Customer engagement is at a breaking point, and the most recent data proves it. Even as organizations accelerate their investment in AI, automation, and analytics, experiences often feel disconnected, impersonal, and reactive.

The problem is not the promise of AI. It’s the gap between intelligence in the system and connection in the moment. Customers are increasingly disengaging because intelligence is not being applied where it matters most.

Technology, particularly AI, has fundamentally changed what customers expect. They assume brands can recognize them across channels, understand context in real time, and anticipate their needs. When that doesn’t happen, the miss feels less like oversight and more like indifference. Timing is off. Service lacks continuity, and personalization stops at the surface, despite all the data behind it.

While many enterprises are trapped in siloed systems and disconnected data, consumer expectations are growing. Brands that don’t deliver the expected experiences are quickly abandoned.

In addition, global socioeconomic factors are increasing rapidly and unpredictably, challenging bottom lines and making customer loyalty more critical than ever—at a time when consumers are less loyal than ever. 

When economies falter, companies usually take one of two approaches. Some hunker down, cut costs and staff, and hope to survive. Others zero-in on differentiators like CX to drive growth and boost profitability.

The importance of CX for key metrics like churn, retention, loyalty, new sales, and competitive differentiation is well-established, so not investing in customer experience could be considered akin to saying you are willing to let those mission-critical metrics falter.

The following 15 takeouts from SAP’s 2026 Global Engagement Index Report highlight some of the most common CX pitfalls and opportunities.

1. 82% of consumers say a brand has disappointed them

Modern customers do not go quietly into the bad experience night. A whopping 82% of consumers say a brand has disappointed them, even when the product itself meets their needs. The issue isn’t the product or service; it’s the experience of purchasing and post-purchase care.

This is the essence of the “Engagement Divide”: the distance between what customers expect in the moments that matter, and what brands are actually delivering.

2. 60% do not pay attention to brands anymore and 48% care more about experience

Consumer attention in a difficult economy has shifted from logos and taglines to experiences that feel useful, contextual, and personal. So, what’s a brand to do when 60% of consumers say they simply don’t pay attention to brands and 48% care more about the experience than the product?

This is where CX outcomes become clear: engagement is no longer about shouting louder; it’s about showing up better and building experiences powered by unified data and intelligent orchestration.

3. Left unread: only 16% of customers skim email headlines, while 29% read one or two sentences

Consumer behavior in the inbox shows just how fragile engagement is:

• Most consumers only read the subject line
• Others will read one to two sentences before deciding whether to delete or engage further

Combined with the fact that 58% of consumers think most marketing emails they receive aren’t relevant, brands are staring down a massive relevancy problem. Sending more emails into the engagement abyss doesn’t solve this problem, but gaining a holistic understanding of your customers as individuals does.

4. 37% do not think brands personalize to their needs

For well over a decade we’ve been talking about the importance of personalization, but today 37% of consumers believe brands don’t personalize engagements to their needs. Surface-level personalization—names in subject lines, basic segmentation—is no longer enough.

This aligns with our assessment that 79% of companies have low or moderate CEM scores, meaning teams can access portions of shared data and deliver basic personalization, but coordination across marketing, sales, service, commerce, and product teams remains limited. Experiences often feel disconnected, forcing brands to rely on short-term tactics rather than building deeper relationships.

Consumers expect real-time, behavior-driven personalization based on context, intent, and history, not just boiler-plate persona buckets. Customers can see and feel investments in personalization and it matters.

5. 46% say customer service feels too impersonal, while 41% believe brands do not understand them as a person

Considering how much data brands collect, it’s striking that nearly half of consumers (46%) say customer service feels too impersonal.

Customers are asking a simple, and valid, question: “If you have all this information about me, why isn’t my experience better?” When data doesn’t translate into empathy and action, it starts to feel like surveillance, not service.

With 46% of consumers saying service isn’t personal, it should be no surprise that a nearly equal amount (41%) believe that brands don’t understand them as a person. However, 34% agree that AI can help brands better understand them and what matters most to them.

This presents brands with a real-time opportunity: use AI and data to close the perception gap. Instead of just predicting purchases, enterprises should also be anticipating customer needs and reducing friction.

