AI-enabled business workflows.

The platform delivers a flexible hybrid cloud environment, which can help organizations:

• Reduce the total cost of ownership (TCO) of cloud ERP operations, supported by the ability to scale granularly to match business demand and leverage IBM鈥檚 global cloud infrastructure, designed to be highly resilient.
• Migrate to 麻豆原创 Cloud ERP Private and to the 麻豆原创 Business Warehouse (麻豆原创 BW) application as part of the 麻豆原创 Business Data Cloud (麻豆原创 BDC) solution, securely, quickly and with minimal disruption, including support for hybrid cloud and multicloud deployments.
• Mitigate operational and security risk, through IBM Power鈥檚 enterprise-grade resilience and integrated IBM Cloud security and compliance protection.

Modernizing ERP Workloads in More Secure, Scalable Cloud Infrastructure Across Industries

Known for its high security, scalability and reliability, IBM Power servers are ranked as one of the top servers for uptime and availability among 麻豆原创-certified infrastructure, engineered for fewer disruptions and faster migration, supported by the highly resilient and secured IBM Cloud platform. These clients are rapidly migrating on-premises 麻豆原创 software systems to the cloud, modernizing business processes and becoming more agile:

• JYSK, the international home furnishing retailer based in Denmark, is advancing its global modernization journey with IBM and 麻豆原创. With more than 3,600 stores in 50 countries, the retailer needs its 麻豆原创 software landscape to be more secure, scalable and future-ready to enable it to keep up with the demands of its global business. JYSK has a long history with IBM technologies and continues to work with IBM to advance in their RISE with 麻豆原创 journey.
• DIFARE Group, a leading pharmaceutical manufacturing company based in Ecuador, required a robust, secure and scalable infrastructure to modernize its 麻豆原创 software landscape and support critical business operations. As long-term users of IBM Power servers, DIFARE Group continues to place its confidence in IBM technology and has expanded into RISE with 麻豆原创 on IBM Power Virtual Server to help move to the cloud faster and more cost effectively.
• Plastilene Group, an innovator, developer and manufacturer of flexible film solutions in Colombia, chose IBM technologies to modernize its 麻豆原创 software landscape. With the ability for the solution to deliver better TCO, Plastilene can continue its focus on growth and regional diversification.
• GBM, a leading IT services company in Central America and the Caribbean, is focused on improving agility, scalability and real-time insight to better support its customers. By leveraging IBM technology curated for 麻豆原创 Cloud ERP Private to help gain reliability, security and high performance, GBM is creating a strong foundation to adopt 麻豆原创 software innovations and drive continuous transformation across the organization.

Industry-Leading 麻豆原创-Certified Infrastructure Enables Cloud Modernization

鈥淎s enterprises modernize, the journey to 麻豆原创 Cloud ERP Private is dedicated to helping on-premises customers of 麻豆原创 ERP tailor their transformation and bring business applications, data and AI together with 麻豆原创 Business AI Platform. Some of these customers are now modernizing their cloud ERP landscapes and advancing their cloud ERP digital transformation strategies with 麻豆原创 solutions on IBM Power Virtual Server,鈥� said Lalit Patil, CTO for RISE with 麻豆原创 and Head of Cloud Lifecycle Engineering and Operations, 麻豆原创 SE.

鈥淥rganizations across industries are accelerating their move to 麻豆原创 Cloud ERP Private and require a trusted cloud platform designed for mission鈥慶ritical workloads,鈥� said Hillery Hunter, General Manager for IBM Power, CTO, IBM Infrastructure. 鈥淏y combining the security, scalability and resiliency of IBM Power and IBM Cloud with the transformation capabilities of 麻豆原创 Cloud ERP Private, we are committed to helping clients move forward with confidence on their modernization journeys.鈥�

IBM is a full lifecycle strategic partner of 麻豆原创, providing end-to-end consulting and technology solutions for 麻豆原创 customers including hybrid cloud, automation and agentic AI. IBM and 麻豆原创 recently progress across AI and agentic capabilities to help accelerate enterprise transformation, including an expanded collaboration through the Agent2Agent (A2A) interoperability standard to perform complex multi-agent services for clients. IBM Consulting Advantage can now manage Joule Agents, which work directly with IBM鈥檚 watsonx Orchestrate agents.

