SAP Sapphire 2025 marked a strategic turning point. While it featured a flood of updates, from partnerships with Palantir and Perplexity to sweeping changes in pricing and packaging, the real story was SAP’s repositioning of AI as the enterprise operating system. For CIOs, this is a shift in how enterprise applications will be built, deployed, and governed — a shift that Forrester has been discussing for some time.

Here is a review of the seven critical signals from Sapphire 2025 and what they mean for your IT strategy and SAP partnership decisions.

1. SAP’s AI Flywheel: From Apps To Agents

SAP’s new “flywheel” model — in which apps generate context-rich data, data fuels embedded AI, and AI enhances apps — creates a self-perpetuating cycle of intelligence and efficiency, with SAP promising a potential productivity surge of up to 30%. The centerpiece is Joule, SAP’s AI assistant, now evolving into a pervasive interface layer across SAP and non-SAP systems. Bolstered by integrations with WalkMe for contextual guidance and Perplexity AI for enriched insights, Joule is now empowered to launch autonomous Joule Agents. These agents, tailored for domains such as finance or supply chain, don’t just provide answers; they are designed to turn “signals to action,” fundamentally rewriting how core business processes are executed. This all runs on a new AI Foundation, providing the governance, development tools (Joule Studio), and multimodel support necessary for enterprise-grade AI.

What it means for tech leaders:

  • You’re no longer just managing applications — you’re managing an AI workforce.
  • Expect a shift from user-driven workflows to agent-driven execution.
  • Establish policies for agent observability, compliance, and control.

2. SAP Business Data Cloud (BDC): The New Data Backbone

SAP’s Business Data Cloud (comprised of Databricks, Datasphere, Business Warehouse and SAP Analytics Cloud) harmonizes structured and unstructured data across SAP and non-SAP systems, preserving business context. Envisioned as a unified data fabric (that will now be available on AWS [live], Google Cloud, and Azure by Q4 2025), BDC leverages the SAP Knowledge Graph to weave together disparate SAP and non-SAP data streams while critically preserving their rich business context. This is the fuel for the entire AI flywheel.

What it means for tech leaders:

  • Recognize BDC as the nonnegotiable data foundation; SAP’s entire Business AI vision and its promised value is predicated upon it.
  • Master BDC’s semantic layer and the SAP Knowledge Graph; preserving true business context across federated data is SAP’s core differentiator for relevant and trustworthy AI.
  • Elevate data governance to a strategic imperative; BDC’s multicloud reach and AI reliance demand board-level focus on data quality, lineage, and security.

3. The “Suite As A Service” And Ecosystem: The Answer To Fragmentation

SAP is championing a “suite-as-a-service” model. This is not just bundling. It involves five new line-of-business-specific Business Suite packages (e.g., for finance or the supply chain) designed to cater to different buyer profiles. With managed integrations and embedded SAP Build capabilities, the goal is to promote extensibility while enforcing a clean core. SAP’s message (and its major market bet) is unequivocal: Isolated tools, however capable, cannot match the exponential intelligence of an integrated suite when AI is the strategic objective. When it wasn’t focusing on the deep integration across its own suite, SAP was busy announcing partnerships with Perplexity, Palantir, Adobe, NVIDIA, Accenture, and every major hyperscaler, just to name a few partners. Ecosystems drive collaborative advantage in business apps. Partner marketplaces are table stakes; true differentiation comes from a deep, outcome-driven ecosystem strategy.

What it means for tech leaders:

  • SAP’s shift toward bundled, subscription-based cloud models and heavy dependence on the Business Technology Platform (BTP) for extensibility increases vendor lock-in. This is partially offset by the extensibility offered by BTP and SAP’s broad ecosystem.
  • Reevaluate your app portfolio: SAP’s integrated AI within the suite-as-a-service model challenges the need for disparate, best-of-breed solutions — raising additional concerns over vendor lock-in.
  • Your SAP strategy now demands leveraging its ecosystem: Identify key partners for gaps/goals and prudently navigate the complex “co-opetition” landscape.

4. Clean Core And Cloud Migration: The Price Of Admission

SAP’s most advanced AI capabilities are unequivocally gated behind a clean core and cloud-native architecture. Whether through RISE with SAP now evolving to a “fit-to-suite” methodology to support comprehensive business transformation or GROW with SAP, organizations must modernize legacy environments to unlock this AI value. SAP acknowledges that ECC-to-S/4HANA migration remains a major hurdle, fraught with historical challenges related to cost, timelines, and clean core adherence. To address this, SAP is significantly enhancing its integrated toolchain, Cloud ALM, as well as SAP Signavio (with new AI-driven transformation advisor and root-cause analysis capabilities), and SAP LeanIX (with AI-assisted architecture guidance) infusing AI to provide smarter guidance throughout the transformation. SAP is moving toward mandating that RISE-validated partners use Signavio and LeanIX from day one of major cloud transformation programs.

