The new pattern: consolidate ERP, move AI to the hyperscaler
Enterprise ERP AI consolidation is the emerging strategy in which large organisations standardise core processes into a clean ERP backbone while shifting most intelligence, data access and machine learning capabilities down into hyperscale cloud platforms instead of keeping them locked in application silos. Nokia’s new multi-year agreement to run its SAP S/4HANA environment on Microsoft Azure using RISE with SAP methodology, and SAP’s acquisition of Dremio, are not isolated moves—they are a blueprint for how AI will be built, governed and consumed in the next wave of cloud-native business transformation. The key takeaway is blunt: AI is becoming a cloud architecture decision, not an ERP module add‑on. Nokia’s SAP S/4HANA Azure migration shows that the platform underneath your ERP now decides performance, resilience and AI readiness. SAP’s Dremio agentic AI data capabilities show that the most valuable intelligence will come from combining SAP and non‑SAP data across hybrid landscapes, in real time, without shuffling data around.
Nokia’s RISE with SAP clean-core play: AI starts with fixing ERP
Nokia’s RISE with SAP methodology deal is a conscious bet that you cannot get serious about AI until you fix ERP. The company is consolidating multiple ERP systems into a unified SAP S/4HANA landscape, with SAP operating and managing that environment in the cloud while Microsoft Azure sits underneath as the hyperscale platform. That three‑party model—SAP for ERP and managed operations, Microsoft for infrastructure, Nokia for process ownership—puts AI on top of standardised, reliable transactional data instead of custom-riddled legacy code. Clean-core discipline is the quiet hero here. SAP’s framework is explicitly designed to provide a road map, integrated toolchain and continuous access to innovation while helping Nokia keep a clean core and avoid recreating the customization sprawl of earlier generations. Cloud migration can reduce complexity, helping transformation teams not carry old customization and fragmented process design into the new environment. In practical terms, that reduction in technical debt is what makes AI model training and inference viable at scale; noisy, inconsistent data is where promising AI pilots go to die.
Azure and Dremio: hyperscalers become the AI operating system
Nokia’s choice of Microsoft Azure is a clear admission that hyperscaler selection now shapes ERP strategy, not just hosting. Large SAP customers are no longer treating hyperscaler choice as a background infrastructure decision; the cloud platform increasingly drives migration risk, performance, security, operational resilience, data strategy, and the pace of AI adoption. Microsoft Azure will serve as the foundation for Nokia’s RISE with SAP journey, giving global scale, security and performance for business‑critical workloads while SAP manages the S/4HANA environment in the cloud. SAP’s completed acquisition of Dremio then takes this one step further. Dremio is an open, high‑performance data lakehouse platform, and SAP says the deal accelerates agentic AI while expanding customers’ ability to combine SAP and non‑SAP data for analytical and AI workloads in real time, with no data movement or conversion and with improved economics. Together, Azure and Dremio signal a simple truth: hyperscalers and data lakehouses are morphing into the AI operating system beneath ERP, not a neutral utility layer.
What it means for ordinary users: cleaner processes, smarter decisions
For employees and managers, these moves are not abstract architecture games; they should translate into day‑to‑day gains. SAP’s cloud ERP portfolio promises ready‑to‑run enterprise resource planning capabilities in the cloud so organisations can run core operations with confidence. When Nokia standardises finance and logistics on a clean SAP S/4HANA backbone—including central finance, master data governance, warehouse management, global trade services and advanced available‑to‑promise—the result should be fewer inconsistent workflows and less time spent reconciling systems. On top of that, Nokia will gain access to embedded AI capabilities through SAP’s cloud ERP, with AI‑enabled functionality adopted progressively as part of the journey. Combined with Dremio’s agentic AI data platform, end users ought to see more real‑time insights drawn from both SAP and non‑SAP sources without waiting for nightly batch jobs or expensive data duplication. The promise is faster decisions and more dependable automation, grounded in cleaner transactional data rather than opaque black‑box predictions.
The strategic takeaway: treat AI as infrastructure, not a feature
Nokia’s RISE with SAP journey and SAP’s Dremio acquisition together make one argument: future AI strategy belongs in the cloud architecture and ERP operating model, not in a handful of isolated app features. RISE with SAP is explicitly framed as a comprehensive business transformation framework, combining methodology, tools and expert guidance to move from legacy ERP to a cloud‑native operating model. Nokia’s move shows that modern SAP transformation means simplifying the ERP landscape, shifting infrastructure management to SAP’s cloud operating model, and using the resulting foundation to adopt embedded AI and cloud innovations over time. The conclusion for CIOs and ERP leaders is clear. Treat hyperscaler choice as a strategic architecture decision. Build a clean core ERP that resists customization sprawl. Invest in data platforms that can combine SAP and non‑SAP sources for agentic AI in real time. If you still see AI as a bolt‑on feature at the application layer, you are planning for yesterday’s problems on tomorrow’s platforms—and you will be outpaced by those who design AI into the cloud layer from the start.
