Many companies are still thinking about how to use AI consistently and practically, but a small group is already getting ahead. A new study from NTT DATA presents a playbook that shows how these “AI leaders” distinguish themselves with solid plans, firm decisions and a disciplined approach to developing and using AI within their organizations.
The results come from a survey of 2,567 senior executives across 35 countries and 15 industries. Only 15% of organizations meet the criteria required to be considered leaders in AI. These companies share a few traits: a clear direction on the place of AI in their business, a solid operating model and consistent monitoring. They also reported higher revenue growth and stronger profit margins than all other study participants.
Yutaka Sasaki, president and CEO of NTT DATA Group, put it simply: “Responsibility for AI now rests with the board of directors and requires a company-wide agenda. Our research shows that a small group of AI leaders are already using AI to differentiate, grow, and reinvent how humans and machines create value together.”
The playbook behind solid AI plans
One of the most obvious differences between leaders and others is how they approach strategy. For these companies, AI is not a side project or a tool added to existing work. They see it as a key driver of growth and adjust their plans accordingly.
A major advantage for these leaders is the extent to which they connect AI to their business goals. This alignment helps them move faster and stay focused, leading to better financial results. They also focus on a few high-value areas of the business rather than spreading resources too thin. By redesigning entire workflows around AI, they unlock more value than if they had made only small improvements in scattered parts of the organization.
The report describes this as a kind of flywheel: early investments generate early gains, which then encourage more investments. Over time, this cycle becomes self-reinforcing. Executives are also rebuilding important applications by integrating AI, instead of adding basic AI functionality to legacy systems. This approach helps them see a deeper impact and prepares the organization for long-term gains.
How leaders execute their plans
A good plan only works if it is backed by rigorous execution. AI leaders are distinguished by the foundations they build, how they support their people, and how they drive adoption throughout the organization.
These companies are investing in secure, scalable systems capable of supporting large AI workloads. In some cases, they are modifying or localizing their infrastructure to meet private or sovereign AI needs. They are also working to remove bottlenecks from the system so that teams can move without obstacles.
Rather than using AI to replace workers, leaders are using it to help experienced employees do higher-value work. This “expert first” approach allows teams to use their judgment while letting AI handle complex or time-consuming tasks.
AI leaders also focus on adoption as a long-term change effort. They view it as a company-wide change, supported by clear communication and structured change management. This helps reduce reluctance and encourages regular use of AI at all levels.
Governance is another major difference. Large organizations centralize their oversight of AI, assign clear responsibilities to leadership positions such as Directors of AI, and build processes that help balance innovation and risk. These systems allow them to scale AI with more confidence.
Partnerships also play a major role. Large companies often bring in outside experts and are open to agreements linking results to shared success. This helps them move forward more quickly while keeping their goals in sight.
Abhijit Dubey, CEO and CAIO of NTT DATA, Inc., summarized the path forward: “Once AI and business strategies are aligned, the most effective decision is to choose one or two areas that deliver disproportionate value and reimagine them end-to-end with AI. Supporting this focused end-to-end approach with strong governance, modern infrastructure, and trusted partners is how today’s AI leaders turn pilot projects into profits and get ahead of the market.”
(Photo by Igor Omilaev)
See also: OpenAI: Enterprise users trade AI drivers for deep integrations
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