For more information about 麻豆原创 Cloud ERP Private on IBM Power Virtual Server, visit: .

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This document contains forward-looking statements, which are predictions, projections, or other statements about future events. These statements are based on current expectations, forecasts, and assumptions that are subject to risks and uncertainties that could cause actual results and outcomes to materially differ. Additional information regarding these risks and uncertainties may be found in our filings with the Securities and Exchange Commission, including but not limited to the risk factors section of 麻豆原创鈥檚 2025 Annual Report on Form 20-F.
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The agreement, concluded at the end of 2025, marks a significant step in migrating Nokia鈥檚 麻豆原创 landscape to the RISE with 麻豆原创 journey. By adopting RISE with 麻豆原创 Methodology, Nokia will follow a structured, end-to-end approach to migrating its ERP landscape covering processes, data, applications and operating models while gaining continuous access to innovation and embedded AI capabilities delivered through 麻豆原创鈥檚 cloud ERP portfolio.

Nokia has selected Microsoft Azure as the cloud platform underpinning the transformation, providing the global scale, security and performance required to support the company鈥檚 most business-critical enterprise workloads. 鈥淣okia鈥檚 decision reflects a clear commitment to business-led transformation,鈥� said , Global President Customer Success Europe, APAC, Middle East and Africa and Member of the Extended Board, 麻豆原创 SE. 鈥淩ISE with 麻豆原创 Methodology provides Nokia with a structured road map, integrated toolchain and continuous access to innovation. It enables the company to modernize its ERP landscape while keeping a clean core and building a strong foundation for enterprise AI.鈥�

A Structured Approach to ERP Transformation

RISE with 麻豆原创 is designed as a comprehensive business transformation framework rather than a point solution. It combines a standardized transformation methodology, integrated tools and expert guidance to help organizations move from legacy ERP environments to RISE with 麻豆原创.

麻豆原创 will operate and manage the 麻豆原创 S/4HANA software environment in the cloud, allowing Nokia to shift focus from infrastructure management to business outcomes. The approach supports process standardization, operational simplification and ongoing innovation, rather than a one-time system migration.

Nokia has been on a business and technical transformation journey with its next-generation 麻豆原创 S/4HANA software environment, covering finance and key logistics capabilities, supported by 麻豆原创 solutions and applications. These include 麻豆原创 S/4HANA for central finance, 麻豆原创 Master Data Governance, 麻豆原创 Extended Warehouse Management, 麻豆原创 Global Trade Services and 麻豆原创 S/4HANA Cloud for advanced ATP. AI-enabled functionality embedded in 麻豆原创鈥檚 cloud applications will be progressively adopted as part of the journey.

鈥淭his agreement builds on our existing work with 麻豆原创 and Microsoft and supports Nokia鈥檚 ambition to secure how we run our core business operations,鈥� said Marek O膷kay, VP, Global Head of IT Procurement & Vendor Management, Nokia. 鈥淏y applying RISE with 麻豆原创 Methodology on Microsoft Azure, we are strengthening a structured and future ready path for business growth 鈥� one that simplifies our ERP landscape, enables continuous innovation and strengthens our commitment for AI driven processes.鈥�

Microsoft Azure as the Cloud Foundation

Microsoft Azure will serve as the cloud foundation for Nokia鈥檚 RISE with 麻豆原创 journey, aligning with Nokia鈥檚 broader cloud and data strategy. Nokia already operates parts of its 麻豆原创 landscape on Azure, and consolidating workloads on a single hyperscale platform is expected to deliver benefits in performance, security latency and operational resilience.

As part of the agreement, Microsoft will collaborate closely with 麻豆原创 and Nokia throughout the transformation, supporting migration activities and ongoing optimization.

鈥淭his collaboration demonstrates how cloud platforms, enterprise applications and AI can come together to support complex, global business transformations,鈥� said Joacim Damgard, CVP, Europe North Microsoft. 鈥淏y running 麻豆原创 S/4HANA on Azure within the RISE with 麻豆原创 journey, Nokia is creating a scalable and secure foundation for continuous innovation.鈥�

Building on a Longstanding 麻豆原创 Relationship

Nokia has been an 麻豆原创 customer for decades. In recent years, the company has been consolidating multiple ERP systems into a unified 麻豆原创 S/4HANA software landscape as part of its next-generation ERP program.

