SAP and IBM Announce Client Momentum Across IBM Technology and SAP Cloud ERP Private to Drive AI Innovation

JYSK, GBM, DIFARE Group and Plastilene Group accelerate their business and drive ERP modernization through SAP Cloud ERP Private on IBM Virtual Server


WALLDORFSAP SE (NYSE: SAP) and IBM today announced that global enterprises JYSK, GBM, DIFARE Group and Plastilene Group have selected SAP Cloud ERP Private solutions on IBM Power Virtual Server to modernize enterprise resource planning (ERP) workloads in secure, reliable and scalable cloud environments.

Run your core operations with confidence using ready-to-run ERP capabilities in the cloud

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

According to a recent study 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 SAP 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’s global cloud infrastructure, designed to be highly resilient.
  • Migrate to SAP Cloud ERP Private and to the SAP Business Warehouse (SAP BW) application as part of the SAP Business Data Cloud (SAP BDC) solution, securely, quickly and with minimal disruption, including support for hybrid cloud and multicloud deployments.
  • Mitigate operational and security risk, through IBM Power’s 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 SAP-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 SAP 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 SAP. With more than 3,600 stores in 50 countries, the retailer needs its SAP 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 SAP journey.
  • DIFARE Group, a leading pharmaceutical manufacturing company based in Ecuador, required a robust, secure and scalable infrastructure to modernize its SAP 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 SAP 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 SAP 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 SAP Cloud ERP Private to help gain reliability, security and high performance, GBM is creating a strong foundation to adopt SAP software innovations and drive continuous transformation across the organization.

Industry-Leading SAP-Certified Infrastructure Enables Cloud Modernization

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

“Organizations across industries are accelerating their move to SAP Cloud ERP Private and require a trusted cloud platform designed for mission‑critical workloads,” said Hillery Hunter, General Manager for IBM Power, CTO, IBM Infrastructure. “By combining the security, scalability and resiliency of IBM Power and IBM Cloud with the transformation capabilities of SAP Cloud ERP Private, we are committed to helping clients move forward with confidence on their modernization journeys.”

IBM is a full lifecycle strategic partner of SAP, providing end-to-end consulting and technology solutions for SAP customers including hybrid cloud, automation and agentic AI. IBM and SAP recently announced 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’s watsonx Orchestrate agents.

For more information about SAP Cloud ERP Private on IBM Power Virtual Server, visit: ibm.com/products/rise-with-sap.

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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 SAP’s 2025 Annual Report on Form 20-F.
© 2026 SAP SE. All rights reserved.
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Customer Retention Over Acquisition: What the Advanced Success Plan for SAP CX Offers Utilities Customers

The utilities industry is undergoing its most significant transformation in decades. The shift to renewables, smart metering, distributed energy resources, and expanding deregulation are reshaping the relationship between utility companies and their customers. Customer experience is no longer a back-office concern; it is a front-line, competitive differentiator.

The Advanced Success Plan version for SAP Customer Experience solutions is designed precisely for this moment. It offers utilities customers a structured, continuously guided approach to maximizing value from SAP Customer Experience (SAP CX) investments, from first adoption through to AI-enabled optimization.

A sector in motion: why customer experience has become strategic for utilities

Four converging forces are making customer experience a boardroom priority for utilities and increasing the demand for structured, expert-led adoption support.

  • Energy transition and service complexity: Renewables, EV charging, solar feed-in tariffs, and demand response programs are adding new service dimensions. Customers expect their energy provider to manage this complexity seamlessly.
  • Deregulation and customer switching: In liberalized energy markets, customers can, and do, switch providers. The cost of acquisition consistently exceeds the cost of retention. Superior service experience is a measurable retention lever.
  • Smart metering and data volume: Smart meter rollouts generate billions of interval readings daily. This data can fuel proactive outreach and personalized billing, but only if the customer experience platform is correctly configured to act on it.
  • Regulatory intensity: Billing accuracy mandates, complaint resolution timelines, and outage notification requirements are intensifying. The SAP CX portfolio can support compliance when features are correctly activated and configured.

SAP in utilities: a significant and growing market

Utilities are not a niche segment for SAP. Understanding the scale of the SAP utilities community frames why the Advanced Success Plan for SAP Customer Experience solutions matters for this industry in particular. SAP is trusted by hundreds of utilities customers globally and is among the leading technology providers in the sector by installed base, a position that continues to grow year-on-year. The investment in the relationship has been made. The question is whether customers are fully using what they have.

With the Advanced Success Plan, customers can turn the SAP Customer Experience portfolio into a driver of growth and innovation. They can gain the confidence to act decisively, supported by unlimited expert guidance and intelligent insights that help ensure every feature can deliver measurable business value.

The business case: customer retention over acquisition

For utilities operating in competitive markets, retaining customers has become as strategically important as acquiring new ones. Customers can switch suppliers in minutes via a digital platform, complaint escalation processes are visible on social media, and billing errors in a smart meter world are harder to excuse and faster to escalate.

Turn transformation strategies into action with the Advanced Success Plan

The SAP CX portfolio can address these challenges across the full customer lifecycle. SAP Engagement Cloud enables targeted, segmented communications. SAP Service Cloud can centralize complaint management and agent interactions. SAP Sales Cloud helps manage accounts, contacts, leads, and opportunities. SAP Commerce Cloud is the digital sales and self-service storefront layer and can handle how customers discover, compare, purchase, and manage energy products online. What the Advanced Success Plan for SAP Customer Experience solutions does is help to ensure these capabilities are not just purchased but adopted, optimized, and continuously improved.

How the Advanced Success Plan structures the adoption journey

The Advanced Success Plan for SAP Customer Experience solutions helps organize the adoption journey across four distinct phases, each with a defined purpose and a set of targeted services:

  1. Introducing innovation: Identify and prioritize the right innovations for your business. Services here include product guidance sessions covering areas such as utilities session and agent desktop, intelligent selling, campaigns and segmentation, and AI foundation and use case navigator.
  2. Adopting innovation: Plan and prepare for structured adoption with minimal risk. Services include the AI process fit-gap analysis, key feature advisory, release guidance, success expert engagement, service planning, value management, innovation checkpoints, and adoption checkpoints.
  3. Activation and optimization: Enable hands-on activation of AI and customer experience capabilities in your environment. Services include activation sessions across SAP Sales Cloud, SAP Service Cloud, SAP Marketing Cloud, and SAP Engagement Cloud; AI agent activation; embedded AI activation; Joule activation; and technical and functional assistance.
  4. Success measurement and continuous improvement: Measure outcomes and sustain momentum through ongoing engagement. Services include a continuous engagement model, release guidance, success expert, value management, innovation checkpoints, and adoption checkpoints.

