SAP expects to deliver 400 Business AI use cases by end of 2025. That's not just a number—it's a complete transformation of how enterprise consulting works.
I've been watching this shift for months, and what's happening is way more radical than the headlines suggest. Traditional consultants armed with ChatGPT are about to get steamrolled by grounded AI systems that can actually prove their recommendations.
The Hallucination Problem That Nobody Wants to Admit
Here's what's driving this change: enterprise consultants can't risk hallucinated guidance when their recommendations impact operations and compliance. That's according to SAP's latest positioning, and honestly? They're absolutely right.
When you're advising a Fortune 500 company on supply chain transformation, "the AI said so" isn't good enough. You need verifiable facts. Predictable behavior. Audit trails.
<> "HANA is the database AI has always been looking for," says Michael Ameling, SAP's president of Business Technology Platform. He's talking about structured predictive use cases, not general LLM tasks./>
The technical shift here is fascinating. SAP just announced SAP-RPT-1—an enterprise relational foundation model designed specifically for structured business data rather than next-token prediction. This isn't your typical transformer model.
What Nobody Is Talking About
The real game-changer isn't the model itself. It's the Model Context Protocol (MCP) support for HANA Cloud coming in Q1 2026.
This means agents can:
- Perform semantic search across customer data
- Navigate supplier relationships in real-time
- Handle spatial reasoning within the same in-memory engine
- Auto-generate knowledge graphs from existing metadata
That last point is huge. Manual ontology work has been the bottleneck for enterprise AI deployment. SAP is automating it away.
The Zero-Copy Revolution
But here's where it gets really interesting. SAP's November partnership with Snowflake enables zero-copy bi-directional data sharing. Futurum's Brad Shimmin called it a "market-defining move" that challenges legacy ETL.
Think about what this means:
- Live business data reaches AI workloads instantly
- No more batch processing delays
- Governed semantics flow directly into AI systems
- Real-time recommendations based on actual business state
This is going to destroy traditional data pipeline companies.
The Consultant Liability Problem
What really excites me about grounded models is the accountability angle. When SAP-RPT-1 predicts a delivery delay or flags payment risk, it can trace that recommendation back to specific data sources.
For consultants, this changes everything:
1. Higher confidence in recommendations
2. Auditable decision trails for compliance
3. Reduced liability when transformations go wrong
4. Faster implementation of proven use cases
But there's a catch. As Computer Weekly pointed out, success depends on clean master data and consistent governance models. Most enterprises aren't ready for this.
The European Sovereignty Angle
SAP is also pushing hard on European digital sovereignty with expanded German infrastructure and Deutsche Telekom partnerships. Smart positioning against the hyperscalers.
Philipp Herzig, SAP's CTO, emphasizes "the difficulty of building AI at scale for large multinationals." Translation: this isn't about cool demos. It's about enterprise-grade reliability.
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The shift from black-box LLMs to grounded models isn't just technical evolution—it's a complete reset of the consulting industry. Companies that can guarantee auditable, fact-based recommendations will dominate. Those stuck with generic AI will get left behind.
The 400 use cases SAP is rolling out aren't just features. They're the new competitive baseline for enterprise AI.
