Most organizations are not struggling to invest in AI. They are struggling to see a return on it. Budgets have been committed, projects launched, and expectations set—yet for the majority, the business case remains unproven.

This is the context in which SAP redesigned the SAP Services and Support portfolio eight months ago. It’s built around a simple premise: transformation isn’t a milestone but a continuous journey, and every organization deserves a partner to guide it at every stage.

The response from customers was clear. Success plans from SAP became the default way organizations engage with SAP’s cloud portfolio, from early cloud deployments to complex, multi-solution transformations powered by SAP Business AI.

As of today, November 2, 2026, Max Success Plan—SAP’s most strategic level of engagement—is available to every customer, whether they choose to work with SAP directly or through a trusted partner. For those working through a partner, it is now accessible via Cloud Choice (CCFlex) and Resell (VAR), with managed service providers coming soon.

With this, success plans are open to every SAP customer, regardless of how they engage with SAP. Foundational Success Plan has been included in every SAP cloud subscription from day one. Advanced Success Plan has long been available across SAP’s full customer base, both directly and through partners. Max Success Plan now helps close the loop—the same complete, tiered path to value that SAP has offered directly since February 2026 is now available to every customer, regardless of how they choose to engage with SAP.  

The evidence: why guidance determines who wins with AI

The data on this is stark. RAND Corporation found that 80% of enterprise AI initiatives fail to deliver their intended business value—twice the failure rate of standard IT projects. S&P Global Market Intelligence found that 42% of companies abandoned most of their AI initiatives in 2025, up from 17% the year before. And MIT’s widely cited GenAI Divide report found that 95% of organizations investing in generative AI see zero measurable return on their P&L, while that same research found that pairing AI adoption with an experienced external partner roughly doubles deployment success, 66% versus 33% for internal-only efforts.

The differentiator isn’t the technology stack. It’s guided execution.

This is exactly the gap success plans were built to close. They are SAP’s cloud engagement model: the structured, continuous guidance customers have been asking for, helping organizations adopt the latest innovations and stay ready for whatever comes next. Foundational Success Plan, Advanced Success Plan, and Max Success Plan can scale that guidance to match a customer’s complexity and AI ambition. And Max Success Plan, as SAP’s most strategic level of engagement, can be that experienced external partner the research points to, built directly into the SAP relationship, not bolted on beside it.

The proof: what success plans actually deliver

IDC’s research found that organizations using Foundational Success Plan achieved $4.9 million in average annual benefits, 28% less time spent on incident management, and a 39% reduction in impactful security breaches*. Advanced Success Plan customers saw a 381% three-year ROI, $3.4 million in annual average benefits, and 19% quicker time to market for new features and functions**. And Max Success Plan customers achieved a 521% three-year ROI, $4.4 million in end-user productivity gains per organization per year, and a 24% improvement in business processes***.

Guidance that pays for itself—at every level. Full findings for each success plan are available on sap.com.

One clear goal: consistent guidance, regardless of how you reach SAP

When SAP introduced the success plans, the goal was clear: give every SAP cloud customer a clear, predictable path to value, one plan included with every subscription and two additional that scale with ambition. What became apparent almost immediately was how many of those customers already reach SAP through a partner—and how natural the next question was: why should the path to value look any different because of that?

Extending Max Success Plan through partner channels closes a gap that had nothing to do with the value of the offering and everything to do with how customers happened to reach it. That relationship should no longer determine the level of guidance available.

“As AI raises the stakes for successful transformation, customers need consistent, strategic guidance regardless of how they engage with SAP. By making Max Success Plan available through our partner channels, we are expanding access to the expertise and support customers need to turn innovation into lasting business value.”

Thomas Saueressig, Chief Customer Officer and Member of the Executive Board of SAP SE

Max Success Plan: strategic guidance, built into every engagement

Max Success Plan is SAP’s most comprehensive success plan, designed for organizations navigating complex transformations, scaling SAP Business AI, or operating in fast-moving business environments. It combines strategic expertise, proactive guidance, and hands-on support to help customers continuously evolve and maximize the value of their SAP investments.

Key capabilities include:

• A designated success plan manager who helps orchestrate the end-to-end customer experience with deep knowledge of the customer’s business and SAP landscape
• Cross-solution process improvement and transformation advisory that can connect strategy to execution across the full SAP landscape
• Tailored AI use case adoption, including prototype development to validate ideas and de-risk investment before scaling
• Everything in the Advanced and Foundational Success Plans, like guided transformation, proactive risk detection, and mission-critical support, so nothing is lost, only added to

Max Success Plan can be directly integrated into how customers run and evolve their SAP solutions. It can be continuous, proactive, and tightly connected to the product road map customers are already investing in. That holds true whether a customer reaches SAP through a partner or engages directly.