8 services available to utilities customers—and how each one helps

The Advanced Success Plan for SAP Customer Experience solutions comprises eight distinct services. Each has a defined scope, a specific business need it addresses, and measurable benefits. For utilities customers, each service connects to a characteristic operational or strategic challenge.

Product guidance
Structured sessions introduce utilities teams to the capabilities most relevant to their context, from meter-read-driven billing notifications in SAP Service Cloud to segmented communications in SAP Engagement Cloud. The goal is to accelerate time-to-awareness, so teams know what exists before they have to find it.

Key feature advisory
This is curated, customer-specific guidance on which features to activate and in what sequence. For utilities, this means filtering a broad SAP CX road map down to the capabilities that matter for smart metering, complaints management, and outage communications then discarding what does not apply.

Release guidance
Every SAP CX quarterly release brings dozens of updates. Release guidance helps ensure utilities teams receive a focused brief on what is relevant to their industry context, not a generic list of all product changes, so adoption decisions can be faster and better informed.

Solution review
This is a structured review of the current solution configuration against best practice. For utilities, this commonly surfaces configuration gaps in complaint workflows, billing notification templates, or service agent desktop layouts that erode the customer experience over time if left unaddressed.

Transformation advisory
Strategic guidance connects SAP CX capabilities to the outcomes utilities care about most: cost-to-serve reduction, complaint resolution improvement, and regulatory compliance. Transformation advisory helps move the conversation from features to business impact.

Activation
This is hands-on, expert-assisted activation of specific capabilities in the customer’s live environment. For utilities, this includes activating Joule for service agents and enabling AI-driven case categorization in SAP Service Cloud. Many autonomous agents or assistants announced at SAP Sapphire, once available, can be activated to help guide service agents to process cases.

Technical assistance
Direct technical support across all phases of the engagement covers integration architecture, performance guidance, load testing guidance for mass billing cycles, and resolution of complex system behavior. This service is especially critical for utilities given the high-volume, time-sensitive nature of meter-read processing and month-end billing runs.

Functional assistance
This comprises business process and functional configuration support throughout the engagement. Utilities-specific coverage includes complaint handling workflows, outage notification sequences, and the configuration of billing determinant displays in the service agent desktop, helping to ensure what is built serves the way utilities actually operate.

A practitioner’s perspective

Working directly with utilities customers shows first-hand how the Advanced Success Plan for SAP Customer Experience solutions can drive meaningful business value, especially for organizations without deep technical or functional SAP CX expertise in-house. Utility companies face a specific set of challenges: complex billing architectures, regulatory requirements, and high customer expectations for responsive service. The right services delivered at the right moment can be genuinely transformational. Four patterns stand out consistently:

  1. Bridging the knowledge gap for business users: Unlike system integrators or technical consultants, many utility business teams may not fully grasp the functional nuances required to maximize their SAP investment. Value-driven customer success manager engagement becomes critical here by translating technical possibilities into business outcomes, advising on feature adoption, and ensuring cross-team alignment across operations, IT, and customer management. The customer success manager acts as connective tissue between what SAP CX can do and what the business needs to achieve.
  2. Go-live checks are the foundation for seamless launches: Utilities cannot rely on generic go-live checklists. Are meter reads flowing end-to-end? Are billing determinants and rate structures properly mapped? Are customer service orders integrated with billing and meter management systems? Comprehensive go-live checks built for the utilities context eliminate the guesswork, giving teams confidence that key processes are functioning correctly from day one, not discovered to be broken three months into the first billing cycle.
  3. Road map guidance enabling better design decisions: Each SAP CX release brings dozens of new features, but only subsets are relevant for a given customer in a given market. Regular, curated road map guidance helps utilities focus on the features and design decisions that will most efficiently drive their specific outcomes, whether that is improving customer satisfaction, streamlining operations, or enriching digital self-service. This targeted approach prevents costly missteps and empowers business stakeholders to make confident decisions without requiring deep product expertise of their own.
  4. Early-phase support building for reliability and performance: The early project phase is often when performance issues and integration risks are best addressed, but it is also where internal teams feel least certain. Proactive support that includes performance reviews spanning interconnected billing and service systems, high-level architecture guidance, and utilities-specific load testing helps ensure reliable operation under real-world peak conditions. Utilities processing millions of daily meter reads, running mass billing cycles at month-end, and handling seasonal demand spikes need to know their system will hold before the peak arrives, not after it has passed.

What stronger SAP CX adoption looks like in practice

When utilities customers engage with the full Advanced Success Plan for SAP Customer experience solutions at the right moments, the outcomes can be concrete and measurable:

  • Adoption confidence: Teams understand the SAP CX capabilities that matter for their industry and know how to use them. Adoption is driven by guided enablement, not trial and error.
  • Configuration quality: Solution reviews and functional assistance can ensure complaint workflows, billing notifications, and service processes are correctly configured, reducing workarounds and support volume.
  • Release relevance: Every quarterly SAP CX update is assessed for utilities relevance. Teams receive a focused brief on what to adopt, not a generic list of all product changes.
  • AI activation at pace: Joule, embedded AI agents, and SAP Engagement Cloud intelligence features are activated with expert assistance, helping to move from available-in-catalogue to live-in-production for utilities use cases.
  • Integration reliability: Standard integrations between SAP Service Cloud and SAP S/4HANA Utilities are correctly configured, giving agents real-time access to meter history, billing data, and service orders.
  • Transformation clarity: Transformation advisory connects the SAP CX road map to the outcomes utilities care about most: cost-to-serve reduction, complaint resolution improvement, and regulatory compliance.

A service portfolio built for the complexity of utilities

The SAP investment in the utilities sector is substantial and well-established. Utilities organizations around the world have already deployed the SAP CX portfolio and are running their customer operations on it. The question is not whether they have access to world-class customer experience capabilities, but whether they are fully using what they have.

The eight services described above, combined with customer success manager-led perspectives on go-live quality, road map relevance, and performance assurance, represent a comprehensive framework for utilities organizations to realize the full potential of their SAP CX investment.