6. 78% of brands say they deliver seamless cross-channel engagement, consumers disagree

Seventy-eight percent of brands say their engagement strategies offer seamless multichannel experiences with glowing outcomes like increased CLV, retention, and advocacy, but consumers are simultaneously reporting little emotional connection and frequent disappointment. In fact, 44% say that brand interactions feel less personal and more generic than ever before.

The takeaway: internal dashboards can create a false sense of success if not tied directly to real customer sentiment and behavioral signals across channels.

7. 54% of enterprises cannot access and use real-time data, and 66% still rely on third-party data

Fifty-four percent of enterprises can’t access and use real-time data. On top of that, 60% suffer from “dark data,” which is information that’s collected but not used throughout the customer journey.

Without real-time, connected data, brands are mostly flying blind. AI, personalization, and omnichannel orchestration don’t fail because the ideas or execution are wrong; they fail because the foundations are.

Although privacy regulations and legislation are increasing while third-party cookies decline, a majority (66%) of enterprises are still heavily reliant on third-party data. Simultaneously, 55% say their data is too unstructured to use effectively.

The lethal combination of overreliance on external data plus underutilized internal data keeps brands from building strong, first-party relationships rooted in trust and value.

8. 78% of brands say AI is essential for customer retention in 2026

AI is everywhere, and 78% of brands view AI as critical to retaining customers in 2026. However, 66% report they can’t use AI to optimize campaign performance in practice, while many also note they can’t utilize real‑time AI optimization in day‑to‑day campaigns.

A quick translation of the above stats: an AI strategy is crucial, but execution is lagging because of fragmented systems, poor data quality, and integration issues.

9. Only 30% share engagement data with a CX or CRM platform

Despite the collective agreement that a comprehensive customer profile is important, only 30% of brands share their customer engagement data within a CX or CRM platform. This means that most brands are attempting to deliver personalized experiences without having a unified engagement core.

If engagement data lives in campaign tools, service systems, commerce platforms, and ERP, but never gets connected via CX or CRM, customers will feel every fracture along their journey.

10. 30% of consumers have used AI agents that act on their behalf

AI is not just an enterprise capability; it’s also a customer behavior. Thirty percent of consumers say they’ve used AI agents to make decisions and act on their behalf when buying from brands.

This is a game-changer when it comes to engagement. Brands are now engaging not only with humans, but also with AI buyers that ruthlessly and continuously optimize for relevance and value. If your systems can’t keep pace, AI will select your competitor whose systems are operationalized for success.

11. When it comes to customer engagement maturity, 79% of brands have yet to integrate data, systems, and teams across their business; only two in five decision-makers see their departments as actually coordinated

The Customer Engagement Maturity (CEM) scoring model assesses how well brands align people, processes, and technology to deliver cohesive, intelligent experiences. Looking at the SAP Engagement Maturity Index:

• 16% of brands reside at low maturity
• 63% sit in the moderate middle
• 21% have high maturity

Despite year-over-year progress, most organizations are stuck in developing or evolving mode, able to execute campaigns but not orchestrate truly connected, enterprise-wide engagement. And leaders agree, with only two in five decision makers believing there is effective collaboration across departments.

12. Just 21% of brands are high-maturity, and they are gaining ground against their competition

High-maturity brands rise above the competition because they connect data and intelligence across marketing, service, sales, commerce, and operations. They use AI and automation to deliver personalized, omnichannel engagement in real-time, at scale.

And the maturity gap is becoming a performance gap. As top performers turn real-time intelligence into growth, the cost of competing with them rises for everyone else.

13. Personalized means personal: 58% of consumers respond positively to localized content

Personalization is more than a word or industry term. It means actually understanding and empathizing with your customer, including their regional traditions and social norms.

When engagement is done right, consumers respond:

• 63% say their favorite brand delivers seamless, connected experiences across mobile, web, and in-store
• 58% value localized content and product recommendations
• 55% appreciate highly personalized content
• 50% believe their favorite brand uses data to make interactions better

Customers aren’t against data or AI at heart. However, they are opposed to wasted data collection and bad experiences. It’s the job of brands to provide a great CX. If that job isn’t taken seriously, you can bet that other brands are willing to roll up their sleeves to fill the gap.

14. 77% of businesses plan to invest in AI-powered engagement in 2026

When it comes to the future state, 77% of businesses plan to invest in AI-powered customer engagement in 2026, and 76% are investing in omnichannel engagement technologies. At the same time, 29% say their top priority is connecting customer and stakeholder data across marketing, sales, service, commerce, and ERP systems.