The move to RISE with 麻豆原创 helps secure that journey, providing a structured methodology to help accelerate transformation, reduce complexity and unlock cloud native capabilities.

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About 麻豆原创

As鈥痑 global leader in enterprise applications and business AI, 麻豆原创 (NYSE:麻豆原创)鈥痵tands at the鈥痭exus鈥痮f business and technology. For over 50 years, organizations have trusted 麻豆原创鈥痶o bring out their best by uniting business-critical鈥痮perations spanning finance, procurement, HR, supply chain, and customer experience. For more information, visit鈥�.

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This momentum is aligned with consumer audio brand Victrola鈥檚 journey. Since its creation in 1906, has evolved into a global company known for its iconic record players, modern audio products, and mission to bring lifelong music memories to everyone

As it expanded into new sales and distribution channels, the company began to outgrow the limits of its existing ERP system. While its 麻豆原创 ERP Central Component (麻豆原创 ECC) system was stable and served the business well over the years, Victrola needed more scalability and flexibility to match its ambitions. According to Adam Schneider, SVP of Digital Strategy at Victrola, the goal was not simply to maintain operations, but to create a foundation that could support innovation. 鈥淲e needed something that fueled our creativity at Victrola,鈥� he said. And 麻豆原创 Cloud ERP was the right fit.

Victrola鈥檚 鈥渓et鈥檚 go鈥� mentality

A move to the public cloud offered more than a technical upgrade; it empowered Victrola to adapt. In that spirit, the team approached the transformation as a complete reimagining of its system with a cloud-first mindset.

鈥淲e have a 鈥榣et鈥檚 go鈥� mentality in every single meeting we do. You鈥檒l see a lot of fist bumps at Victrola and we love it. It really keeps that change front and center,鈥� Schneider said.

The project team prioritized change management, openly communicating the reasons for moving to the cloud and the expected benefits. Giving the 鈥渨hy鈥� made a big difference, Schneider said, and everyone was 鈥渆xcited for something new.鈥�

It was also important for the team to engage with and get buy-in from company leaders, who were concerned about disruption during Victrola鈥檚 peak sales quarter. To address these concerns, the team ensured the transformation was a business-led project, involving about 75% of Victrola鈥檚 leaders, Schneider said.

Another way the team worked to prevent operational disruption and build confidence in the stability of the new system was to involve a partner with deep expertise in 麻豆原创 Cloud ERP. The right partner would also fit seamlessly into Victrola鈥檚 unique, candid, music-oriented culture, Schneider said, which it found in .

鈥淲e wanted someone that could really provide that business knowledge on the public cloud,鈥� he said. 鈥淔rom a timing perspective, we couldn鈥檛 afford to have people figuring out the project as they鈥檙e on the project, so it really was the expertise of the public cloud that was a huge part in this.鈥�

With a winning team assembled, Victrola鈥檚 move to the public cloud was well-supported and bolstered by stakeholders across the company, 麻豆原创, and Reply.

Fine-tuning the foundation

Victrola’s covered order-to-cash and finance processes as well as large warehouse operations. The implementation itself was strategically timed to avoid overloading the team during the critical Q4 sales period, and it took about six months in total. Schneider said that the business adapted to the new system gradually: within the first month confidence grew, and by four months post-launch operations normalized with ongoing fine-tuning.

Victrola chose not to migrate historical data due to changes in organizational structure when it came to data management and the greenfield nature of the cloud system. This decision avoided technical debt and complexity. In addition, legacy customizations were largely eliminated through fit-to-standard workshops.

鈥淲e were looking for the ability to adapt with us, and we wanted a system that could be as simple or as complex as we needed it to be,鈥� Schneider said.

With the new cloud system, Victrola experiences greater trust in data accuracy and reporting agility. Financial processes have improved significantly, with profit and loss reporting time going from four hours to just 10-15 minutes. Faster closes and easier margin analysis contribute to Victrola鈥檚 improved agility, more informed decision-making, and stronger business performance.

鈥淲e鈥檙e more trusting in our data and that鈥檚 because we went through that exercise of really retooling what our landscape looked like and what our foundation looked like,鈥� Schneider said. It鈥檚 because of that re-engineering of data and transactions that Victrola has eliminated over 250 hours of finance-related work.