The Advanced Success Plan for SAP Customer Experience solutions is not a generic offering. When applied with industry focus and customer success manager expertise, it becomes a strategic asset, one that helps utilities deliver on the promise of a superior customer experience in an increasingly competitive, regulated, and technically complex market.


Rajeev Ranjan is product manager for the Advanced Success Plan for SAP Customer Experience.
Tara Tracey is global product owner for the Advanced Success Plan for SAP Customer Experience.

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Nokia, SAP and Microsoft Enter Strategic Multi-Year Agreement to Advance Cloud- and AI-Driven Business Transformation

WALLDORF SAP SE (NYSE: SAP) today announced that Nokia, a global leader in connectivity for the AI era, has signed a new multi-year agreement with SAP to help accelerate its enterprise transformation using RISE with SAP Methodology, with its SAP S/4HANA software environment hosted on Microsoft Azure.

Run your core operations with confidence using ready-to-run enterprise resource planning capabilities in the cloud

The agreement, concluded at the end of 2025, marks a significant step in migrating Nokia’s SAP landscape to the RISE with SAP journey. By adopting RISE with SAP 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 SAP’s 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’s most business-critical enterprise workloads. “Nokia’s decision reflects a clear commitment to business-led transformation,” said Manos Raptopoulos, Global President Customer Success Europe, APAC, Middle East and Africa and Member of the Extended Board, SAP SE. “RISE with SAP 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.”

A Structured Approach to ERP Transformation

RISE with SAP 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 SAP.

SAP will operate and manage the SAP 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 SAP S/4HANA software environment, covering finance and key logistics capabilities, supported by SAP solutions and applications. These include SAP S/4HANA for central finance, SAP Master Data Governance, SAP Extended Warehouse Management, SAP Global Trade Services and SAP S/4HANA Cloud for advanced ATP. AI-enabled functionality embedded in SAP’s cloud applications will be progressively adopted as part of the journey.

“This agreement builds on our existing work with SAP and Microsoft and supports Nokia’s ambition to secure how we run our core business operations,” said Marek Očkay, VP, Global Head of IT Procurement & Vendor Management, Nokia. “By applying RISE with SAP Methodology on Microsoft Azure, we are strengthening a structured and future ready path for business growth — one that simplifies our ERP landscape, enables continuous innovation and strengthens our commitment for AI driven processes.”

Microsoft Azure as the Cloud Foundation

Microsoft Azure will serve as the cloud foundation for Nokia’s RISE with SAP journey, aligning with Nokia’s broader cloud and data strategy. Nokia already operates parts of its SAP 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 SAP and Nokia throughout the transformation, supporting migration activities and ongoing optimization.

“This collaboration demonstrates how cloud platforms, enterprise applications and AI can come together to support complex, global business transformations,” said Joacim Damgard, CVP, Europe North Microsoft. “By running SAP S/4HANA on Azure within the RISE with SAP journey, Nokia is creating a scalable and secure foundation for continuous innovation.”

Building on a Longstanding SAP Relationship

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

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

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OMV’s Approach to Data-Driven Workforce Decisions

Do your workforce insights drive decisions or sit in dashboards? OMV uses the People Intelligence solution in SAP Business Data Cloud (SAP BDC) to spot workforce composition patterns and move talent where it’s needed. Looking ahead, OMV plans to expand into workforce planning and learning analytics, bringing people investments closer to measurable business outcomes.

OMV is a multinational oil, gas, and chemical company headquartered in Vienna, Austria. With operations spanning Europe, the Middle East, Africa, New Zealand, and Norway, OMV is a truly global enterprise.

Like much of the energy sector, OMV is navigating a significant strategic pivot. The company is investing heavily in sustainability initiatives: transforming plastic waste back into oil, building one of Europe’s largest waste-sorting facilities to produce feedstock for refineries, and recycling plastic cups collected from aircrafts into sustainable kerosene. This shift in the business model has triggered a corresponding transformation inside the business—and nowhere more so than in HR.

OMV’s People and Culture (P&C) function launched a strategic program to place people at the center of the company’s transformation. The ambition was clear: become a global HR center of excellence, increase service quality, standardize and harmonize processes, and move decisively towards digitization, automation, and self-service.

The challenge: fragmented data and a manual reporting cycle

Before SAP BDC entered the picture, OMV’s HR data landscape was fragmented across a patchwork of systems that were never designed to work together for workforce reporting and analytics. Employee data lived in two on-premise SAP HCM systems and SAP SuccessFactors HCM, alongside Microsoft Excel, SharePoint, and a system originally built for financial consolidation that P&C used for headcount reporting and planning.

Drive better people and business decisions across hiring, retention, pay, and more

The day-to-day consequences were significant. When a business unit head or department manager wanted a workforce KPI—headcount figures, turnover rates, or anything beyond a basic report available in the system—they would raise a request with their HR business partner. From there, the HR business partner would spend considerable time navigating multiple systems, manually pulling data, compiling it into spreadsheets, and formatting it into a presentation before handing it back to the manager. It was time-consuming, error-prone, and consumed HR capacity that should have been spent on strategic work. Managers had no direct, self-service access to their own workforce data.

Choosing SAP Business Data Cloud and People Intelligence

“Normally, our strategy is not to be the first with a new solution. With SAP BDC it was different,” Bernhard Graser, head of SAP Finance, HR, and Reporting at OMV, said. “We saw the potential immediately and wanted to stop the outbound migration of our HR and SAP data and keep it firmly in the SAP ecosystem.”

The timing was fortuitous. OMV had already completed a substantial SAP SuccessFactors HCM implementation, having deployed SAP SuccessFactors Performance & Goals, SAP SuccessFactors Learning, and SAP SuccessFactors Succession & Development and going live in 2023 with SAP SuccessFactors Employee Central, SAP SuccessFactors Compensation, and SAP SuccessFactors Recruiting. With all core employee data now sitting in a cloud-based SaaS system, the foundation for SAP BDC connectivity was already in place.

OMV’s implementation of SAP BDC and People Intelligence

OMV structured its SAP BDC journey in three steps.

The first step—turning People Intelligence live—was connecting SAP SuccessFactors HCM to SAP BDC. This was not entirely without friction: OMV discovered that its on-premise HCM systems sat on a different Identity Authentication service than SAP SuccessFactors HCM, which required alignment before integration could proceed.