The signal is clear: investment alone won’t close the Engagement Divide. The winners will be the brands that invest in connection—of data, teams, and systems—not just in tools.

15. 15% say seamless integration will be the biggest driver of success

Lastly, and possibly most importantly, 15% of businesses believe seamless integration of engagement systems will be the single biggest driver of success. While that may sound like a small number, it captures a critical strategic shift: engagement is no longer a marketing problem or a channel problem. It’s an enterprise discipline that depends on unified data, coordinated teams, and embedded AI.

Artificial intelligence provides an evolving service for businesses. Employing cloud-based systems that can store, analyze, and route data will be the differentiator for brands in the marketplace.

Loyalty is transactional, and driven by great CX and a connected enterprise

Digital engagement has raised the bar when it comes to customer expectations, with more demands and a plethora of competitive choices if a brand doesn’t deliver.

It’s not a big leap to state that better customer experiences increase customer loyalty, which in turn leads to more purchases, augmented product utilization, and increased brand affinity and sentiment. And let’s not forget that an enhanced CLV lowers customer acquisition costs.

After all, loyalty is transactional and forged by the experiences customers encounter. In my conversations with customers across the globe, it’s clear that only the brands with CX truly at the heart of their operations will retain and grow their customer bases in the enterprises of the future.

That ambition relies on a technology foundation that can consistently deliver those experiences at scale. For British-founded luxury fragrance brand Molton Brown, moving from legacy systems to SAP Commerce Cloud provided a high‑performance platform built for peak‑season resilience and continuous innovation. The impact was immediate: 100% uptime during peak trading, even as volumes surged to one order every three seconds during major events.

This kind of reliability is increasingly critical as the moments that shape experience and loyalty expand beyond owned channels. As product discovery shifts to social platforms and AI‑powered assistants, consistent content and availability help the brand remain visible and trusted wherever customers engage. SAP’s evolving agentic commerce innovations are designed for this reality, keeping products discoverable, credible, and actionable across both human and AI interactions.

Ultimately, technology and AI are not the goal—the experience is. The brands that succeed will be the ones that use AI to show up more human, not less, turning insight into relevance and automation into trust.

The future of CX is for companies that operationalize intelligence across the enterprise—connecting data, systems, and teams so AI can orchestrate experiences, not just analyze them.

Manos Raptopoulos is global president of Customer Success Europe, APAC, Middle East & Africa, and a member of the Extended Board SAP SE.

Manufacturing is entering a decisive moment. Rising costs, intensifying global competition, expanding regulatory requirements, and the rapid acceleration of agentic artificial intelligence are reshaping how products are designed, planned, produced, delivered, and serviced. Volatility is no longer an exception; it is the operating environment.

To succeed, manufacturers need more than incremental improvements or siloed optimizations. They need to orchestrate their operations end to end with connected processes and trusted data, so they can respond faster to change, operate more efficiently, remain compliant, and continue to grow—even as disruption is constant.

At Hannover Messe 2026, the world’s leading stage for industrial transformation, SAP will introduce a new set of AI‑powered manufacturing and supply chain innovations. These innovations help companies ensure business continuity by orchestrating people, processes, and technology across their extended enterprise, turning volatility into an opportunity for resilience, efficiency, and customer impact.

From AI insight to AI in execution

For years, manufacturers have invested in analytics and dashboards to improve visibility. But visibility alone does not prevent disruption. What’s required now is AI embedded directly into core business processes, where intelligence can analyze alerts, reason over business impact, and provide real-time solutions to resolve issues. With agentic AI, companies are now able to go a step further: automating the right actions for the best outcomes, with humans remaining in the loop wherever critical decisions are required.

SAP is operationalizing AI at industrial scale by embedding AI agents directly into supply chain and manufacturing workflows and contextualizing them with trusted enterprise and network data. Built on harmonized industrial, transactional, and network data, these agents can move beyond analysis to real‑time prediction and execution, working to deliver resilience, regulatory readiness, and measurable customer impact from day one. Creating tangible ROI is what matters most—whether by reducing unplanned downtimes, scrap, and rework, or by increasing quality and ultimately production output.