“For many of our customers, the partner relationship is the primary one. Extending Max Success Plan into Cloud Choice and Resell means our partners can now sell that same strategic service offering themselves.”

Karl Fahrbach, Chief Partner Officer at SAP

Available now: growing to meet you where you are

Max Success Plan is now available to organizations working with Cloud Choice (CCFlex) or Resell (VAR) partners. Managed service provider (MSP) is currently piloting with a few customers, allowing MSP partners to align their delivery models and prepare for broader availability.

This phased approach reflects a key insight since February: the organizations that get the most from success plans are those that adopt at a pace matching their own readiness.

As SAP builds toward the Autonomous Enterprise, where AI increasingly supports execution while people set the direction and hold accountability, the guidance layer around that technology matters as much as the technology itself.  Expanding Max Success Plan across partner models gives more customers access to the strategic guidance they need to adopt innovation, navigate continuous transformation, and realize greater value from their SAP investments.

The guidance is in place. The next step is yours.

The difference between an AI initiative that transforms a business and one that quietly stalls is rarely the technology. It is the guidance around it—the expertise that connects a product roadmap to a business outcome and keeps that connection strong as both evolve.

That guidance is now available to every SAP customer, however they choose to reach us. Success plans remain the starting point for any SAP cloud engagement, for customers mapping out their next transformation and for the partners they rely on to get there.

Ready to take the next step? Explore success plans to find the level of engagement that best fits your organization. Partners can explore the success plans within the partner portal.

Ville Leivo is global head of Cloud Success and Premium Portfolio at SAP.

Ryseff, J. and Narayanan, A. Why AI Projects Fail and How They Can Succeed. RAND Corporation, 2025. rand.org/pubs/research_reports/RRA2680-1.html
S&P Global Market Intelligence. Generative AI Shows Rapid Growth but Yields Mixed Results. Voice of the Enterprise: AI & Machine Learning, October 2025. spglobal.com/market-intelligence
Challapally, A., Pease, C., Raskar, R., and Chari, P. The GenAI Divide: State of AI in Business 2025. MIT NANDA (Project NANDA, MIT Media Lab), July 2025. nanda.media.mit.edu/ai_report_2025.pdf

*IDC White Paper, sponsored by SAP, The Business Value of Using SAP’s Foundational Success Plan, doc ##US54140525-BVWP, April 2026
**IDC White Paper, sponsored by SAP, The Business Value of Using SAP’s Advanced Success Plan, doc #US54296426-BVWP, April 2026
***IDC White Paper, sponsored by SAP, The Business Value of Using SAP’s Max Success Plan, doc #US54437226-BVWP, May 2026

The Germany-based logistics company DACHSER has set itself an ambitious goal: to become the world’s most digitally integrated logistics service provider by 2030, seamlessly aligning its resources, experience, and modern digital operational capabilities with the needs of its customers, employees, and partners.

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

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

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

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

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

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

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

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

SAP S/4HANA transformation

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

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

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

One way to look at AI in the context of the Autonomous Enterprise is how sophisticated AI models are, their speed, reasoning capabilities, or ability to automate complex tasks. But that’s looking at the story from the inside out.

The real measure of an Autonomous Enterprise isn’t how intelligent its AI is. When you add the customer to the picture, the conversation shifts to making their lives easier, helping them achieve their business goals, and earning their trust and confidence.

This customer-centric perspective and the possibilities of AI reshape how organizations think about work.

One of our life sciences customers is already putting this vision into practice. Every day, the company receives tens of thousands of customer emails across sales, service, and support. Each message must be reviewed, categorized, prioritized, and routed to the right team, often requiring employees to navigate a patchwork of legacy systems, disconnected applications, and manual workflows. As customer expectations continue to rise, simply adding more people to keep pace is no longer a sustainable strategy. By enabling intelligent agents to coordinate work across complex business processes, the company is transforming how customer requests are handled while improving both operational efficiency and customer experience.

This is more than another wave of process automation. It represents the beginning of the Autonomous Enterprise, where enterprise operations become more efficient without sacrificing quality, governance, or control.