A more substantive challenge was data governance. As an Austrian company with a Works Council, it was not possible for OMV to simply push all HR data into SAP BDC. The team implemented data masking, configured Read Access Logging, and established permission controls that mirror SAP SuccessFactors HCM exactly, meaning a user can only see data in SAP BDC that they are already authorized to view in SAP SuccessFactors HCM. This level of governance was a prerequisite before any business users could interact with the system.

The second step, currently in progress, involves migrating both HCM systems to SAP S/4HANA. Once complete, SAP S/4HANA will connect directly to SAP BDC, enabling a fully unified data feed from both SAP SuccessFactors HCM and SAP S/4HANA into a single platform.

The third step, planned for the near future, is the retirement of the legacy reporting stack entirely, eliminating the spreadsheets and replacing the current workaround in the financial consolidation system with SAP BDC as the single reporting and planning environment for HR.

SAP BDC’s architecture played a key role in the decision. SAP-managed data products—pre-built data models maintained and updated by SAP—were particularly attractive, especially because OMV had kept its SAP SuccessFactors HCM configuration close to standard. That near-standard posture meant a larger share of OMV’s HR data could be served through SAP-managed products, reducing the internal maintenance burden. When something changes in a source system or a data definition, it is SAP’s responsibility to update the model, not OMV’s.

Current and future use cases

After evaluating the intelligent content available in People Intelligence, OMV decided to start with workforce composition insights, now live and providing out-of-the-box dashboards on headcount, workforce structure, and composition, fully configurable and filterable by business users.

With the foundation in place, OMV’s P&C team has been actively collecting ideas for what to build next on SAP BDC. On the operational side, the team wants to track accident-related data as a workforce KPI, monitor open positions across the business, and measure time-to-hire. Diversity is another priority—data that currently sits fragmented across systems. Through its participation in SAP’s forward deployed engineering program, OMV is co-building use cases around learning and certification compliance—a business-critical need in a refinery environment where workers must hold current safety certifications to enter operational sites—as well as skills and headcount. Looking further ahead, OMV intends to move into machine learning and predictive modelling, using the SAP Databricks capability in SAP Business Data Cloud to forecast workforce demand and identify gaps in skills and FTEs before they materialize.

The bottom line

The direction is clear: a single source of truth for HR data, self-service access for every manager and business unit head, and a platform capable of growing from descriptive reporting today into predictive workforce intelligence tomorrow. As Graser encouraged his audience at the end of his session at SAP Sapphire Madrid: “We see great potential in SAP BDC—not only in HR, but also in finance. You should try it.”

Learn more about People Intelligence here.


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How SAP Customers Are Simplifying Software Expansion with SAP Store

The hardest part of buying enterprise software isn’t finding it—discovery is basically solved. You can find thousands of enterprise software options in an afternoon. The hard part is everything that happens between finding the right solution and actually having access to it.

Who owns the procurement motion? How does pricing get negotiated? Who handles the contract? What about tax, invoicing, and payment? Which team tracks approvals? And once it’s signed, how does it fit into existing contracts and renewal cycles?

Discover, try, and buy solutions from SAP and partners

Most of these previously mentioned challenges occur in e-mail chains, spreadsheets, and conversations that no one fully documents. Seventy-three percent of B2B buyers actively avoid suppliers who send irrelevant outreach—they’ve already done their research by the time they engage. But the internal process of actually completing a purchase remains as manual as it was a decade ago. Research, shortlist, evaluate, and then hand it off to a process that moves at a completely different speed.

This is especially true for organizations with existing SAP investments. Expanding a software landscape that’s already complex—adding new capabilities, aligning contracts, managing co-term timing across multiple products—adds layers of coordination that can slow even straightforward decisions to a crawl. Every new solution that doesn’t co-term with an existing contract means another renewal date to track, another negotiation cycle to manage, and another piece of the landscape that runs on its own timeline.

SAP Store exists to help remove those layers and barriers. For SAP customers, it’s the single place to discover, trial, and purchase both SAP and partner solutions—over 3,600 of them—within an environment that’s already connected to their existing SAP landscape. When a customer modifies an existing contract through SAP Store, new purchases automatically co-term with the original order. Pricing and discounts, if applicable, are inherited from the previous contract. There are no separate renewal cycles to manage, no renegotiations from scratch.

The buying process itself is also built to help remove the common points of friction. Automated entitlement checks confirm compatibility before a purchase is completed. Pre-verified product dependencies prevent deployment issues after the fact. For customers that want to move quickly, many solutions offer a “Buy Now” path that goes from selection to provisioned access in under 15 minutes. No forms to fill out, no calls to schedule.

AI Agents to Take Over 100,000 Manual Order Confirmations at Lemvigh‑Müller

The Danish wholesaler Lemvigh‑Müller has deployed artificial intelligence to automate one of the most time‑consuming tasks in procurement: processing supplier order confirmations. The solution consists of multiple AI agents, each responsible for a clearly defined task, orchestrated into a single automated workflow built on SAP Business AI. The outcomes are faster processing, improved data quality, and more accurate delivery information for customers.

When suppliers send order confirmations as PDF files, even minor discrepancies in price, quantity, or delivery dates can trigger significant manual effort within procurement. For Lemvigh‑Müller, one of Denmark’s largest wholesalers within steel, plumbing, heating and electrical products, this has long been a familiar challenge, consuming substantial time and resources.

The company has now tackled the very point where earlier automation initiatives often stalled. With a new solution based on several specialized AI agents, developed on SAP technology and implemented in close collaboration with NTT DATA Business Solutions, supplier PDF order confirmations can now be read, interpreted, compared, and processed automatically—directly against SAP systems.

Capture business-wide AI value with speed and confidence

“We have previously tried both RPA and traditional automation approaches without really achieving the desired effect. The key difference this time is that we broke the task down into multiple independent AI agents, each responsible for a specific part of the process. Together, they now handle what previously required manual review,” says Frederik Aakerlund, IT director at Lemvigh‑Müller.

10 weeks from idea to AI agents in production

The project originated with an e-mail from Jess Frederiksen, an AI‑savvy project manager in Lemvigh‑Müller’s Market and Procurement organization. After successfully matching an order confirmation with a purchase order using ChatGPT as an experiment, he approached the IT director to explore whether this could be turned into a fully integrated system solution.

