WALLDORF — SAP SE (NYSE: SAP) today announced that it has adjusted the company’s non-financial key performance indicators (KPIs), which are a component of the Executive Board’s compensation.

With this, SAP also adjusts its non-financial guidance. The guidance for Women in Executive Roles will be replaced with the Business Health Culture Index (BHCI). SAP has measured and reported the BHCI, which is based on the results of the company’s employee engagement surveys, since 2009. In 2025, SAP expects a BHCI score in the range of 80% to 82%.

The other non-financial KPIs remain unchanged. In 2025, SAP continues to expect:

• A Customer Net Promoter Score of 12 to 16.
• The Employee Engagement Index to be in a range of 74% to 78%.
• To steadily decrease carbon emissions across the relevant value chain.

SAP remains committed to creating an inclusive workplace where all employees have equal opportunities, so that the company fully complies with the legal requirements in every country in which it operates.

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Daniel Reinhardt, +49 6227 7-40201, daniel.reinhardt@sap.com, CEST
SAP Press Room; press@sap.com

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For the 12^th consecutive year, SAP has been recognized as a Leader in the Gartner Magic Quadrant for Warehouse Management Systems (WMS). WMS vendors compete to address market demands like cost reduction, automation and robotics support, and cloud deployment. Gartner says that Leaders execute well against their current vision and are well positioned for tomorrow. A Gartner Magic Quadrant is a culmination of research in a specific market, giving you a wide-angle view of the relative positions of the market’s competitors.

SAP’s positioning as a Leader is based on our ability to execute and the completeness of our supply chain vision. We believe this recognition represents our ongoing commitment to developing best-in-class warehouse management technology that can help organizations withstand the ever-shifting landscape of logistics operations.

Building on strength

Every day, supply chain managers are tasked with adapting to rapidly evolving technology, unprecedented disruptions, and increasing demand for faster delivery. These challenges are driving shippers toward implementing intelligent and agile technologies that make them more flexible and responsive.

However, that’s not enough. Now, integrated logistics processes are the new standard—allowing businesses to automate, optimize, and improve productivity across their entire warehouse and logistics operation.

SAP Extended Warehouse Management (SAP EWM) is a flexible, modern application that helps businesses manage a high volume of goods and run sustainable, digitalized, and risk-resilient operations with cloud-based warehouse processes. From simple warehouses to high-volume and automated distribution facilities, SAP EWM can integrate supply chain logistics with warehouse and distribution processes, helping to deliver the visibility and control organizations need.

• Logistics process orchestration: SAP EWM offers integrations with SAP ERP Central Component (SAP ECC) and SAP S/4HANA and components like transportation management, global trade compliance, plant maintenance, and manufacturing integration capabilities. With harmonized data and business objects, organizations can have fewer silos between warehousing and transportation with advanced shipping and receiving (ASR) to manufacture and distribute products more efficiently.
• AI applications: SAP EWM offers AI and machine learning capabilities to help streamline warehouse operations, such as slotting to optimize storage and predictive labor demand planning to address the pressing challenges in executing warehouse operations that companies face due to labor shortages and increased order volumes.
• Robotic-powered smart warehousing: SAP EWM customers can quickly onboard multiple robotics vendors to enable collaborative and efficient warehouse task operations. Customers have a choice of specialized SAP partners on SAP Store for faster adoption of robots in their warehouses. This scalable integration offers flexibility and can ultimately drive innovation by helping to lower costs, increase accuracy, and enhance capacity.

Why companies choose SAP

Companies worldwide, across diverse industries, rely on SAP Extended Warehouse Management to help optimize their warehouse operations and enhance supply chain efficiency.

• The largest WMS customer base: With thousands of SAP EWM customers in 75 countries and 24 industries, our best-in-class deployment capabilities make us the preferred choice for businesses globally.
• Comprehensive ecosystem: Our offerings encompass implementation, consulting, insights, and various other functions, enabling SAP EWM customers to manage their warehouse operations seamlessly within the SAP environment. Customers can access additional extensions through SAP Store, and future releases will foster further integration within the larger SAP ecosystem.

Recent innovations in extended warehouse management innovations

The latest releases of SAP Extended Warehouse Management include several key benefits:

• Enhanced logistics process orchestration: Deep integration with SAP S/4HANA capabilities in transportation, production, and quality management
• AI-assisted warehouse operations: Streamlined processes through artificial intelligence
• Efficient goods management: Improved planning and execution of movement and storage processes
• Optimized warehouse automation: Better management of diverse automation landscapes
• Flexible deployment options: Cloud-based solutions for adaptable implementation
• Process optimization: Integration with SAP Signavio solutions for enhanced efficiency

These innovations can provide a comprehensive approach to modern warehouse management, combining advanced technology with practical operational improvements. 

Read the full Magic Quadrant report from Gartner and learn more about the capabilities of SAP Extended Warehouse Management.

Till Dengel is global head of Product Marketing for Logistics and Asset & Service Management at SAP.

