When everything moves at once, where do you start with AI?
Read enough about the future of AI and it's easy to feel overwhelmed. Start experimenting, and excitement quickly mixes with unease, a million questions about what comes next. No one has a crystal ball. No one truly knows. So, what can you actually do, right now?
KPMG's global survey of 1,750 senior leaders across 20 countries - as well as perspectives from KPMG alliance organizations including ServiceNow, Workday, SAP, and Oracle - offers a foothold.
The uncomfortable headline: transformation activity has never been higher, yet only 14% of organizations call themselves top performers and just 26% strongly agree AI has improved their growth. The constraint is no longer ambition, budget, or technology, it's that AI is deployed faster than organizations can rethink how they work. Gains stay local - a faster task here, a better forecast there - instead of adding up across the enterprise.
Part of the answer is concrete: stop fitting AI into old structures. Are you genuinely redesigning how work flows end-to-end across your value streams or just layering new tools on top of the way things already run? And as decisions become AI-assisted, do you even know how the people around you are reaching theirs? The rest is a capability the survey calls orchestration: with several transformations running at once, coordinating them through committees isn't enough. It means steering actively from the center - where to accelerate, where to align, and, the hard part, where to stop - so initiatives reinforce each other instead of quietly competing for the same people and budget. Think less of a committee, more of a conductor. It's a shift that changes what you'll ask of leadership, your workforce, and governance.
This is the real question for public services and financial institutions in Belgium, where reform, cost discipline and urgency collide. Not "are we doing enough with AI?" but "are we organized to turn it into value?"
Read our survey-based Transforming the Enterprise 2026 paper to see what leaders worldwide are thinking and contact KPMG to explore what it means for you.
Key findings
Organizations are investing heavily in AI, digital capabilities, and operating model transformation. Yet enterprise-wide outcomes remain uneven, with many struggling to translate transformation activity into sustained enterprise performance.
The capability gap is widening
Organizations increasingly understand which capabilities will shape future competitiveness and long-term enterprise value creation. Few believe they have built them at enterprise scale.
Trust is recognized as critical, but not consistently embedded
60% view trust and governance as a strategic differentiator, and only 28% measure operational or revenue outcomes tied to trusted AI.
Early AI gains are exposing deeper operational constraints
AI is accelerating productivity and experimentation, but many organizations are layering AI onto fragmented workflows and disconnected systems. Sustained value depends on redesigning work, decision-making, and execution across the enterprise, supported by stronger enterprise AI strategy, enterprise AI governance, and enterprise trust.
Enterprise orchestration is becoming the defining leadership capability
Organizations pulling ahead are not necessarily transforming more than their peers. They are better able to align priorities, integrate execution, and direct transformation coherently across interconnected systems, workflows, and decisions.
Three priorities for orchestrating enterprise transformation
Transforming the Enterprise
Discover how organizations can unlock growth, speed, resilience, and competitive advantage
About the research
Transforming the Enterprise 2026 is based on a global survey of more than 1,750 senior transformation leaders across 20 countries, conducted in February 2026. Respondents include C-suite executives and functional leaders across Finance, Front Office, HR, Supply Chain, Risk, and Technology.