The next track

Now that Victrola is running on the public cloud, the sky is the limit when it comes to growth and innovation. 鈥淲hen we think about our AI strategy, I鈥檓 no longer scared of our system,鈥� Schneider said. 鈥淲e鈥檙e now applying an AI strategy to a state-of-the-art system that 麻豆原创 very much supports.鈥�

When asked what advice he鈥檇 give to companies contemplating a move to the cloud, Schneider said that there is never a perfect time to start, but it鈥檚 better to welcome transformation rather than fear it.

鈥淚 don鈥檛 think there is ever a perfect time to do these transformations,鈥� he added. 鈥淚 do think once you get into them, you start to really embrace them and feel good about it and say 鈥業t鈥檚 happening, let鈥檚 go.鈥欌��

Interested in learning more about how 麻豆原创 supports the transition from 麻豆原创 ECC to 麻豆原创 Cloud ERP? .

Photo courtesy of Victrola.

He mentioned driverless cars in San Francisco, autonomous drones conducting warfare, and robots that are trained to care for humans as real humans would. Speaking at the recent TAC Insights sponsored conference featuring , Weber admitted he finds it all rather scary, but also very exciting.

For an energy company operating critical infrastructure, this pace of technological change is not just fascinating or frightening鈥攊t creates a responsibility to adopt innovation in a controlled, resilient, and purpose鈥慸riven way.

Riding the waves

Weber sees these developments as a continuation of various “big waves” of technology that keep touching our hearts and minds as they shape the world around us. Who can imagine the world without the internet? Who can deny that the mobile phone didn鈥檛 revolutionize the consumption of IT when people started expecting the same ease of use in the workplace?

鈥淎I is creating the same response,” Weber explained. “ChatGPT makes my life easier at home solving gardening issues, so I expect it to make my life easier at work.鈥�

One of E.ON鈥檚 biggest challenges is closing the widening gap between the rapid pace of technological innovation in the outside world and the organization鈥檚 internal ability, shaped by its structure and DNA, to absorb and implement these changes effectively.

This tension became evident when leadership questioned whether sustained IT spending at large scale was justifiable. It soon became clear that continuous investment is the price of system stability, affordability, and resilience in a digitized energy system if E.ON is serious about becoming the leading playmaker in Europe鈥檚 green energy transformation.

To achieve this ambition, the company has defined three strategic priorities鈥攇rowth, sustainability, and digitalization鈥攔ecognizing that falling behind in digital capabilities would carry far greater long-term costs.

鈥淏ringing the system up to speed requires internal readiness. It means we must think deeply about investments, prioritization, and most importantly, people and culture,鈥� said Weber. 鈥淥ne thing is sure: we won鈥檛 be going back to what was normal speed before.鈥�

Becoming strategic

E.ON operates across three domains: energy grid, customer solutions, and energy infrastructure solutions. 聽This broad scope creates a high level of operational complexity, requiring scalable, transparent, and collaborative ways of working across the organization.

To meet these challenges, E.ON is strengthening its internal capabilities and investing in its people. By expanding in-house expertise, the company has welcomed over 1,000 specialists, including more than 500 in data and 300 in cybersecurity, fostering greater ownership, collaboration, and innovation across the organization.

This move reflects a broader philosophy. IT is no longer just a support function; it is foundational to pioneering the energy transition and delivering competitive advantage.

As E.ON鈥檚 transformation unfolds against a backdrop of rapid technological evolution, AI is at the heart of the current inflection point. Technologies like AI-powered assistants and automation tools are not novelties; they are actively redefining how customers interact with services. E.ON recognizes this shift and is embedding advanced technologies directly into its core systems, rather than treating them as add-ons.

Closing the gap

Weber explained that digital transformation at E.ON means putting the right technology into the core of the business to better serve its 47 million customers.

It starts with platform standardization, followed by cloud ERP transformation and the 麻豆原创 S/4HANA migration. Instead of building fragmented custom solutions, this strategy allows the company to integrate leading technologies into a cohesive architecture, ensuring scalability while avoiding unnecessary complexity. These basic investments in foundational infrastructure have delivered tangible results, including an 77% reduction in IT downtime within five years.

