AI”.Inside the Playbooks of Companies Winning with AI

Many enterprises are still grappling with how to embed artificial intelligence (AI) into daily operations in a consistent, value‑driven manner. Yet a handful of firms have already turned AI into a competitive differentiator. New research from NTT DATA maps a “playbook” that details how these AI frontrunners distinguish themselves through rigorous strategic planning, decisive leadership, and disciplined execution across the organization.

The study surveyed 2,567 senior executives across 35 countries and 15 industries. Only 15 % of respondents met the criteria to be classified as AI leaders. Those companies share three core traits: a crystal‑clear vision of AI’s role in the business, a robust operating model that integrates AI at scale, and relentless follow‑through on execution. The data shows that these leaders outpace peers on both top‑line growth and profit margins.

Yutaka Sasaki, President and CEO of NTT DATA Group, summed it up: “AI accountability now belongs in the boardroom and demands an enterprise‑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 strong AI plans

The starkest contrast between leaders and laggards lies in strategic approach. For AI leaders, artificial intelligence is not a peripheral experiment; it is a core growth engine that shapes corporate strategy from the top down.

These firms tightly align AI initiatives with business objectives, prioritizing a handful of high‑impact use cases rather than diluting effort across numerous low‑value pilots. By redesigning entire workflows around AI—rather than tacking on isolated algorithms—they generate a multiplier effect that accelerates both speed‑to‑value and financial performance.

The research describes this as a virtuous flywheel: early, well‑funded AI projects deliver quick wins, which in turn justify additional investment. Over time, the cycle becomes self‑reinforcing, allowing the organization to embed AI deeper into its core processes. Leaders also rebuild critical applications with AI baked in from the ground up, avoiding the pitfalls of retrofitting legacy systems with superficial add‑ons.

How leaders put their plans to work

A solid strategy is only as good as its execution. AI leaders stand out by constructing a resilient technical foundation, fostering a talent ecosystem that amplifies human expertise, and driving organization‑wide adoption through disciplined change management.

Infrastructure Investment
These companies allocate significant capital to secure, scalable platforms capable of handling large‑scale model training and inference. Many adopt hybrid cloud or sovereign cloud architectures to meet data‑privacy regulations while maintaining elasticity for burst workloads. They also streamline data pipelines, eliminating bottlenecks that impede rapid experimentation.

Human‑Centric Augmentation
Rather than viewing AI as a workforce replacement, leaders employ an “expert‑first” philosophy. AI tools automate routine or compute‑intensive tasks, freeing seasoned employees to focus on judgment‑heavy activities such as strategy, negotiation, and creative problem‑solving. This collaboration amplifies productivity without eroding employee morale.

Change Management & Adoption
AI adoption is treated as a long‑term transformation initiative. Leaders roll out comprehensive communication plans, establish AI champions in each business unit, and implement structured training programs. By embedding AI literacy into onboarding and continuous learning pathways, they reduce resistance and embed new capabilities into the corporate DNA.

Governance & Risk Management
Top performers centralize AI oversight, often appointing a Chief AI Officer (CAIO) or an equivalent senior role to own end‑to‑end AI governance. They institute transparent model‑risk frameworks that balance innovation speed with compliance, ethical considerations, and cybersecurity. These controls enable confident scaling across geographies and business lines.

Strategic Partnerships
AI leaders actively partner with leading technology providers, AI research labs, and niche startups. Many adopt outcome‑based contracts that tie vendor compensation to measurable business results, accelerating time‑to‑market while safeguarding against vendor lock‑in.

Abhijit Dubey, CEO and CAIO of NTT DATA, Inc., distilled the recipe: “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. 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 profit and pulling ahead of the market.”