Orchestrating the supply chain end to end with AI

At the center of SAP’s focus at Hannover Messe is end-to-end supply chain orchestration with AI.

SAP helps manufacturers connect processes and data not only across internal teams, but also across company boundaries—with suppliers, logistics partners, and service providers. By using AI agents to connect design, planning, procurement, manufacturing, logistics, service, and asset management—and by integrating seamlessly with ERP and line-of-business systems—SAP helps break down silos that slow decision-making and increase operational risk.

This new agentic orchestration is powered and governed by a portfolio of intelligent applications that act, not just analyze, enabling faster, more coordinated responses without sacrificing quality, control, or growth.

New AI agents redefining planning, service, and operations

At Hannover Messe 2026, SAP will showcase AI agents that help manufacturers and operators reduce time to value, stabilize operations, and improve service levels amid ongoing disruption. As a precursor to broader announcements planned for SAP Sapphire, these agents demonstrate how agentic AI delivers practical benefits across all supply chain domains. Here are a few examples:

Manufacturing

• Production Master Data Agent helps automate and optimize the creation and maintenance of production master data. By leveraging the bill of materials, the agent can generate production routings—including operations and work centers—and help ensure components are correctly assigned across the production process. This helps reduce manual effort, accelerate production setup, and keep production data accurate as requirements change. General availability is planned for Q2 2026.
• Production Planning and Operations Agent enables planners to release production orders using natural language while automatically validating material availability, capacity, and scheduling constraints. Joule provides recommendations—such as alternative components or rescheduling options—that planners can review and approve, reducing manual work and keeping production aligned with real‑world conditions. General availability is planned for Q2 2026.

Assets & services

• Field Service Dispatcher Agent can improve service responsiveness and asset uptime by dispatching the right technician based on skills, location, asset condition, and priority—driving faster resolution and better workforce utilization. General availability is planned for Q2 2026.
• Alert Processing Agent can enrich operational alerts using past incidents, resolutions, and contextual signals and recommend clear, data‑driven actions to help teams resolve issues faster and improve operational reliability. General availability is planned for Q3 2026.
• Asset Health Agent analyzes time‑series health indicators to assess and summarize the current and projected health of individual and multiple technical objects. By forecasting when assets are likely to become critical and alerting users in real time, the agent supports condition‑based maintenance and helps minimize downtime while ensuring asset availability. General availability is planned for Q3 2026.

AI agents advancing logistics execution

• Material Reservation Agent helps ensure materials are available when and where needed by automating reservation creation and maintenance based on business rules—reducing delays, improving inventory accuracy, and optimizing working capital. General availability is planned for Q2 2026.
• Outbound Task Orchestration Agent can protect customer service levels by detecting and resolving picking and packing issues in real time, orchestrating corrective actions to support on‑time, accurate delivery. General availability is planned for Q2 2026.

Aligning workforce, logistics, and assets in real time

Operational resilience also depends on synchronizing people with all other resources as conditions change.

With SAP SuccessFactors Workforce Scheduling, skills, certifications, availability, and labor rules are aligned with real-time operational demand so workforce plans can adjust automatically as production changes.

In logistics, SAP S/4HANA Cloud Public Edition, AI‑assisted backorder processing, together with the new SAP Logistics Management solution, helps organizations reduce transportation costs, accelerate warehouse execution, and improve delivery performance. Using conversational interaction with Joule, order managers can prioritize fulfillment while automatically accounting for availability and scheduling constraints.

Asset and quality operations also benefit from embedded intelligence. AI-assisted anomaly detection and alert processing in SAP Asset Performance Management helps teams identify risks earlier, prioritize actions, and reduce unplanned downtime. In parallel, SAP Document AI can automate the processing of incoming quality certificates, improving throughput, data quality, and compliance at scale.

Regulatory readiness and what’s next

As regulatory requirements tighten, SAP is expanding support for Digital Product Passports as part of SAP Business Network, aligned with the EU’s Ecodesign for Sustainable Products Regulation (ESPR). These capabilities help manufacturers create ESPR‑ready product records capturing environmental impact, material composition, repairability, and recyclability data. General availability is planned for Q2 2026.

Expanded SAP Business Network capabilities also deliver built‑in e‑invoicing compliance and data-residency support, enabling secure partner collaboration, synchronized logistics, and improved delivery performance across global networks.