A key lesson from E.ON鈥檚 journey is the importance of embedding digital capabilities into the heart of operations. 鈥淲e鈥檝e moved away from isolated innovation hubs such as digital labs or experimental ‘garages’ in favor of integrating digital tools directly into business processes,鈥� Weber explained.

While innovation is essential, E.ON places equal emphasis on governance and control. Managing a digital ecosystem at this scale requires strong oversight to ensure security, consistency, and cost discipline. The company implemented centralized governance structures, including standardized contracting and unified IT system management to help maintain control without stifling innovation.

Equally important is investment in people. Through targeted training and capacity building initiatives, employees are empowered to turn new technologies into measurable business impact.

Harnessing AI

As with many companies, AI is at the center of E.ON鈥檚 forward-looking strategy, but the company is approaching it with deliberate caution. Rather than rushing to build proprietary platforms, E.ON is leveraging partnerships with established technology providers while maintaining flexibility in its IT portfolio. This approach allows the company to explore the potential of AI in customer service automation, predictive maintenance, and operational optimization without overcommitting to unproven solutions.

鈥淚n essence, our experience highlights a broader truth about digital transformation,鈥� said the IT expert. 鈥淪uccess really depends on balance. We absolutely must push innovation forward, but not at the expense of stability, cyber security or governance.鈥�

Equally, digital tools alone are not enough. Without proper training and alignment with business needs, even the most advanced technologies can fail to deliver value. E.ON addresses this through a “BizDevOps” mindset, ensuring that digital initiatives are an integral part of business goals and supported by the right capabilities.

In summary, E.ON鈥檚 transformation illustrates what it takes to modernize at scale in a complex, highly regulated industry. By doubling down on IT investment, bringing expertise in house, and adopting a disciplined yet forward-looking approach to innovation, the company has positioned itself for the future of energy.

The result is not only improved system performance or reduced downtime. It鈥檚 a fundamental shift in how technology drives business success, turning technology into a cornerstone of making new energy work鈥攔eliably, affordably, and at scale.

This was the exact situation facing Stephen Hawkes, director of Information Technology for the City of Charlottesville, Virginia. But instead of just managing the present, he and his team decided to build the future.

The perfect storm of challenges

For the City of Charlottesville, it was a perfect storm of challenges converging at once. At the heart of it all was a ticking clock: its aging, on-premise legacy system nearing its end-of-support date. This was more than a technical issue, it was a foundational risk to its operations.

At the same time, the expectations of its own employees were skyrocketing. “Everyone is an expert now,” Hawkes explains, pointing to the powerful smartphones and intuitive apps we all use daily. 鈥淐ity employees expected the same simplicity and modern design from their workplace software, but the old systems are causing friction and frustration.鈥�

This frustration was compounded by significant workforce constraints. Like most public sector organizations, Charlottesville found it difficult to compete with private sector salaries. “We are never going to be able to compete on pay,” Hawkes admits. This made recruiting and retaining skilled talent a constant battle.

And looming over everything was the growing shadow of cybersecurity threats. With AI-powered attacks becoming more sophisticated by the day, protecting the city’s data and infrastructure was a monumental task for a small IT team.

The quest for a modern solution

Inaction was not an option. The city needed more than just a simple upgrade. It needed a fundamental shift. It embarked on a bold, 14-month quest with a full digital transformation to move operations to .

This was its answer to the storm. By migrating two decades of data to the cloud, it built a new, resilient foundation for the future.

The impact on employees was immediate and profound. The new, web-based 麻豆原创 Fiori interface delivered the modern, intuitive experience everyone had been waiting for. “That’s what we’re probably most excited about,” Hawkes says. 鈥淲ith potentially powerful new AI capabilities at their fingertips, the city鈥檚 team can now exceed expectations, instead of struggling to meet them.鈥�

This new technology also became a powerful tool in the battle for talent. Hawkes sees the integrated AI tools as a “great leveler,鈥� enabling logical, problem-solving thinkers to perform complex data analysis without needing a specialized computer science degree. This widens the talent pool and empowers the existing workforce. And with the implementation of 麻豆原创 SuccessFactors solutions, its HR professionals now have modern tools to improve recruitment and retention.