Powered by agentic AI, intelligent agents are becoming active participants in executing business processes, collaborating with one another, and driving measurable business outcomes. Their defining characteristic is not just intelligence. They act autonomously within defined guardrails while humans remain accountable for the decisions they make, the actions they authorize, and the business outcomes they deliver.

With that, entire operating models begin to evolve as intelligent agents handle routine coordination, accelerate decision-making, and enable the business to respond with greater speed and resilience. In a volatile environment where customer expectations and market dynamics continue to accelerate, the Autonomous Enterprise is emerging not simply as a technology strategy, but as a new operating model for delivering better outcomes for customers and business alike.

The evolution of service delivery in the AI era

AI is fundamentally reshaping how enterprise software services are delivered and consumed. Service delivery is evolving to proactive, AI-powered operations where intelligent agents automate routine tasks, predict and prevent issues, accelerate incident resolution, and continuously optimize system performance. This enables service delivery organizations to scale efficiently, improve customer experience, and shift human expertise toward higher-value innovation and strategic customer engagement.

The shift to agentic AI makes AI fluency a foundational skill for becoming more productive and efficient in day-to-day activities.  Effective collaboration with intelligent agents can streamline routine tasks, generate higher-quality insights, and free up time for higher-value activities while facilitating innovation-focused customer advisory and strategic decision-making.

Rather than replacing expertise, agentic AI augments teams by enabling faster decisions, automating routine work, and delivering better customer outcomes. Key areas include:

• Customer engagement readiness: AI consolidates customer context, surfaces key insights and risks, and recommends next best actions to help teams prepare faster and engage more effectively.
• Intelligent service delivery processes: AI automates repetitive tasks, orchestrates workflows, predicts issues, and accelerates resolution, enabling more proactive and efficient service delivery.
• Connected Intelligence: AI captures expertise, recommends relevant knowledge, identifies patterns across engagements, and continuously optimizes delivery processes and best practices.

Together, these capabilities enable us to work alongside our customers as their partners, anticipating needs, tackling their challenges, and delivering intelligent, outcome-focused services.

How customers adopt AI as they become autonomous enterprises

For customers, service delivery becomes more proactive, personalized, and outcome-driven. Technical challenges and incidents are no longer assessed solely through a technical lens. They are evaluated based on their impact on business outcomes, customer experience, operational resiliency, and organizational performance.

Instead of reacting to incidents after they occur, AI agents continuously monitor environments, predict potential issues, autonomously resolve common problems, and provide faster, more intelligent support, resulting in higher service reliability, quicker resolution times, and a more seamless customer experience. This shift enables organizations to prioritize response and remediation according to business criticality rather than technical severity alone.

One of our manufacturing customers leverages Joule Agent to continuously monitor ERP system health, identify root causes of issues, recommend corrective actions, and autonomously execute approved resolutions. The solution delivers approximately 3,000 hours of annual effort savings, minimizes unplanned business downtime, and enables standardized, 24/7 AI-powered reporting that aligns with the firm’s enterprise reporting requirements.

Customers are ready to scale AI across their organizations, but they expect transparency, governance, and clarity on where AI acts autonomously and where human judgment remains essential. While enthusiasm for AI’s potential remains strong, customers are seeking clear insights into where AI’s potential lies within their organization. Three themes consistently emerge:

• Measurable ROI: Customers expect AI to deliver a measurable impact beyond innovation. Through our success plans, SAP partners with customers to define success metrics, align AI initiatives to business priorities, and drive outcomes across execution speed, productivity, experience, and operational resilience.
• End-to-end use cases: Point solutions optimize individual tasks, but customers seek enterprise-wide value. Cross-functional workflows such as claims processing and procure-to-pay, where multiple AI agents collaborate, deliver far greater impact than isolated copilots. One of our American customers leverages AI for proactive monitoring, AI-powered root cause analysis, automated exception resolution, and autonomous execution of approved actions, accelerating issue resolution while minimizing manual effort. With up to 80% gains in operational efficiency and improved on-time vendor payment by 25%, the company streamlined its business processes and enhanced supplier collaboration.
• Governance is a business imperative: AI governance is no longer an IT agenda. It became a strategic imperative as business leaders now shape AI decisions, recognizing that trust is the foundation of enterprise adoption. Leading organizations are investing in AI innovation and AI governance in parallel, because sustainable scale requires both.

To address evolving customer needs, the Global Delivery Hub offers personalized success plans that tailor service experiences from self-guided resources to strategic partnerships, helping customers achieve continuous value and success.  Delivering this level of personalized, AI-enabled customer success requires a fundamentally different approach to service delivery.

