SAP Sapphire Madrid 2026: From AI Assistance to the Autonomous Enterprise 

A Few Days in Madrid 

I had the opportunity to attend SAP Sapphire Madrid 2026 from 19 to 21 May, joining customers, partners, and SAP experts from across Europe to discuss the future of enterprise technology. While there were many interesting sessions throughout the event, the Global Keynote on 20 May, titled The Beginning of Better, stood out as the clearest expression of where SAP sees business technology heading next.

Presented by Christian Klein, Sebastian Steinhaeuser, Philipp Herzig, and Muhammad Alam, the keynote focused on a vision that goes beyond using AI as a productivity tool. Instead, SAP introduced its concept of the Autonomous Enterprise, where people define objectives, policies, and boundaries, while AI agents execute business processes within governed and trusted environments.

A Shift in How Enterprise AI Is Framed

One of my main observations from the keynote was that SAP is moving the conversation beyond AI assistants that simply help employees perform tasks faster. The focus is increasingly on AI systems that can carry out work autonomously while remaining under human oversight.

The centrepiece of this vision is the newly announced SAP Autonomous Suite. SAP described it as a framework that brings together AI agents, assistants, business applications, and governance capabilities into a single operating model. Rather than deploying isolated AI solutions, organizations would be able to orchestrate business processes that span multiple functions while maintaining visibility, compliance, and control.

This felt like an important distinction. Many organizations are currently experimenting with AI pilots and productivity tools, but the challenge often lies in connecting those capabilities to real business processes. SAP’s message was that enterprise AI needs to be embedded directly into operational systems rather than existing alongside them.

The Evolution of Joule

Another significant announcement was the evolution of Joule. Joule is now expanding into a broader AI workspace.

SAP presented Joule Work, Joule Assistants, Joule Agents, and Joule Studio 2.0 as components of a larger ecosystem designed to support both employees and autonomous business operations. The direction suggests a future where users interact with AI not only through conversational assistance, but also through specialized agents capable of executing defined business tasks.

What I found particularly interesting was how SAP positioned these capabilities as part of a coordinated environment rather than separate products. The emphasis was on enabling collaboration between people, AI assistants, and autonomous agents within existing business workflows.

Trust, Data, and Governance Take Center Stage

Perhaps the most important theme throughout Sapphire was trust.

SAP repeatedly emphasized that autonomous AI can only be effective when it is grounded in trusted business data and governed appropriately. This is where SAP Business Data Cloud, the new SAP Business AI Platform, and the SAP AI Agent Hub fit into the broader strategy.

The SAP Business AI Platform was presented as the foundation for building, governing, deploying, and operating enterprise AI agents. At the same time, SAP Business Data Cloud provides the business context that agents need to make informed decisions, while governance capabilities ensure transparency and accountability.

I was also interested to see SAP highlight its collaboration with Mistral AI and its commitment to trusted European AI and sovereign AI capabilities. For many organizations, particularly in Europe, questions around data sovereignty, regulatory compliance, and trusted AI infrastructure are becoming just as important as model performance.

Why This Matters

For organizations exploring AI adoption, the announcements at Sapphire were less about individual features and more about architecture and operating models.

Many companies have already discovered that deploying AI tools is relatively easy compared to scaling them across critical business processes. The challenge is creating an environment where AI can operate reliably, securely, and in alignment with business objectives.

The message from the keynote The Beginning of Better was clear: the next phase of enterprise AI is not simply AI assisted work. It is AI executed business processes operating under human governance. SAP’s vision of the Autonomous Enterprise brings together Joule, AI agents, trusted business data, and the SAP Autonomous Suite to make that transition possible.

Looking Ahead

Leaving Madrid, my impression was that enterprise AI discussions are becoming more practical and more operational. The focus has shifted away from experimentation toward questions of governance, execution, trust, and measurable business outcomes.

Whether organizations are ready for fully autonomous business processes today is another question. However, the direction presented at SAP Sapphire 2026 suggests that enterprise software is steadily evolving toward environments where humans set the goals and AI increasingly handles the execution. It will be fascinating to see how quickly that vision becomes reality over the coming years.

-Juuso Maijala, CEO

SAP Business Data Cloud explained: how Snowflake and Databricks fit into SAP’s multi-platform data strategy

Insights from SAP TechEd Berlin 2025: why data became SAP’s strategic core

Reflecting on SAP TechEd Berlin 2025, one theme stood out above all others: data has become the foundation of SAP’s future strategy. 

While AI demonstrations and development tooling attracted attention, the most meaningful announcements focused on how enterprise data is accessed, shared, and activated across platforms. 

At the center of this shift is SAP Business Data Cloud (BDC), a strategic layer designed for organizations operating in increasingly complex, multi-platform landscapes. Its implications are significant for customers navigating increasingly complex data landscapes. 