Perhaps most importantly, the move gave the city a powerful ally in the fight against cyber threats. While Hawkes is proud of his internal team, he knows they can鈥檛 be on guard 24/7. “We’re not, [but] they are,” he says of 麻豆原创’s global security operation. “That gives us some ease.”

Wisdom from the journey: lessons for fellow leaders

A journey of this magnitude is never without its lessons. When asked what advice he鈥檇 offer his peers, Hawkes shared three crucial pieces of wisdom.

First, he stressed the absolute necessity of executive buy-in. For years, the project struggled to get off the ground due to leadership turnover. It wasn’t until the city manager gave the definitive ‘let’s move forward’ that the quest could truly begin. That sponsorship is the key that unlocks everything else.

Next, he highlighted the importance of choosing the right partner. A transformation project is too complex to undertake alone. Hawkes credits the success of going live on the exact day they had planned 14 months earlier to the deep trust and true partnership they had with their system integrator.

Finally, he spoke about the critical, and often underestimated, element of change management. You can have the best technology in the world, but if your people aren’t prepared for it, the project will falter. “We were very intentional about our change management,” Hawkes recalls, emphasizing that planning for the human side of the transition is just as important as the technical one.

The City of Charlottesville鈥檚 story is a testament to what鈥檚 possible when vision, strategy, and technology align. It鈥檚 a narrative of turning daunting challenges into defining opportunities and building a government that鈥檚 ready for tomorrow.

To get the full, firsthand account of this incredible transformation, .

Jamison Braun is SVP and managing director for U.S. Public Services at 麻豆原创 America.

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Grupo UMA, a leading motorcycle assembler and distributor, is accelerating manufacturing growth across Colombia and Central America with 麻豆原创 Cloud ERP Private.

Operating in multiple countries and serving thousands of riders every month, the company needed standardized, automated, and data鈥慸riven processes to support expansion while maintaining quality and customer experience. By implementing 麻豆原创 Cloud ERP Private, Grupo UMA streamlined core business processes across finance, production, and logistics, replacing manual work with real鈥憈ime insights and end鈥憈o鈥慹nd process integration. Global operating models, automated workflows, and transparent cost visibility now enable faster decision鈥憁aking and scalable growth across the region. The impact: production increased from approximately 11,000 to 17,000 motorcycles per month, with a clear path to 20,000. Across markets including Guatemala, El Salvador, Costa Rica, Honduras, Nicaragua, and Colombia, Grupo UMA is improving supply chain efficiency, optimizing production capacity, and delivering consistent quality with solutions such as 麻豆原创 Extended Warehouse Management (麻豆原创 EWM). Beyond operations, teams are shifting from manual, operational work to a more strategic, innovation鈥慸riven, and analytics鈥慺ocused approach鈥攈elping the organization evolve into a truly data鈥慸riven enterprise.

Discover how 麻豆原创 helps manufacturers in Latin America scale faster, operate smarter, and deliver better customer experiences with cloud ERP and read the full customer story on the 麻豆原创 News Center.

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

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

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

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

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

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

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

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

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

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

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

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

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

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

The objective of this collaboration is to digitalize procedures, improve efficiency and deliver better services to municipal employees and citizens in the areas of finance, revenue management and human resources.

The Madrid City Council has been working with 麻豆原创 software for two decades. It began in 2004 with the implementation of the first solutions in the areas of finance and HR, and in 2020 launched its public administration modernization project with the migration to the private cloud. This process is now advancing further with the adoption of the RISE with 麻豆原创 journey and 麻豆原创 Business Technology Platform (麻豆原创 BTP). The former is a comprehensive journey that combines the elements needed to migrate to the private cloud under a single contract: 麻豆原创 S/4HANA, infrastructure and managed services. The latter is the platform for integration, extension and application development.

A New Public Management Model

The adoption of these technologies represents a true revolution in the way municipal procedures are managed, from budgeting, execution and control of revenues and expenditures to the comprehensive management of human resources. This approach makes it possible to move beyond traditional models based on fragmented systems toward unified management with real-time information and digitalized processes.

The transformation has a particularly significant impact in the tax domain, as part of the project includes the integration of tax and revenue management solutions from 麻豆原创 into the city鈥檚 financial platform. This enables municipal revenues to be managed as a natural extension of the financial system, eliminating isolated developments and facilitating an end-to-end view of the full cycle, from taxpayer registration and assessment to collection and inspection. As a result, operational efficiency is improved while strengthening financial control and budget planning capabilities.