From the initial tests to production deployment, the entire project took just 10 weeks. According to Lemvigh‑Müller, this short implementation timeline was critical in allowing the solution to demonstrate tangible business value quickly and build internal support.

“This was not a long-running project. In 10 weeks, we moved from idea to AI agents in production, already delivering measurable value to our procurement officers,” Aakerlund says.

Over time, Lemvigh‑Müller expects the solution to free up resources equivalent to three to four full-time employees. These resources will instead be redeployed to higher-value activities, including handling the most complex and exception‑driven orders.

“The objective is not to reduce headcount, but to use our expertise more effectively. The AI agents take care of routine tasks, enabling procurement officers to focus on cases where their experience genuinely matters,” Aakerlund adds.

More than 100,000 order confirmations automated

Each year, Lemvigh‑Müller sends approximately 175,000 purchase orders to more than 2,000 suppliers. While part of this volume is handled in a structured manner via EDI, around 60% of supplier order confirmations are still received as unstructured documents.

With the coordinated AI agents in place, the company can now automatically identify delays, quantity changes, and price discrepancies—and respond significantly faster.

“Previously, when order confirmations were handled manually, it could take hours or even days before changes were reflected across the organization. Today, the AI agents update the data almost immediately, allowing customers to receive a much more accurate picture of deliveries far sooner,” says Klaus Heinemann, head of SAP ERP at Lemvigh‑Müller, who led the development together with the project team. “In addition, we now identify price discrepancies before the final invoice is issued, saving time both for us and for our suppliers.”

Multiple AI agents orchestrated in a single workflow

The solution is built around three cooperating AI agents, each with a clearly defined role in the process. One agent handles incoming e-mails and attachments, a second extracts and structures data from PDF documents, and a third compares the extracted information against purchase orders in SAP to determine whether there is a match or a deviation.

As a result, complex and unstructured supplier data can be processed in a unified, automated workflow without requiring procurement officers to open and manually review lengthy PDF files.

“What makes this solution robust is the interaction between the agents. Each agent is highly specialized, but they are orchestrated in a way that ensures the process flows seamlessly from start to finish,” Heinemann explains.

Three AI agents working together at Lemvigh‑Müller

Lemvigh‑Müller’s solution is built around three specialized AI agents, each responsible for a clearly defined task within the procurement process. Together, they form a single, end‑to‑end, automated workflow:

1. The e-mail agent receives and sorts incoming e-mails from suppliers. The agent identifies relevant order confirmations and attached documents and routes them to the next step in the process.

2. The data extraction agent extracts key information such as prices, quantities, and delivery dates from PDF documents and structures the data so it can be compared directly with purchase orders in SAP.

3. The matching agent compares the extracted data with existing purchase orders in SAP and determines whether there is a match or a deviation. In case of a match, the process continues automatically, while deviations are flagged for further handling.

During the project, the importance of master data quality also became increasingly clear.

“In areas such as Incoterms and other master data, we identified improvements that need to be addressed. This has been an important learning not just for this initiative, but for our broader work with AI,” he says.

While it is still too early to measure the full impact on customer experience, error rates, or claims, expectations are that faster and more precise handling of supplier confirmations will, over time, lead to fewer surprises and significantly improved delivery transparency. Internally, the solution has been met with strong interest and curiosity among employees.

“Procurement officers clearly recognize the value of being relieved from the most tedious routine work. This has sparked a constructive dialogue about how technology can best support their day‑to‑day responsibilities,” Heinemann says.

The interaction between the three AI agents makes it possible to automate a task that previously required manual review of unstructured documents.

Business AI with a clear business outcome

According to Lemvigh‑Müller, the investment is expected to deliver a return within a relatively short timeframe.

“We are talking about quarters rather than years when it comes to ROI. That is why it was essential for us to get the solution into production quickly and focus on processes with a clear and measurable impact,” Aakerlund says.

For SAP, the project serves as a concrete example of how artificial intelligence can be embedded directly into core business processes rather than remaining a disconnected experiment.

“Many companies talk about AI agents primarily in terms of automation. Lemvigh‑Müller demonstrates that the real challenge—and the real opportunity—lies in coordination,” says David Pontoppidan, head of AI at SAP for the Nordics and Baltics. “It is the orchestration of three specialized agents directly within the core process that makes this solution robust. This is also where many multi‑agent initiatives fail, not due to limitations of individual agents but because of insufficient coordination. Lemvigh‑Müller has succeeded by anchoring the solution in its SAP landscape, where data, business rules, and governance frameworks are already firmly established.”

He continues: “Innovation is not about company size. Lemvigh‑Müller shows that a Danish organization with short decision paths and a pragmatic approach to technology can move faster than many large global enterprises that are still in the planning stage. Ten weeks from idea to production is far from the norm, but perhaps it should be.”

Designed for operations and scalability

The solution was implemented in close collaboration with NTT DATA Business Solutions, which was responsible for making the solution production‑ready and fully integrated into Lemvigh‑Müller’s SAP landscape.

“By distributing responsibilities across multiple AI agents, Lemvigh‑Müller has been able to automate a complex process without losing transparency or control. This has enabled a fast and secure transition from pilot to production and ensures a more robust solution that can easily be expanded as new requirements emerge,” says Kristian Dahl, SAP UX manager at NTT DATA Business Solutions.

According to Dahl, the modular, agent‑based architecture was a key enabler in moving efficiently from proof of concept to live operation.

First step in a broader AI agent strategy

Initially, the AI agents have been deployed for selected supplier inboxes and business areas. However, Lemvigh‑Müller already sees significant potential in applying the same agent‑based approach across additional administrative processes.

“This is the first AI agent solution we have put into production. The experience has given us the confidence to consider similar approaches across other areas, including invoice processing and order management,” Aakerlund concludes.


Ellen Vig Nelausen is a Nordic Integrated Communications Expert at SAP.

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Sovereign Data Infrastructure in Europe: Essential or a Distraction?

The push for sovereign AI data centers in Europe (and elsewhere) reflects a shift in how IT infrastructure is perceived by enterprise customers, policy makers, and politicians. Because of the growing importance of business AI capability, compute capacity is no longer seen as “just” IT plumbing—it is strategic infrastructure, akin to energy or telecommunications.

