Sapphire 2026: From Reporting and Planning to Directing
- AI, SAP Business Data Cloud (BDC)
- 5 min reading time
Michael May
The Sapphire Announcements 2026 have made quite a splash, but what does it really mean for businesses? While most commentators are talking about agent numbers and cloud partnerships, Michael May, CEO of s-peers AG, sees the real revolution elsewhere: in the transformation from reporting and planning to directing.
Table of contents
- 1. SAP delivered in Orlando. And I don't say that lightly.
- 2. The foundation comes first, and that’s how it should be
- 3. From Reporting and Planning to Directing
- 4. The Autonomous Enterprise with more than 200 AI agents
- 5. The new platform layer: SAP Business AI Platform with Joule
- 6. The trend is toward an open ecosystem. Because that's what customers want!
- 7. What role do SAP partners play?
- 8. Are Swiss companies ready?
- 9. My Conclusion
1. SAP delivered in Orlando. And I don't say that lightly.
Anyone who has been following developments over the past few months knows that the market is asking SAP a simple question: “What role will SAP play in a world increasingly shaped by artificial intelligence?”
For a long time, the answer seemed unclear. At Sapphire 2026, Christian Klein provided that answer. My first thought: Finally!
Because what SAP presented was far more than just another technology update. It was a blueprint for a new vision for businesses—a vision that SAP calls the “Autonomous Enterprise.” This is not about replacing people with AI. It’s about empowering companies to recognize opportunities faster, make better decisions, and execute processes with increasing autonomy. That is precisely why I see Sapphire 2026 as a turning point.
2. The foundation comes first, and that’s how it should be
Many companies are already discussing generative AI, agents, and large language models, but they are still grappling with inconsistent master data, isolated data silos, and a lack of governance structures. SAP has recognized what is often overlooked: Artificial intelligence is only as good as the data it is based on.
This is where SAP has a significant strategic advantage. Companies that use SAP already have a vast amount of structured, business-critical data—financial data, supply chain information, HR data, production data, and customer data. This data reflects a company’s digital reality. But simply having data is not the same as being able to use it.
This is exactly where the SAP Business Data Cloud (BDC) comes in: data should be harmonized, semantically described, and made available for AI use under clear governance rules. The fact that SAP is entering into partnerships with Databricks, Snowflake, Microsoft, and Google is not a concession—it is a sign of strategic realism. SAP accepts the heterogeneity of modern enterprise architectures rather than ignoring it.
The real challenge in the coming years won’t be the introduction of agents—it will be making corporate data AI-ready. Those who start cleaning up their databases today will have a significant competitive advantage in two to three years.
3. From Reporting and Planning to Directing
In my view, however, the true significance of the Sapphire announcements runs even deeper. For decades, the role of reporting was to provide transparency. The role of planning was to plan for the future. Companies analyzed historical data, created forecasts and budgets, and then made decisions based on that information.
With the Autonomous Enterprise, this focus is shifting fundamentally.
Companies are shifting from reporting and planning to directing:
- Reporting answers the question: “What happened?”
- Planning answers the question: “What could happen?”
- Directing answers the question: “What should we do now?” —and, increasingly in the future: “What can we do automatically within defined parameters?”
Directing is not merely an extension of reporting and planning—it is a qualitatively different mode of corporate management. The difference lies in the mechanism: instead of providing information and waiting for human decisions, a closed loop is created. Data is continuously analyzed, AI identifies patterns and evaluates options for action, agents implement defined measures—and the measured impact is immediately incorporated into the next decision.
The Autonomous Enterprise is therefore not a one-time decision-making process, but rather a learning system that continuously integrates analysis, decision-making, execution, and performance monitoring. While SAP provides the technological vision, Directing describes the business implications that result from it—and this, to me, is where the true value of Business AI lies.
4. The Autonomous Enterprise with more than 200 AI agents
The media has frequently highlighted the figure of over 200 SAP agents. While this number is impressive, it does not tell the whole story.
The real innovation isn't that SAP provides hundreds of agents. The real innovation is that SAP creates a platform that brings together agents, business processes, corporate data, and governance.
In the future, agents will be able to take on tasks in finance, procurement, HR, service, or the supply chain. It is important to note that the Autonomous Enterprise is not a concept designed to replace employees. Rather, SAP describes a new form of collaboration between people, AI, and agents:
- People set goals, priorities, and guidelines.