Gartner does not endorse any vendor, product or service depicted in its research publications, and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions of Gartner’s research organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose.
GARTNER is a registered trademark and service mark of Gartner, Inc. and/or its affiliates in the U.S. and internationally, and MAGIC QUADRANT is a registered trademark of Gartner, Inc. and/or its affiliates and are used herein with permission. All rights reserved.

Today we can finally see the consumer version of what futurists, writers, and filmmakers have been conceptualizing for long: AI that can predict events and outcomes even before they happen. When Isaac Asimov foresaw cars with “robot brains,” he described a fictional technology that would fuel such an invention. Seven decades later, autonomous cars are a reality because of AI’s ability to analyze vast amounts of data from sensors, cameras, and other sources. And these proactive, predictive, and preventative capabilities of AI are equally applicable in almost any industry today, for example in healthcare with AI-powered wearables, retail with optimization of inventory for high-volume sales, or manufacturing with maintenance through anomaly detection.

When it comes to customer support, these capabilities are game-changing not only for current applications but also for future implications. The way businesses deliver support is improving every day, thanks to the rapidly evolving framework: technological breakthroughs, business innovations, and process agility. Here are six key methods that can transform the delivery of customer support.

1. Real-time monitoring

With AI-infused features in diagnostics, an electric car can detect potential malfunctions and schedule its own service appointment automatically, preventing issues like battery depletion or tire pressure drops before they become critical.

How does real-time monitoring play out in the world of business software? SAP Cloud ALM provides a feature-rich observability platform that can collect telemetry data, like metrics, logs, and traces, from applications and their supporting infrastructure, allowing support teams to review the health of these systems. By providing real-time analytics and a centralized dashboard, SAP Cloud ALM helps empower IT teams to quickly respond and fix issues, so the business remains operational with minimal interruptions. Additionally, the use of OpenTelemetry standardizes observability within a modern customer landscape.

“The SAP Cloud ALM solution has been instrumental for our IT operations. It offers real-time insights and seamless integration across all our enterprise applications, making everything run more smoothly. It’s like having a bird’s-eye view of our operations, ensuring efficiency and helping us stay proactive rather than reactive.”

Omprakash H, Senior Director, Blueprint Technologies Pvt. Ltd.

2. Proactive resolution

Customer feedback loops play an important role in improving products and services and refining customer relationships. Repeat requests, in customer and user feedback, help service providers identify critical needs and also prioritize features to be delivered.

For example, users within SAP Business Network and SAP Ariba solutions go to the help center for self-service or case assistance 10.8 times less than they did years ago. These drop-in, end-user support sessions are the result of features that have been built into the product, based on customer feedback.

AI-enabled outbreak detection is another significant process in proactive resolution that allows support teams to address unexpected increases in anomalies, customer complaints, or issues.

“We continuously identify the reasons for frequent customer demands and challenges from inquiries raised to SAP support. This allows SAP to proactively deliver the most impactful product changes before they become a challenge for more customers. This way, we improve our products while also focusing on key product capabilities used by our customers today.”

Alexey Ukrainsky, Solution Support Architect, SAP MCC

3. Predictive analytics

In the retail industry, predictive analytics is used effectively for proactive and preventative support. One prominent example is SAP’s holiday season readiness program, which helps position SAP as a front-runner in AI-driven, predictive, and proactive support solutions. With the goal of issue prevention at its core, the program can provide a comprehensive, 360-degree customer support profile, helping to accelerate issue detection and anticipate potential problems with AI-driven features like a virtual support assistant, resource prediction, web traffic prediction, a recommendation engine, case history analysis, issue correlation, and pattern recognition.

“During Cyber Week 2024, SAP’s holiday reason readiness program equipped our support and ops teams to achieve 100% uptime for our customers with the predictive, proactive, and bi-directional support model implemented by the program.”

Tarun Luthra, Head of Support, I&CX Solutions

4. Customer journey mapping

SAP Signavio solutions can help businesses visualize the end-to-end customer journey, tracking interactions across different touchpoints. This enables companies to identify areas of improvement in their customer support processes, leading to more personalized and effective interactions.

With the help of SAP Signavio Process Intelligence, SAP can successfully map support processes to help implement AI improvements for optimizing our services. The result: a 100% increase reported in customer value.

For example, a business that struggles with connecting customer experience data and operational data can take advantage of the SAP Signavio Journey-to-Process Analytics solution to help reduce time to insight and uncover anomalies and trends.

“The challenge in increasing our customer experience lies in the direct link between process and journey activities. I see SAP Signavio solutions as the perfect tools for consolidating these two perspectives to develop operational excellence in step with customer experience.”

Stefan Gammel, Business Process Consultant, Hilti Group

5. In-app support

Seamlessly integrating support features in a product, service, or system gives users easy access to directly request assistance within the interface, without needing to contact a support team or leave the platform. Built-In Support can include contextual, AI-assisted, self-service options like help application-specific documentation, troubleshooting tools, knowledge bases, and FAQs or real-time options like live chats with support engineers.

For example, WalkMe solutions and Built-In Support—layered over multiple applications in a business workflow—can provide real-time, proactive, in-app guidance to users, helping to significantly reduce the need for live assistance or support tickets.