AI infrastructure as strategic asset 

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

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

Security and compliance imperatives 

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

As Christian Klein, CEO of SAP SE, noted at the SAP Sapphire Madrid event last month, many European customers operate in the public sector or other highly regulated industries. “Geopolitical risk is a growing concern,” he said. “What if sanctions suddenly block data flows across borders? Or if the latest LLMs can’t be deployed in certain regions?”

SAP protects data, operations, trust, and growth

Christine Lagarde, president of the European Central Bank, also highlighted this concern in her November 2025 speech titled “The transformative power of AI: Europe’s moment to act,” noting that Europe must “avoid single points of failure” in critical areas such as data centers and compute capacity.  

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

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

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

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

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

Barriers and concerns

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

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

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

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

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

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

The business view 

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

While data residency and the other elements of digital sovereignty are essential for some businesses operating in sensitive and highly regulated sectors, the sovereignty debate in Europe risks oversimplifying a fundamentally global industry. As Henna Virkkunen, the European Commission’s technology chief, noted: “Nobody can be competitive alone.”  

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

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

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


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SAP Introduces End-to-End Solution for CBAM Declarants

The EU’s Carbon Border Adjustment Mechanism (CBAM) is moving beyond a regulatory reporting exercise. From 2026 onwards, emissions embedded in imported goods carry real, measurable cost exposure. To help customers navigate it, SAP is introducing an integrated, end-to-end CBAM solution that starts with CBAM declarants, built on SAP Sustainability Footprint Management and SAP Green Ledger, and will expand to fully support operator needs.

Companies need to quantify those emissions, recognize liabilities, withstand audit scrutiny, and, ultimately, prepare to settle carbon costs through certificates linked to the EU Emissions Trading System.

In practical terms, carbon becomes a priced input, one that directly affects margins, cash flow, and sourcing decisions in a way that is comparable to other cost drivers.

Why CBAM matters now

CBAM cuts across business functions. Finance teams manage liabilities and forecast costs. Procurement teams need emissions data from suppliers and must incorporate it into sourcing decisions. Trade and compliance teams ensure imports are correctly classified and reported.

No single function can manage this in isolation. The financial implications depend on operational data, and operational decisions increasingly depend on carbon cost exposure.

The regulation initially applies to imports of iron and steel, aluminum, cement, fertilizers, hydrogen, and electricity, with a threshold of more than 50 tonnes annually for declarants. While this concentrates formal obligations on larger importers, the effects extend into supply chains as companies request more detailed and verified emissions data from suppliers and adjust sourcing decisions accordingly.

From reporting to financial exposure

What changes in 2026 is not only what companies must report, but what follows from it. Imports of CBAM-covered goods into the EU create a carbon liability for authorized declarants based on their verified embedded emissions. Those liabilities accumulate throughout the year and must be reported, audited, and settled through the purchase and surrender of CBAM certificates in 2027.

This creates an ongoing compliance cycle with clear financial implications:

  • Emissions must be tracked and translated into certificate requirements.
  • Liabilities accumulate throughout the year.
  • Certificates must be purchased, managed, and surrendered to cover those liabilities.

For finance, this means ongoing exposure that needs active management. For procurement and supply chain teams, costs now hinge on supplier emissions data.

An integrated approach to CBAM

Decarbonize your value chain with carbon accounting software from SAP

Many organizations are currently managing CBAM across multiple systems, spreadsheets, and manual processes. That approach becomes difficult to sustain under audit and as volumes increase.

SAP’s approach brings together the key elements of CBAM management into a connected process: data collection and mapping, emissions and cost calculation, analytics, carbon and financial accounting of liabilities, certificate asset management, and declaration generation.

SAP will offer an integrated, end-to-end CBAM solution for declarants, designed on SAP Sustainability Footprint Management and SAP Green Ledger. This builds on SAP’s strengths in carbon and financial management.

This new approach allows companies to move away from fragmented workflows toward an integrated solution tied to core business processes.

Coming soon: End-to-end CBAM data capture and calculation with SAP Sustainability Footprint Management

SAP Sustainability Footprint Management will provide the operational backbone for CBAM by helping to establish a reliable data foundation. At its core will be customs data, such as import records and CN code classification, sourced from SAP Global Trade Services and other trade systems. Without that layer, companies struggle to identify where CBAM applies.

Building on this foundation, SAP Sustainability Footprint Management will help centralize CBAM-relevant ERP, trade, and supplier data in one place; ingest supplier emissions data via Excel uploads with automated interpretation; and calculate embedded emissions, certificate requirements, and estimated CBAM costs. A dedicated CBAM dashboard will allow organizations to analyze emissions and cost exposure, while built-in reporting capabilities support the generation of CBAM reports ready for submission to EU authorities.

Available today: Financial control of CBAM exposure with SAP Green Ledger

A critical differentiator in CBAM readiness is the ability to connect carbon data with financial processes. Today, with SAP Green Ledger, companies can track the number of certificates required, valuate them as financial liabilities, continually revaluate based on price changes, and post financial impacts to the appropriate accounts. This is the level of traceability finance teams and auditors expect, in line with the International Accounting Standards.

This integration enables organizations to:

  • Recognize, valuate, and periodically revaluate CBAM liabilities.
  • Track certificate holdings and their valuation (coming soon).
  • Support audit-ready reporting and verification.
  • Forecast and plan for cash impacts (coming soon).
  • Break down and manage costs on a product level (coming soon).

Most organizations still treat operational data and financial impact as separate. These capabilities can bring them together.

Beyond compliance: enabling better decisions

While CBAM is often framed as a compliance burden, it also provides an opportunity to improve decision-making. When carbon costs are visible and integrated into business processes, companies can see exactly where exposure sits and where action will make the biggest impact.

With better data, organizations can:

  • Identify high-cost emission hotspots in their supply chains.
  • Evaluate supplier choices based on emissions and cost trade-offs.
  • Improve forecasting and budgeting of carbon-related costs.
  • Reduce reliance on conservative and costly default values by using actual data.

This does not remove the cost, but it can make it easier to manage and, in some cases, reduce.

What to focus on now

As CBAM has entered its definitive phase, the immediate priority is building a reliable data foundation. That includes accurate customs data and clear mapping of where CBAM applies. Supplier engagement is another practical constraint. Collecting verified emissions data often requires structured outreach and follow-up. Tools such as SAP Sustainability Data Exchange can support with supplier communication and data collection, but the effort remains organizational as much as technical.