What it means for tech leaders:

  • SAP is increasing its pressure on implementation partners to adopt a clean core strategy, as so far there has been a heavy dominance of brownfield projects.
  • Budget holistically for business, operations, and process transformation, not just technical lift-and-shift projects.
  • Use SAP’s AI roadmap to justify long-postponed modernization efforts.

5. Services Oversight: Elevating Accountability With SAP Services Partners

In response to persistent concerns over migration costs, overruns, and uneven quality, SAP is adopting a more hands-on approach to service delivery. It will provide direct oversight on all ECC-to-S/4HANA migration projects and selectively take on delivery responsibilities itself, claiming faster timelines and reduced costs compared to traditional partners. But SAP’s ability to deliver business transformation at scale is still untested, especially for greenfield projects, which typically involve complex process redesign and higher organizational change overhead. Brownfield migrations, which SAP seeks to expedite, are more feasible technically but often compromise on the clean core — an essential prerequisite for SAP’s AI roadmap.

What it means for tech leaders:

  • Prioritize service partners with proven clean-core success — aim for over 60% standardization as a continuous journey.
  • Leverage SAP’s seeded tools (e.g., Signavio, LeanIX) early; in 2024, both were offered free for six months.
  • Evaluate partner value beyond lift and shift: Advisory, accelerators, and change management remain essential in complex SAP environments.

6. Revamped Commercial Strategy: Pricing For Strategic Adoption

SAP is simplifying its commercial model to match its AI-first platform strategy. It is eliminating the historically complex SKU sprawl in which some finance deployments faced over 80 SKUs with streamlined suite-based packaging per user, per month, and by line of business. More critically, SAP is introducing consumption-based pricing using AI Units for premium Joule Agents and transactional AI capabilities, pooled by user and function. While more transparency is still needed, the shift moves SAP closer to aligning value with usage.

To accelerate modernization, SAP announced a bold incentive: It will cover the typical migration cost for ECC and S/4HANA customers that commit to a standardized RISE with SAP journey. This is more than a discount — it’s a time-sensitive nudge to move to SAP’s cloud innovation platform.

What it means for tech leaders:

  • A clean core is now an ongoing discipline to continuously adopt SAP’s AI innovations.
  • View S/4HANA migration as the strategic unlocking of enterprise data, not just technical debt retirement.
  • Build agility on BTP, where differentiation happens; deep core modifications will limit future innovation.

7. Trust And Governance: A Work In Progress

SAP’s Business Technology Platform underpins both its application suite and its emerging AI workforce. At the center of this is Joule Studio, enabling the creation and orchestration of AI agents. SAP aims to scale from 230 to 400 agents in 2025, forming an interoperable “AI workforce” across domains. To support this, SAP introduced an AI agent hub within LeanIX that’s designed to map agents to business processes, track compliance, and ensure alignment with enterprise policies.

SAP’s governance posture is still evolving, however. While the agent hub is a meaningful step, SAP has not fully clarified its approach to AI security, GRC, or data sovereignty within BDC and Business AI. It’s evident that deeper oversight will depend on partner and customer-led frameworks.

What it means for tech leaders:

  • Be aware that agent interoperability protocols (e.g., with Google Cloud) are promising but currently immature, requiring diligent validation.
  • Expect to augment SAP’s stack with third-party tools and robust internal frameworks for comprehensive compliance, auditability, and risk management of autonomous AI agents.
  • AI agent governance extends far beyond HR; it requires cross-functional ownership across IT, security, legal, and compliance.

SAP’s Process-Centric Bet: Competing With Other Platforms

SAP’s Business AI vision doesn’t exist in a vacuum. Tech leaders are navigating a landscape where Oracle embeds AI deeply within its vertical applications, Microsoft champions a broad platform-first Azure AI strategy, ServiceNow focuses on intelligent cross-application workflow automation, and Salesforce continues to drive its Data Cloud and Einstein AI primarily within the CRM domain. SAP’s distinct strategic wager is that embedding AI deeply within its integrated core business processes (e.g., enterprise resource planning, supply chain management, finance, HR), powered by the contextualized data from its Business Data Cloud, could deliver scalable, enterprisewide intelligence and automation.

For CIOs, the decision transcends selecting AI features; it’s about committing to an architectural philosophy. Evaluate whether SAP’s deeply integrated, process-centric AI embedded in your foundational systems — as opposed to more platform-, workflow-, or line-of-business-specific strategies — best fuels your fundamental operational transformation and long-term competitive advantage.

Stay tuned for follow-up analyses and reviews from Charles Betz, Faram Medhora, and Akshara Naik Lopez on the SAP Business Suite, AI execution models, enterprise architecture strategies, and the evolving role of service partners in business transformation.