“Context significantly enhances the quality of support. Built-In Support works like a pit stop at a racetrack. The repair crew is right where the action is. The interruption is brief and far less disruptive than taking your car to the workshop, ensuring a smoother return to your activities. In the context of your company, this helps you win your business race.” 

Wilhelm Jütte, Chief Product Owner, Customer Support, SAP

6. Proactive mindset

None of the tools and processes that we deploy to implement a proactive and preventative support strategy are sustainable if our teams are not tuned to a proactive mindset. I believe high-performing support teams deliver the best results with a combination of human-machine collaboration, in a culture that promotes a forward-thinking, outcome-driven, service-oriented, and data-driven mindset. 

At the end of the day, the best issue is the issue that we can prevent. Proactive and preventative support is not just about solving problems, but about creating peace of mind for end users, customers, partners, and support engineers so every customer receives custom care, even before they need help.

“Knowledge management within support is not just about enabling self-service through portals to deflect incoming tickets, but about eliminating the need to come to the support portal in the first place.”

Derek Matthews, Technical Support – Procurement Chief Innovation Officer, SAP

Stefan Steinle is executive vice president and head of Customer Support & Cloud Lifecycle Management at SAP.

Artificial intelligence (AI) has become the new catalyst of enterprise innovation. Yet, as AI becomes more embedded in core business processes, one thing is becoming clear: generic, out-of-the-box solutions alone cannot meet the complex, evolving demands of modern enterprises.

Customers don’t seek off-the-shelf AI, they seek outcomes. They demand solutions tailored to their industry, aligned with strategic goals, and built to drive real results.

That is where customer-specific AI solutions add depth — not just as a technical enhancement, but as a strategic lever to unlock transformative business value.

According to McKinsey’s State of AI 2024, 72 percent of companies use AI in at least one business function, but only 23 percent report a significant impact on their bottom line. Why? Because many AI projects lack the contextual depth to solve the real industry-specific challenges businesses face.

Similarly, a 2024 IDC study shows that while 80 percent of enterprise leaders plan to increase AI investments, nearly half say the absence of domain-tailored solutions is a barrier to ROI. While foundational AI models provide broad capabilities, true business value comes from solutions tailored to each customer. These targeted applications ensure that innovation aligns with specific regulatory demands, operational realities, and customer requirements.

These custom solutions leverage proprietary data; they are designed for specific business processes and are co-developed with stakeholders who understand the operational heartbeat of the enterprise. The result is measurable business impact, as well as faster deployment and better performance.

At SAP, we see AI’s true potential in enhancing human decisions, simplifying complexity, and transforming customer experiences. But this potential is only realized when AI is deeply grounded in each customer’s business context. That is why our approach to customer-specific AI is built on three core principles:

• Context-rich insights: With unmatched access to enterprise data from across industries and business functions, SAP is uniquely positioned to deliver AI that understands how real businesses run.
• Trust and transparency: From model explainability to data privacy, AI from SAP is built on a foundation of enterprise-grade governance and responsible AI standards.
• Co-innovation at scale: SAP partners closely with customers to develop differentiated AI solutions that solve their unique challenges.

Real outcomes with real customers

To address the complexity of managing nearly a million annual invoices across more than 40,000 contracts, Accenture partnered with SAP to simplify its fragmented, manual billing process. Using SAP Business Technology Platform and generative AI, the company built an intuitive, compliant application that empowers account executives to use AI for specific rate cards and contract terms, managing invoicing independently, and reducing reliance on specialist teams. The result was faster, more accurate billing, a better user experience, and major time savings, freeing commercial teams to focus on clients. By year-end, billing efficiency is expected to improve by 32 percent, with setup times cut in half and manual work replaced by an intuitive, automated platform.

Similarly, a global chemical and consumer goods company recently partnered with SAP to embed AI into its dispute management process, automating document indexing and classification. This customer-specific AI solution reduced manual effort, sped up resolution times, and boosted user productivity, showing how business-specific AI can streamline workflows and elevate customer experience at scale. The result was efficiency gains of up to 1,000 hours a month, reduced manual effort by over 500 hours/month, and improved accuracy and faster turnaround time for document-driven workflows.

These examples highlight a clear trend: customers want to co-create AI tailored to their needs, not just adopt a one-size-fits-all solution. Customer-specific AI solutions empower them to embed intelligence into the very workflows that define their competitive advantage, whether it’s last-mile logistics in retail, claims processing in insurance, or energy optimization in utilities.

In the coming years, enterprises will not differentiate by whether they use AI, but by how effectively they align AI to their business. Customer-specific AI solutions make this alignment possible. They bridge the gap between technology potential and business reality. They transform AI from a generic tool into a strategic advantage, enabling businesses to move faster, think smarter, and lead with purpose.

As more organizations navigate the complexities of digital transformation, those that embed AI into the heart of their unique processes will be the ones to redefine what is possible.

The future belongs to businesses that don’t just adopt AI, but shape it to fit their vision, values, and velocity.

Thomas Saueressig is a member of the Executive Board of SAP SE, Customer Services & Delivery.
Sindhu Gangadharan is head of Customer Innovation Services at SAP and managing director of SAP Labs India.