Organizations with a clear AI strategy achieve better financial results. Only fifteen percent of the companies surveyed fall into the “AI leader” category, characterized by a structured approach and targeted execution.
The analysis is based on a survey of 2,567 senior executives across 35 countries and 15 industries. Only 15% of participating organizations qualified as “AI leaders,” defined by clear AI strategies, mature operating models and focused execution. These leaders report significantly higher revenue growth and profit margins than other organizations.
“AI accountability now belongs in the boardroom and demands an enterprise-wide agenda,” said Yutaka Sasaki, President and CEO, NTT DATA Group. “Our research shows that a small group of AI leaders already are using AI to differentiate, grow and reinvent how humans and machines create value together.”
Strategy
Leaders treat AI as a core growth engine and rewire their strategy accordingly.- Strategic alignment and speed: AI leaders win by tightly aligning AI with business strategy and turning strategic focus and speed into outsized financial returns.
- Focused end-to-end approach: Top performers focus on high-value domains that unlock disproportionate economic value and redesign workflows end to end.
- Flywheel effect: These front-runners create a cycle where initial investments fuel early success that drives reinvestment for further growth.
- Core reinvention: Growth leaders rebuild core applications with embedded AI rather than limiting themselves to surface-level add-ons.
Execution
AI leaders differentiate through resilient foundations, empowered humans, hardwired adoption and governance, and expert partners.- Secure at scale: AI leaders build scalable and secure stacks, localize or relocate AI infrastructure for private/sovereign AI, and invest to eliminate infrastructure bottlenecks.
- Expert-first AI: These front-runners use AI to amplify the impact of experienced, highly skilled employees rather than replace them.
- Change that sticks: Top performers treat adoption as a company-wide change program and adopt constructive change management to reduce resistance.
- Governed for scale: Leading organizations centralize AI governance, formalize enterprise-wide oversight, and empower dedicated Chief AI Officers (CAIOs) to own risk and align innovation.
- Partner-powered growth: Best-in-class players lean on strategic external collaborators and are open to outcome-based gain-sharing models that accelerate AI value.