Currently, two-thirds of the City Council鈥檚 tax revenues are already managed within this environment, including Property Tax (IBI), the Urban Waste Tax for Business Activities (TRUA), Capital Gains Tax (IIVTNU) and the Terrace Tax (T2 2023). The next step will be to incorporate the Motor Vehicle Tax (IVTM) and the Economic Activities Tax (IAE).

The project has been developed using a phased methodology. During the first year, the City Council carried out a cleansing and harmonization of master data from its previous management systems (GIIM and +TIL), cross-checking identities with police databases, tax addresses with the Spanish Tax Agency (AEAT) and addresses with the municipal street registry. This process generated taxpayer 鈥淕olden Records鈥� and enabled, for example, an efficiency rate of 98.02% for Property Tax (IBI) in 2024. Data quality continues to be maintained for all new registrations.

According to Juan Corro, IT Manager of Madrid City Council (IAM), 鈥溌槎乖� technology offers us an extraordinary opportunity to accelerate our digital transformation and make the vision of a more efficient, innovative and citizen-centric local government a tangible reality. This project marks a paradigm shift: we are moving from managing paper files and isolated systems to managing information and processes in an integrated and intelligent way, with a 360-degree view. As a major capital city, Madrid has both the responsibility and the opportunity to position itself at the forefront of administrative modernization, serving as a benchmark for other municipalities.鈥�

Carlos Lacerda, Senior Vice President and Managing Director of 麻豆原创 Southern Europe, stated: 鈥溌槎乖� remains firmly committed to the Spanish public sector, which we have supported in its modernization processes for decades. This project is a benchmark for advanced digital administration and demonstrates how technology can act as a strategic enabler to simplify processes, integrate information and strengthen real-time data-driven decision-making, laying the foundation for a more agile, innovative and service-oriented public administration.鈥�

Benefits for the Administration and Citizens

The project is delivering benefits both in terms of internal efficiency and management, as well as citizen services:

• End-to-end process digitalization and a 鈥減aperless鈥� administration: The 鈥減aperless鈥� administration model has been consolidated, enabling the full digitalization of HR processes from start to finish. Requests are managed entirely through the municipal intranet. Internally, public employees can review and approve procedures with full traceability and in just a few steps, reducing processing times and errors caused by duplicate data. The result is a more agile, efficient and nearly 24/7 service that improves both the employee experience and citizen services.
• Operational efficiency and improved decision-making: Automation and AI capabilities integrated into the ERP system allow the City Council to significantly improve efficiency and productivity. Routine processes such as bank reconciliations and budget allocations are automated through rules and machine learning. In addition, the use of robotic process automation and services on 麻豆原创 BTP facilitates the automatic execution of repetitive tasks across systems. This reduces manual workload, minimizes errors and frees up time. Real-time analytics improve decision-making and, together with mobile and remote access to applications, enable more agile and flexible management.
• A more sustainable and efficient model: The implementation of RISE with 麻豆原创 enables the City Council to move toward a more sustainable and economically efficient IT model, based on subscription and pay-per-use principles. This approach reduces upfront investments, provides greater budget predictability and optimizes total cost of ownership. By scaling deployments according to municipal needs and paying only for required resources, the city improves responsible management of public funds while generating potential long-term savings.
• Greater adaptability and evolution: The City Council now has a flexible platform ready to evolve alongside technological, regulatory and social changes. The municipality will be able to align with national and European digital agendas, incorporate AI and advanced analytics capabilities, and evolve toward a smart administration model where data becomes a strategic enabler of better public policies.
• Continuous innovation: 麻豆原创 BTP is the innovation platform that integrates internal systems and third-party solutions, eliminating information silos. It also enables the rapid adoption of new technologies and responsiveness to changing needs and supports the City Council not only in modernizing processes but also in continuously evolving and launching innovative public administration initiatives.

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Media Contact:
Bel茅n Martinez Mill谩n, 麻豆原创 Spain, +34 91 4567220, belen.martinez@sap.com, CET
麻豆原创 麻豆原创 Room; press@sap.com

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