See it live at Hannover Messe 2026

Taken together, these innovations reflect a shift from reactive management to intelligent execution—where AI is embedded directly into the processes that keep manufacturing and supply chains running today while laying the foundation for the next wave of innovation that will be unveiled at SAP Sapphire.

Visit SAP at booth F08 in Hall 15 at Hannover Messe 2026, April 20–24, to see how AI-infused orchestration, embedded AI agents, and end‑to‑end supply chain applications are redefining manufacturing.

Dominik Metzger is president and chief product officer for SAP Supply Chain Management.

HANOVER — SAP SE (NYSE: SAP) and machine and plant manufacturer Uhlmann today announced an integrated approach that embeds digital production environments, open data ecosystems and SAP Business AI directly into operational processes.

The announcement was made at HANNOVER MESSE 2026, where they showcased PacXplorer, a high-tech packaging machine from Uhlmann that serves as both an industrial demonstrator and a development platform.

PacXplorer: Connected Production in Industrial Practice

Developed through collaboration within Factory‑X, the PacXplorer brings together digital twins, condition monitoring, smart services and interoperable production solutions within a collaborative data ecosystem. Factory‑X is a lighthouse project funded by the German Federal Ministry for Economic Affairs and Energy as part of the Manufacturing‑X initiative. Its objective is to establish a decentralized data space for the capital goods industry, enabling secure and interoperable data exchange across companies and industries for equipment manufacturers and operators alike.

The machine is integrated into SAP system landscapes and operated live. It demonstrates how industrial data can be used in a sovereign, interoperable and cross‑company manner not as a theoretical model, but in real production operations. This creates transparency regarding asset condition, utilization and performance while laying the foundation for new data‑driven services.

Service as a Key to Resilience

The value of this approach becomes particularly clear in service operations. Where production, data, and operations are tightly interconnected, service plays a decisive role in ensuring asset availability, productivity, and stable customer relationships. One often underestimated lever is spare parts service: delays lead directly to downtime and economic losses, especially in volatile market and supply situations. At the same time, these processes remain heavily manual in many industrial companies.

SAP and Uhlmann are deliberately advancing the further development of this area. An AI‑supported process assists throughout the entire workflow from handling incoming inquiries and clarifying missing information to identifying the correct spare part and generating quotations. The approach integrates into existing SAP service and sales processes and is closely aligned with real‑world business operations. The objective is fast, reliable and scalable customer service.

“Today, industry is less concerned with cost optimization than with decision‑making under uncertainty,” says Dominik Metzger, President and Chief Product Officer for SAP Supply Chain Management at SAP. “With SAP Business AI and integrated production and service solutions, we move decision‑making directly into business processes. This allows companies to identify risks early, respond with greater flexibility and remain operational even under unstable conditions.”

Rethinking Value Creation Together

The collaboration between SAP and Uhlmann illustrates a fundamental shift in industry: resilience is not achieved through additional buffers, but through better, faster and more-connected decisions across the entire value chain. Companies that manage their production and service processes in a data‑driven way can respond more flexibly to change and secure their competitiveness over the long term.

Beyond HANNOVER MESSE, SAP and Uhlmann will continue their innovation partnership. Following the event, the PacXplorer will be operated at the SAP S.Factory in Walldorf, serving as a platform for customers, partners and co‑innovation to continuously advancing industrial transformation.

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Media Contact:
Dana Roesiger, +49 6227 7 63900, dana.roesiger@sap.com, CET
SAP Press Room; press@sap.com

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.
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Today, educators across disciplines face a common challenge: preparing students with the analytical skills employers increasingly demand.

According to the World Economic Forum’s Future of Jobs Report, analytical thinking ranks as the top sought-after skill in the job market. Yet traditional teaching often struggles to connect theory with practice in a way that truly engages students.

It’s not a shortage of content or tools; rather, it is a gap in relevance and inspiration that leaves students disengaged from the very skills that could define their careers. Learning needs to be anchored in real-world data, meaningful contexts, and hands-on experience that sparks curiosity and excitement. The best learning doesn’t come from memorizing concepts, it comes from doing, especially when theory is tied to a topic that learners care about.

This is where Business Builders, in collaboration with the NHL, comes in.

We have created a new Business Builders game that brings hockey into the classroom—not just as a sport, but as a rich, real-world data environment for teaching analytics and critical thinking.

