NTT DATA’s 2026 Global AI Report outlines how leading enterprises convert AI pilots into measurable gains

NTT DATA has released its 2026 Global AI Report: A playbook for AI leaders, presenting new benchmark research on how a small group of “AI leaders” are translating artificial intelligence initiatives into financial and operational results. The study analyses responses from 2,567 senior executives across 35 countries and 15 industries, classifying only 15% of organisations as leaders, those demonstrating a clear AI strategy, mature operating models and focused execution.

According to the report, these top-performing organisations are 2.5 times more likely to achieve revenue growth of more than 10%, and over three times more likely to report profit margins of at least 15%, compared with their peers.

Yutaka Sasaki, President and CEO of NTT DATA Group, said that AI has become a board-level responsibility requiring an enterprise-wide approach. He noted that a small segment of organisations is already using AI to “differentiate, grow and reinvent how humans and machines create value together.”

Strategic characteristics of AI leaders

The study highlights several strategic traits common to high-performing organisations:

• Alignment of AI with business strategy: Leaders embed AI into core strategies and prioritise speed in execution.
• Focus on high-value domains: Rather than dispersing efforts across numerous use cases, they concentrate on areas capable of delivering outsized economic impact.
• A reinforcing “flywheel” effect: Early gains encourage reinvestment, accelerating future outcomes.
• Reinvention of core systems: Leaders embed AI into foundational applications instead of adding AI features superficially.

Execution models that differentiate top performers

The report identifies several execution practices that set AI-focused organisations apart:

• Secure and scalable foundations: Leaders invest in infrastructure that supports private or sovereign AI models and removes bottlenecks.
• Human-centred augmentation: AI is used to enhance the output of experienced employees rather than replace them.
• Structured, organisation-wide adoption: Change management is treated as a formal programme to reduce resistance and ensure sustained use.
• Centralised governance: AI oversight is formalised, often led by dedicated Chief AI Officers responsible for innovation alignment and risk management.
• Strategic partnerships: External partners play a role in accelerating deployment, with some leaders adopting outcome-based collaboration models.

Abhijit Dubey, CEO and CAIO of NTT DATA, Inc., noted that organisations see the strongest impact when they select one or two high-value domains and redesign them end-to-end with AI, supported by modern infrastructure and structured governance.

About the study

The survey was conducted between September and October 2025, capturing insights from senior leaders across technology, manufacturing, banking, financial services, healthcare, consumer sectors and other industries.