NTT DATA 2026 AI analysis points to maverick playbook moves
AI is here, but is it?
Through the rise and development of predictive, generative and agentic AI services, we have heard so many vendors (and indeed AI advocates and evangelists) tell us about the rise of new platforms, paradigms and processes… but firms have been widely reported to struggle with real world practical implementations that go beyond prototyped experimentation.
All that said, the chasm between still-nascent AI functions and enterprise systems reinvention is not news; we know there’s an architectural disconnect and we know that tech vendors are working to simplify, unify and perhaps even transmogrify the way their products (by which we mean services) are coming to market.
In the wake of NTT’s R&D Forum 2025 conference and essentially practical and hands-on exhibition showcase, NTT DATA has detailed its 2026 Global AI Report: A playbook for AI leaders..
The playbook is based on the company’s benchmark research and claims to be able to reveal how AI leaders (by which we can infer individual people, teams, or whole departments or organisations) are separating themselves from their competitors through strategy and execution.
What is an AI leader?
The analysis is based on a survey of 2,567 senior executives across 35 countries and 15 industries. Only 15% of participating organisations qualified as “AI leaders” here, a position defined by clear AI strategies, mature operating models and focused execution.
These leaders report significantly higher revenue growth and profit margins than other organisations.
“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.”
Sasaki and team say that leaders in this space treat AI as a “core growth engine” and rewire their strategy accordingly. The report clarifies the suggestion that AI leaders win by tightly aligning AI with business strategy and turning strategic focus and speed into outsized financial returns.
High-value domains
Top performers focus on high-value domains that unlock disproportionate economic value and redesign workflows end-to-end. This leads to what NTT DATA calls a “flywheel effect” i.e. these front-runners create a cycle where initial investments fuel early success that drives reinvestment for further growth.
NTT DATA does not specify what “high-value domains” for AI might be in exact terms, but we can suggest that this means highly definable industry-specific applications such as those in healthcare, legal and financial (possibly education too) and those that are the most ethical, trustworthy and quantifiable. This is not meant to be a defining statement, but perhaps something that we should analyse further in the future.
The NTT DATA team says that growth leaders rebuild core applications with embedded AI rather than limiting themselves to surface-level add-ons.
“Once AI and business strategies are aligned, 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. “Supporting this focused, end-to-end approach with strong governance, modern infrastructure and trusted partners is how today’s AI leaders are turning pilots into profits and pulling ahead of the market.”
Elements of execution
The company says that AI leaders differentiate through resilient foundations, empowered humans, hardwired adoption and governance and expert partners. The following points summarise the takeaways here:
- Secure at scale: AI leaders build scalable and secure stacks, localise 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 organisations centralise AI governance, formalise 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.
The survey was conducted between September and October 2025.
Respondents included C-suite, senior executives and other senior staff from enterprises spanning technology, manufacturing, banking, financial services, healthcare, consumer and other sectors.
Image credit: NTT DATA, Inc.