In this latest edition of games under the Business Builders umbrella, students take on the role of a hockey analyst responsible for identifying the factors that drive goal scoring using real NHL Game data.

“Hockey is fast, dynamic, and full of rich data, a perfect environment for teaching critical thinking,” said Brant Berglund, senior director of Coaching and GM Technology at the NHL. “Leveraging a strategic partnership with NHL, SAP, and HEC Montréal, we’ve created a pathway for universities to access approved NHL.com data for academic initiatives, without compromising the integrity of the League‘s data.”

Through our collaboration with the NHL, we provide a learning platform for educators that is full of authentic data students can relate to. The NHL generates just under 1.5 million data points per game, including about 120 shot attempts, 1,000 passes, and 5,000 puck touches—raw material for deep, practical analysis.

Business Builders can ignite an interest in STEM and help students build real data skills. The hockey-focused game was developed by the team at ERPsim Lab at HEC Montréal led by Prof. Pierre-Majorique Léger, as well as the support of academics from other universities. This reinforces a core principle of Business Builders: It is created by educators, for educators.

“When the question feels meaningful, learners lean in, stay focused, and keep pushing forward,” Léger explained. “For students in sport management or business management, real sport data can also elevate the learning experience. It adds context, complexity, and constraints that traditional teaching methods cannot provide. Students learn to judge what truly matters, justify their decisions, and manage trade-offs. This develops professional judgment, confidence in analytics, and the ability to communicate strategy and decisions clearly. These skills translate directly to real careers in sport management and business.”

Students explore questions such as:

• What sets top NHL scorers apart?
• Does shot angle affect scoring?
• Which NHL players lead in goals scored, and from what distances?
• Which shot speeds and shot types yield the highest goal conversion rates?

By analyzing these scenarios with SAP Analytics Cloud, students learn to interpret visualizations, tell compelling data stories, and sharpen their data-driven decision-making and critical-thinking skills.

For professors, the platform is equally powerful. Business Builders supports active learning at scale by enabling educators to manage and evaluate larger groups more efficiently while gaining visibility into student engagement. This makes grading easier, supports discussion-based learning, and helps instructors understand how students interact with data.

By introducing a modern, meaningful learning experience—far more dynamic than slides alone—professors bring real-world relevance into their classroom and elevate the impact of teaching.

SAP’s role in this collaboration reflects its broader commitment to education, skills development, and preparing students for the future workforce. In a rapidly changing world shaped by AI, data, and digital transformation, access to practical learning tools that build real competencies is essential. Through the SAP University Alliances program, SAP works with educational institutions around the world to help bridge the gap between academic theory and real-world practice.

“Access to business software and real data is essential for preparing students for the future,” said Dr. Katharina Schaefer, head of Academic Partnerships at SAP. “With free learning platforms like Business Builders, we empower educators to bring enterprise analytics into the classroom and help students develop the skills that are increasingly in demand across industries, and in a world where data and AI define the competitive advantage. Today’s learners need more than conceptual understanding; they need practical experience with real software and real data to build confidence and readiness for work life.”

One of the educators closely involved in shaping this new game is Prof. Olivier Caya from the University of Sherbrooke, who contributed his perspective as both a faculty member and practitioner.

“What makes this experience so powerful is that it all happens in SAP Analytics Cloud, the same solution used by thousands of organizations worldwide,” Caya said. “This creates a strong connection between what students do in the classroom and what they will encounter in professional practice. Students are not working with software detached from reality; they are developing skills with the same software used in real business environments.”

The result is a learning experience that is fun, interactive, and relevant. Educators can stand out with a state-of-the-art platform that connects passion with pedagogy, while students gain highly sought-after skills using real software from a global technology leader.

Business Builders is provided free of charge to educators and students and includes access to SAP Analytics Cloud. It is designed from beginner-friendly introductions to more advanced analytical challenges optimized for master’s-level courses.

After using Business Builders, students can deepen their analytical knowledge through access to SAP Learning Hub, student edition, a free learning platform that offers guided learning content, practice systems, and up to two SAP certification exam attempts per year, helping them to boost their career opportunities even further.

Business Builders is about connecting passion with education. Together with academic and industry partners, SAP is making analytical thinking tangible and memorable—empowering the workforce of tomorrow with the skills that matter most today.