SAP Business Data Cloud: embracing reality, not fighting it

Enterprise data is no longer confined to a single platform. SAP systems, cloud data warehouses, and analytics tools already coexist in most organizations. What SAP Business Data Cloud does differently is acknowledge this reality instead of trying to replace it. 

BDC is designed as an open data access layer, connecting SAP data natively with platforms such as:

  • Snowflake
  • Databricks
  • Google Cloud
  • and Microsoft Fabric

The emphasis on zero-copy data sharing is particularly important: data can be consumed and analyzed without constant replication. This reduces cost, latency, and architectural complexity. 

From Etlia’s perspective, this is a welcomed and pragmatic shift. Many organizations already run hybrid data architectures, and BDC provides a way to integrate SAP data into those environments without forcing disruptive migrations or one-size-fits-all solutions. 

How SAP Business Data Cloud works with Snowflake, Databricks and Microsoft?

SAP’s message at TechEd was clear: there is no single “correct” data platform. Instead, SAP is enabling a coordinated, multi-platform data strategy where each platform plays a distinct role.

Platform roles in SAP’s multi-platform data architecture

  • SAP Business Data Cloud (BDC)
    • Open data access layer and governance backbone, connecting SAP data with external platforms securely and consistently
  • Snowflake
    • Scalable analytics and data sharing platform, positioned as an SAP-certified solution extension
  • Databricks
    • Scalable analytics and data sharing platform including advanced analytics, machine learning, and data science workloads
  • Microsoft Fabric
    • Tight integration with Microsoft 365, Power BI, and the Power Platform, especially in Microsoft-centric ecosystems

This model reflects how enterprises already work in practice: SAP remains the system of record, while analytics, AI, and innovation happen across multiple specialized platforms.

Snowflake as a Strategic Extension, Not Just an Integration 

One of the most notable announcements at TechEd was SAP’s positioning of Snowflake as a Solution Extension to SAP Business Data Cloud. 

This is more than a technical integration or partnership label. As a solution extension, Snowflake becomes: 

  • Fully certified, packaged, and sold by SAP 
  • Supported by SAP throughout the full lifecycle 
  • Aligned with SAP’s roadmap and enterprise support model 

Crucially, SAP Snowflake includes the full Snowflake feature set while complementing it with SAP-specific strengths, particularly in planning. 

From Etlia’s point of view, this confirms something we already see in customer projects: Snowflake, Databricks, and Fabric are not competing replacements for SAP, but complementary platforms. The strategic shift from SAP is clear: value is created by choosing the right tool for the right workload and ensuring that data flows cleanly, securely, and governably between platforms.

One Data Strategy, Multiple Platforms

A key takeaway from SAP TechEd Berlin 2025 is that SAP is no longer pushing a single “correct” data platform. Instead, it is enabling a multi-platform data strategy, where: 

  • SAP remains the system of record for core business processes 
  • Snowflake excels in scalable analytics and data sharing 
  • Databricks supports advanced analytics and data science 
  • Microsoft Fabric fits naturally into Microsoft-centric ecosystems 

For customers, the challenge is no longer choosing one platform over another. The real challenge is designing an architecture where these platforms work together, with clear ownership, strong governance, and measurable business value.

Data as the Foundation for Enterprise AI 

AI discussions at TechEd consistently came back to one point: AI only works if the data foundation is solid. 

SAP’s introduction of SAP-RPT-1, an AI foundation model for structured business data, reflects this mindset. Rather than focusing on language alone, SAP is investing in models that understand tables, relationships, and enterprise semantics, the kind of data that actually runs businesses. 

With Model Context Protocol (MCP), SAP is also addressing a growing need: enabling Large Language Models to access business data in a governed, contextual way. This opens the door to AI use cases that go beyond chatbots and into real decision support, analytics, and automation. 

From Etlia’s perspective, this reinforces a critical message to customers: AI success is not about tools, but about data readiness. Clean models, shared semantics, and well-designed data architectures matter more than the choice of any single AI platform. 

What This Means in Practice

SAP TechEd Berlin 2025 showed a SAP that is more open, more realistic, and more aligned with how enterprises actually operate today.

SAP Business Data Cloud, deeper partnerships with Snowflake, Databricks and Microsoft Fabric and native support for multi-platform architectures all point in the same direction. 

For organizations, the question is no longer whether SAP data will live alongside Snowflake, Databricks, or Fabric, but how well those environments are integrated. 

And that is where the work for Etlia begins.

– Juuso Maijala, CEO


Etlia is a data consultancy specializing in SAP, Snowflake, Databricks, and Microsoft Fabric architectures for enterprise environments.

Etlia works with organizations designing SAP-centric data architectures where SAP Business Data Cloud acts as the governance and access layer, while analytics, AI, and business intelligence are delivered across multiple best-of-breed platforms.

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