From there, organizations can assess their CBAM exposure, ensure the necessary data flows are in place, and plan their solution architecture to optimize total cost of ownership, automation, and integration into business functions. It continues with ensuring that emissions calculations are traceable and auditable. That influences behavior; carbon now drives planning, which no team can ignore.

At the same time, companies need to define how CBAM data flows into finance. Linking emissions, liabilities and certificates to financial systems early helps avoid rework and reduces audit risk.

What’s next

CBAM is a broader shift in how environmental impact is reflected in business performance. Carbon is tracked, priced, and managed alongside other cost drivers.

Organizations that treat CBAM as a periodic reporting task will likely remain reactive. Those that integrate it into financial and operational decision-making will be better position to manage its impact.

For more information, visit sap.com/carbonaccounting.


Gunther Rothermel is chief product officer for SAP Sustainability.

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How the Advanced Success Plan for SAP CX Operationalizes Hyper-Personalization at Scale

Customers expect brands to know them, anticipate their needs, and engage them with relevance across every channel and touchpoint. The challenge isn’t agreeing on the vision. The challenge is closing the gap between that vision and systematic, scalable execution.

For many SAP Commerce Cloud and SAP Engagement Cloud customers, this gap shows up in familiar ways: recommendation engines that surface generic results because behavioral data is not connected, e-mail campaigns timed by calendar rather than by individual habit, loyalty programs that reward transactions rather than relationships, and personalization rules that require significant manual effort to maintain at scale.

The ambition is there; the infrastructure to fulfill it, however, is often partial. Clean data is siloed, AI capabilities are underutilized, and the organizational discipline to run ongoing experimentation does not yet exist.

This is precisely the problem the Advanced Success Plan version for SAP Customer Experience solutions is designed to solve.

What hyper-personalization actually requires

True hyper-personalization is not a feature you switch on. It is a capability you build systematically across three interdependent layers: data, decisioning, and delivery.

Turn transformation strategies into action through a coordinated set of services and guidance for every stage of your journey

Data is the foundation. Hyper-personalization requires unified, consent-aware, real-time customer profiles consolidated across commerce transactions, engagement history, browsing behavior, service interactions, and loyalty activity. Without this foundation, even the most sophisticated AI models are operating on incomplete signals.

Decisioning is where AI translates those signals into action—the next best product to surface, the right offer to present, or the optimal moment to reach out. This layer requires not just model accuracy but governance, knowing when to trust the algorithm and when human judgment should override it.

Delivery is where the personalized experience reaches the customer, at the storefront, in the inbox, through a mobile push, or across a loyalty interaction. This layer requires orchestration across channels, consistent with the customer’s current context.

The Advanced Success Plan for SAP Customer Experience solutions helps address all three layers simultaneously, providing the expert guidance, governance frameworks, and adoption acceleration needed to move from point capabilities to an integrated operating model.

Hyper-personalization in SAP Commerce Cloud

SAP Commerce Cloud can provide the storefront execution layer for personalization at scale. The solution’s AI-assisted product recommendations capability enables organizations to show the most relevant products to each visitor at the right point in their shopping journey, from trending products and related items to complimentary products that support cross-sell and upsell motions. This can go beyond manual merchandising rules; it can respond dynamically to real-time behavioral signals, helping to improve conversion performance and drive product discovery at a scale no merchandising team could replicate manually.

Yet many SAP Commerce Cloud customers have not yet activated the full depth of these capabilities. The blockers are predictable: data quality gaps that limit recommendation model performance, integration complexity between the commerce layer and upstream profile data, and an absence of the experimentation discipline needed to tune and improve models over time.

The Advanced Success Plan for SAP Customer Experience solutions can bring targeted guidance to help address these barriers. Data readiness assessments can establish the quality baselines and integration patterns required to feed reliable signals into SAP Commerce Cloud’s personalization engine. Adoption accelerators help teams operationalize experimentation, defining hypotheses, running A/B tests, and translating results into durable configuration changes. The outcome is a storefront that can continuously learn and improve, rather than one frozen at the point of initial configuration.

Hyper-personalization in SAP Engagement Cloud

SAP Engagement Cloud, powered by SAP Emarsys, can extend personalization beyond the storefront and into the full lifecycle of the customer relationship. This is where SAP Commerce Cloud’s transactional signals combine with engagement history to help power cross-channel personalization that is individual rather than segment-based.

The solution’s AI-assisted send time optimization capability is a direct example of this philosophy in practice. Rather than sending campaigns on a fixed schedule, the capability can analyze each contact’s behavioral patterns—independently of time zone, language, or region—and deliver messages at the precise time each individual is most likely to engage. This is not personalization as a concept; it is personalization as an automated, scalable operational process.

Paired with the SAP Emarsys, AI-assisted campaign translator capability and omnichannel orchestration, SAP Engagement Cloud enables marketing teams to move from building campaigns to orchestrating journeys where the system is continuously learning which signals should trigger which interactions and adapting those interactions based on what drives response.

The native integration between SAP Commerce Cloud and SAP Engagement Cloud is a critical accelerator here. By unifying commerce behavior and engagement data, organizations can drive increases in conversion rate, purchase frequency, and average order value in ways that neither system could achieve independently. The Advanced Success Plan for SAP Customer Experience solutions helps customers realize this joint value by aligning integration architecture, data governance, and adoption milestones across both products within a single, coordinated engagement model.

How the Advanced Success Plan enables continuous improvement

Hyper-personalization projects are often treated as one-time implementations. The Advanced Success Plan for SAP Customer Experience solutions is designed to make them repeatable, continuously improving programs. This means:

  • Outcome-based governance: Co-defining the KPIs that matter, such as conversion rate lift, repeat purchase rate, engagement open rates, and average order value, and building work streams aligned to move them measurably.
  • Prescriptive adoption patterns: Structured playbooks for activating AI-assisted recommendations, send time optimization, and next-best action logic, with clear milestones and measurable gates.
  • Continuous enablement: Role-based coaching for the teams responsible for data, product ownership, and campaign operations, closing skills gaps that otherwise cause personalization programs to plateau or regress.
  • Proactive telemetry: Regular adoption checks that surface underperforming configurations before they impact business outcomes, and AI-guided best practices that inform ongoing tuning.

