From Pilots to Profit: What NTT DATA's 2026 Global AI Report Means for the C-Suite
Most companies are still stuck in pilots. A small group isn't. NTT DATA's 2026 Global AI Report shows only 15% of organizations qualify as "AI leaders," and they're already posting higher revenue growth and better margins.
The gap is widening because leaders run AI like a business function, not a side project. As one executive put it, "AI accountability now belongs in the boardroom and demands an enterprise-wide agenda."
What AI leaders do differently (Strategy)
- Tie AI to the P&L: They link AI directly to business strategy and move fast on a few priorities that matter.
- Focus on one or two high-value domains: Pick the process clusters with outsized economic upside and redesign end to end, not just a feature here or there.
- Build a flywheel: Early wins fund the next wave-capital, talent, and data compounding into advantage.
- Rebuild the core: They rework core applications with embedded AI instead of lightweight add-ons.
Execution that scales (Operating Model)
- Secure at scale: Modernize the stack, localize/relocate infrastructure for private or sovereign AI, and remove bottlenecks.
- Expert-first AI: Use AI to amplify experienced talent-don't try to swap them out.
- Change that sticks: Treat adoption as a company-wide change program with hands-on enablement, not a memo.
- Governed for scale: Centralize AI governance, set enterprise-wide oversight, and empower a CAIO to own risk and velocity.
- Partner-powered growth: Bring in strategic partners and be open to outcome-based gain-sharing.
Quote: "Once AI and business strategies are linked, the single most effective move is to pick one or two domains that deliver disproportionate value and redesign them end-to-end with AI," said Abhijit Dubey, CEO and CAIO, NTT DATA, Inc.
Your 90-day plan
- Pick the battleground: Select 1-2 domains (e.g., underwriting, pricing, supply planning, claims, customer service) with measurable upside.
- Stand up governance: Name a CAIO, define decision rights, and adopt a risk framework with model, data, and security controls.
- Fix the plumbing: Confirm data access patterns, latency, privacy needs, and capacity. Budget to remove the top two infrastructure constraints.
- Back your experts: Pair senior operators with AI teams; set weekly adoption targets and frontline feedback loops.
- Choose partners for outcomes: Structure contracts around KPIs (e.g., cycle time, cost per case, conversion lift) and gain-share.
- Make it real: Ship a production-grade workflow redesign in 12 weeks with clear before/after metrics.
Metrics that prove it's working
- Time-to-value from idea to production (weeks, not quarters)
- Frontline adoption rate and task coverage
- Unit cost reduction and cycle-time improvement
- Infra utilization and model performance stability
- Policy compliance incidents (target: zero material breaches)
- Revenue and margin uplift in the chosen domains
Research snapshot
The report draws on a survey of 2,567 senior leaders across 35 countries and 15 industries, fielded in September-October 2025. Only 15% met the bar for "AI leaders," defined by clear strategies, mature operating models, and focused execution.
Why this matters now
AI is moving from experimentation to core business. Leaders are converting early bets into compounding advantage by linking AI to strategy, rebuilding the work, and installing governance that lets them scale safely.
Quote: "A small group of AI leaders already are using AI to differentiate, grow and reinvent how humans and machines create value together," said Yutaka Sasaki, President and CEO, NTT DATA Group.
For governance reference points, see the NIST AI Risk Management Framework here. Read the full source release on Business Wire here.
About NTT DATA
NTT DATA is a $30+ billion business and technology services company serving 75% of the Fortune Global 100 with AI, cloud, security, connectivity, data centers, and application services across 70+ countries.
Next step for your team
If you need structured upskilling for executives and operators running these programs, explore role-based AI course paths here.
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