- Business AI analyzes information, generates recommendations, and simulates possible courses of action.
- Agents are responsible for carrying out defined tasks.
Responsibility remains with people—productivity increases through the intelligent collaboration of all three levels. The key point here is that “autonomous” does not mean “uncontrolled.”
SAP has placed great emphasis on ensuring that all activities remain traceable, audit-proof, and controllable. Each agent operates within defined rules, documents their decisions, and can be monitored at any time.
This is a key factor for success, especially for Swiss companies with stringent compliance and audit requirements.
5. The new platform layer: SAP Business AI Platform with Joule
The unveiling of the SAP Business AI Platform was particularly noteworthy. It will serve as the central layer for the development, operation, and governance of business AI solutions.
Joule enables users to access business processes using natural language.
In my view, however, Joule is often underestimated. Joule is not simply a new chatbot for SAP applications. Joule is evolving into the central interaction layer of the Autonomous Enterprise. In the future, employees will no longer navigate through individual applications; instead, they will ask business questions, make decisions, and initiate processes directly through Joule.
Joule brings together people, corporate data, business processes, and AI agents in a shared workspace.
With Joule Studio, companies can develop their own agents. The AI Agent Hub provides the necessary governance and transparency. The SAP domain models bring deep process and domain expertise to the AI applications.
6. The trend is toward an open ecosystem. Because that's what customers want!
SAP does not attempt to develop all AI technologies in-house. Instead, the company relies on an open ecosystem and integrates leading technology partners such as Anthropic, NVIDIA, Microsoft, Google, and AWS.
In my view, that is exactly the right approach.
No company today operates exclusively in an SAP environment. Data resides in Azure, AWS, Snowflake, or Databricks. AI models come from a variety of providers. The ability to bring all these environments together in a secure and governed manner is becoming a critical factor for success.
The future does not belong to closed platforms. The future does not belong to the companies with the most data. It belongs to the companies that turn data into decisions and decisions into results.
7. What role do SAP partners play?
SAP has announced that it will invest heavily in its partner ecosystem. This is a logical move.
The platform alone will not create an autonomous enterprise. Companies need partners who understand business processes, build data platforms, establish governance, and translate business AI applications into measurable business results.
In my view, simply providing the technological platform is not enough. Success depends largely on how business units, data teams, SAP teams, and AI initiatives work together.
In many companies today, we still see organizational silos between business units, SAP, data platforms, and analytics. It is precisely these silos that often prevent the rapid implementation of innovations and significantly slow down time-to-market.
The full potential of data, analytics, and AI can only be realized when these fields work together toward a common goal.
That is why the journey toward the Autonomous Enterprise does not begin with technology, but rather with:
- a clear prioritization of the technical requirements,
- a coordinated data, analytics, and AI strategy,
- as well as a joint roadmap.
We see this as a key area where we can support companies both methodologically and through facilitation.
8. Are Swiss companies ready?
My answer is: Yes.
Switzerland is one of the most innovative business locations in Europe. Swiss companies do not invest in technologies simply because they appear modern. They invest only when there is a clear business case.
It is precisely this business case that is now becoming clear.
At the same time, it becomes clear that any company that permanently disconnects itself from the cloud-based innovation pathways of the major platform providers will lose ground in the realm of business AI.
So the question is no longer: Cloud or AI?
The question is: How quickly can we create the conditions necessary to use AI in a way that makes economic sense?
9. My Conclusion
Sapphire 2026 was much more than just a product showcase. SAP presented a vision of how companies will work, make decisions, and be managed in the future—and the foundation for this is clear: data, governance, and an open platform strategy.
The real challenge begins now.
Companies need to make their data AI-ready. They need to build up expertise. They need to establish governance structures. And they need to learn how people and agents will work together in the future.
The path to that goal does not begin with technology. It begins with a clear vision of how companies want to make decisions, manage their operations, and act in the future.
That is exactly where we support our customers.
Your data strategy is unique—your consulting should be too.
The choice between these methods depends on countless factors: your existing system landscape, your business goals, and your data culture. There is no standard answer.
Let’s talk, with no obligation, about which path is right for you.
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