Making the business case concrete

For SAP Commerce Cloud customers, the value of operationalized hyper-personalization can be seen in storefront metrics: higher conversion from AI-surfaced recommendations, increased average order value through intelligent cross-sell, and improved product discovery that reduces bounce and exit rates.

For SAP Engagement Cloud customers, the value can be seen in engagement quality: open rates and click-through rates that reflect individual relevance rather than list-wide broadcast, improved campaign ROI through AI-optimized delivery, and loyalty program engagement that reflects relationship depth rather than transaction volume.

Across both, the compounding effect of unified data and orchestrated decisioning is what transforms hyper-personalization from a POC into a sustained growth mechanism, one that gets measurably better over time.


Payal Sachdev is product manager for the Advanced Success Plan for SAP Customer Experience.
Tara Tracey is global product owner for the Advanced Success Plan for SAP Customer Experience.

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Procurement’s New Balancing Act: Cutting Costs, Adopting AI, and Proving Strategic Value

As cost pressures intensify, procurement leaders must find new ways to deliver savings, manage risk, and accelerate transformation.

Over the past several years, procurement has steadily expanded its influence inside the enterprise. As supply chains faced unprecedented disruption, procurement leaders became trusted advisors to the C-suite on resilience, risk management, and sustainability. Their visibility increased and so did the expectations placed upon them.

Now, the playbook is being rewritten once again.

Research from the 2026 Economist Enterprise Report titled Procurement at a crossroads: from optimism to realism, sponsored by SAP, finds that financial performance has reemerged as the primary benchmark of procurement’s success. Drawing on a global survey of 2,648 C-suite executives, the report found that 54% cite cost control as procurement’s greatest contribution to the business, up from 43% just one year earlier. The findings point to a function that is increasingly stretched, yet positioned to deliver measurable business outcomes—if it can navigate a difficult balancing act.

Cost control returns to center stage

The shift is not surprising given the environment. Persistent inflation, tariff uncertainty, and continued investment in supply chain resilience have pushed cost management back to the top of the executive agenda. At the same time, companies are investing in dual sourcing, nearshoring, and inventory buffering to reduce exposure—strategies that strengthen resilience but often raise costs. Procurement is expected to offset those increases elsewhere.

Cost savings can be sustainable with AI-powered and integrated sourcing, contracting, and supplier management applications

What makes this moment particularly challenging is that procurement’s broader responsibilities have not diminished. Teams are still expected to manage geopolitical risk, advance sustainability, and support digital transformation. The mandate has expanded significantly, often without a corresponding increase in capacity, tools, or operating model support. Delivering savings, limiting cost increases, and managing input costs while fulfilling a growing strategic role is the defining tension facing procurement leaders today.

AI is becoming procurement’s digital imperative

Technology, and AI in particular, is increasingly seen as the key to resolving tension. In the Economist Enterprise study, 60% of executives identified digital transformation as procurement’s top strategic priority over the next 12 to 18 months, up sharply from 38% in 2025. More than half (56%) identified AI as the primary driver of that transformation.

The emergence of agentic AI is accelerating expectations further. More than half of executives are planning to implement or evaluate agentic AI capabilities within the next 12 to 18 months. Unlike earlier generations of AI that focused primarily on generating insights, agentic AI introduces the ability to execute workflows—from guided buying experiences to automated purchase order creation—enabling procurement to move beyond recommendations and drive actions.

Even so, executive expectations remain grounded. Only 9% of survey respondents want AI to lead most procurement decisions within three years. Procurement’s highest-value work continues to rely on human judgment, strong supplier relationships, and the ability to navigate complex trade-offs. AI plays a critical role in strengthening these capabilities, but it does not replace them.

Realizing that potential, however, requires the right foundation. Connected data, clear governance, and close collaboration across procurement, finance, IT, and operations are prerequisites for generating AI outputs that are reliable and accountable.

Category management takes on greater importance

As procurement balances cost pressures with broader business priorities, category management is emerging as a critical discipline. The report found that category and demand management are expected to receive the second highest level of digital investment among procurement disciplines over the next three years, trailing only spend and performance analytics.

This reflects the growing complexity of procurement decisions. Category leaders are no longer simply awarding projects to the lowest-cost supplier. They are expected to weigh cost, risk, sustainability, and supplier performance simultaneously—a level of complexity that demands better analytics and faster insight-to-action capabilities.

That level of nuance can strengthen procurement’s impact, but it can also slow execution. More sophisticated category strategies require better data, sharper analytics, and faster insight-to-action capabilities. The report found that category strategy has become the third most common source of process delays, behind only contracting and sourcing.

Success increasingly depends not on collecting more data, but on turning data into confident decisions quickly. Organizations that close that gap will be better positioned to execute strategy, not simply develop it.

Procurement’s strategic value is being tested

Perhaps the most striking finding in the report is a growing confidence gap. While nearly three-quarters of executives still believe procurement collaborates effectively across the organization, that figure dropped from 90% in 2025 to 74% in 2026. Confidence in procurement’s role in shaping digital transformation strategy also declined meaningfully over the same period.

These numbers do not signal a retreat from procurement’s strategic importance. Rather, they reflect a broader shift in how enterprise decisions are being evaluated. As AI democratizes access to data across the organization, more stakeholders have the information to question decisions and demand clearer evidence of value.

Procurement leaders are now expected to control costs, manage risk, strengthen resilience, and help guide AI adoption, often simultaneously and without additional resources. The question is no longer whether procurement belongs at the leadership table. It is whether procurement can consistently deliver the value expected of it across an expanding and increasingly complex set of priorities.

Procurement’s next chapter

The Economist Enterprise findings paint a picture of a function at a pivotal moment. Cost savings has returned as the primary mandate, yet procurement is still expected to manage risk, protect supply continuity, and lead digital transformation.

Meeting those expectations will require more than layering AI onto existing processes. It demands connected data foundations that make AI outputs trustworthy, visibility across suppliers and spending, and technology that enables teams to move from reactive decision-making to proactive intervention.

The leaders who will define procurement’s next chapter are those who can turn AI, data, and connected processes into faster decisions, stronger resilience, and measurable business impact.

To learn more, join the upcoming Economist Enterprise–hosted webinar, “Leading the firm: The future of procurement,” on June 25, 2026, which will explore how leaders can accelerate AI adoption, prove digital value, and strengthen supply chain resilience.


Gordon Donovan is vice president of Research for Procurement and External Workforce at SAP.

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