How do you turn an AI strategy into business value? For many organizations, the answer remains frustratingly out of reach. A new KPMG survey finds that while most enterprises say they have an AI strategy, only a small fraction are realizing meaningful return on investment — and the gap, the survey suggests, has less to do with models and more to do with how companies organize themselves.
What the KPMG survey shows
The survey, conducted by KPMG, delivers a blunt diagnosis: organizations must transform operations to scale AI. According to KPMG's findings, the existence of an AI strategy is now common across enterprises, but actual ROI is scarce. The report highlights that the companies achieving measurable results are not treating AI as a point project or a narrow technical exercise; instead, they are embedding AI into operations, governance and workforce development from the start.
Why embedding AI into operations, governance and workforce development matters
If KPMG is correct, the struggle to convert strategy into value is an organizational problem as much as a technical one. Embedding AI into operations aligns machine-driven capabilities with the routines and decision points where work actually gets done. Embedding AI into governance creates the rules and oversight needed to manage risk and maintain trust as AI becomes part of standard practice. Embedding AI into workforce development ensures that people and processes evolve together, so technology augments rather than disrupts core business functions.
Viewed together, these three areas form a practical architecture for scaling AI: operations to make models useful at scale, governance to keep their use sustainable and accountable, and workforce development to make sure organizations have the human skills and workflows to exploit AI’s potential. The KPMG survey points to that architecture as the distinguishing feature of enterprises that are “getting it right.”
Different perspectives on the gap between strategy and ROI
- Technologists: For technical teams, the survey’s emphasis on operational integration underscores that deployment, monitoring and iteration matter as much as model design. Without operational hooks, even high-performing models may never move from experiments into repeatable business outcomes.
- Policymakers and governance leads: The survey’s focus on governance highlights the need for organizational rules and oversight as AI moves into routine use. Governance frameworks play a role in shaping how quickly—and safely—AI can be scaled.
- Business leaders and users: From the viewpoint of managers and frontline users, workforce development is essential. The KPMG findings suggest that training, role redesign and change management are not optional extras but core elements of an AI strategy that delivers ROI.
- Adversaries and risk managers: Embedding AI into governance and operations also affects the risk surface. The survey implies that without institutional structures in place, organizations may be more exposed to operational failures, misuse or unintended consequences as AI systems are deployed more broadly.
What this means in practice
The central takeaway from KPMG is straightforward: having a strategy is not the same as having a scalable program. Enterprises that report tangible returns are those that planned for AI as a systems change. They built the operational pathways to integrate AI into day-to-day processes, established governance to guide its acceptable use, and invested in workforce development so employees could actually make use of the new capabilities.
In short, the survey reframes the challenge of AI adoption. Success appears less about finding the next breakthrough model and more about reshaping organizational structures so that AI can be applied repeatedly, responsibly and by people who know how to use it.
If most organizations already have a strategy but only a few are seeing ROI, the question becomes not whether to pursue AI but how to reconfigure operations, governance and workforce development so that strategy leads to sustained value. How quickly enterprises act on that imperative may determine which ones become leaders—and which ones are left chasing results that never materialize.