At the core of this transformation are four guiding pillars that enable the Global Delivery Hub to combine human expertise with intelligent automation and deliver consistent, outcome-driven experiences.

Four C’s power the Global Delivery Hub’s AI-driven delivery model

The transition to agentic AI is not defined by technology alone. It is defined by how organizations prepare their people, evolve their ways of working, and establish the right foundations for responsible autonomy. Service delivery organizations that successfully embrace this shift will combine human expertise with intelligent automation to create more agile, resilient, and outcome-driven services.

Our AI-driven delivery model is built on four critical pillars: customers, capabilities, collaboration, and controls, required to unlock the full potential of AI while maintaining trust, accountability, and business alignment.

• Customer: Through the combination of intelligent agents, automation, and human expertise, service delivery teams can better understand customer needs, anticipate challenges, and provide more proactive, personalized advisory. This creates a stronger partnership model where AI continuously optimizes delivery services and accelerates customer success.
• Collaboration: Driving value with AI requires stronger, more connected, agile, and cross-functional collaboration across the organization. Product, engineering, delivery, and customer teams must work as one team, continuously aligning technology, operations, and customer outcomes to accelerate innovation and business value.
• Capabilities: Realizing the full potential of agentic AI is not simply a technology transformation; it is a people transformation. The future of delivery will be shaped by professionals who combine deep operational expertise with the ability to work effectively alongside intelligent agents. Technical excellence must complement AI fluency, automation skills, and the ability to leverage data-driven insights to make faster, better decisions. The organizations that succeed will be those that empower their people to adapt, learn, and collaborate with AI, creating a workforce that is not only AI-enabled, but AI-empowered.
• Controls: As AI becomes more autonomous, governance must evolve from a set of controls into a strategic capability that enables trust, scale, and responsible decision-making. Organizations need clear principles that define where AI agents can act independently, where human oversight is required, and how decisions are monitored and improved. Strong governance provides the foundation to scale agentic AI with transparency, accountability, and alignment to business objectives.

Without these foundational pillars, organizations risk adding complexity rather than creating value. Those that take a customer-centric approach while investing in the right capabilities, cross-functional collaboration, and appropriate controls will be better positioned to scale agentic AI, strengthen operational resilience, accelerate innovation, and deliver superior customer outcomes.

As agentic AI continues to reshape enterprise operations, these capabilities are becoming the foundation for the next generation of software service delivery.

Leading the next era of software service delivery

Organizations that act early will be better equipped to unlock the value of autonomous capabilities while ensuring governance, trust, and alignment with strategic business priorities. As software service delivery shifts to proactive, AI-powered operations, customers increasingly view providers as strategic advisors and AI co-pilots that help navigate their transformation journey.

By combining intelligent agents, automated workflows, and human expertise, organizations can proactively address challenges and achieve stronger business outcomes. To succeed in this new model of engagement, customers should focus on key areas that will accelerate their path toward an Autonomous Enterprise:

• Adopt a mindset of continuous adaptation: The AI landscape will continue to evolve rapidly. Customers that treat AI adoption as an ongoing transformation will be better equipped to innovate, respond to change, and build a resilient foundation for the autonomous enterprise.
• Build AI-ready teams and operating models: As delivery becomes increasingly collaborative between humans and intelligent agents, teams need a clear understanding of what is automated, what requires human judgment, and how to engage when exceptions occur. Preparing employees with AI fluency, updated processes, and new ways of collaboration will be critical to maximizing the value of agentic AI.
• Early alignment on shared outcomes, governance, and ways of working: Successful AI-enabled delivery requires clear alignment between customers, SAP, and partners on business objectives, success metrics, decision rights, and accountability. Establishing joint KPIs, governance models, and escalation paths early helps ensure AI-driven operations remain transparent, trusted, and focused on measurable business value as autonomous capabilities evolve.

The shift to agentic AI is not simply about automating existing services. It is about creating a new partnership model focused on continuous improvement, shared accountability, and business outcomes. Customers that prepare today will be better positioned to take advantage of the agility, resilience, and innovation enabled by the Autonomous Enterprise.

Sanjay Kulkarni is global head of Delivery Hub and Customer Value Group at SAP.
Julia Kloppenburg is a technology consultant in Customer Engagement & Adoption at SAP SE.
Benedikt Gieger is Product Strategy and AI lead in Digital Manufacturing at SAP SE.