AI leaders surge ahead in growth & profitability

NTT DATA has identified a small group of companies that are pulling ahead on growth and profitability from artificial intelligence deployment, in new global research that tracks how executives apply AI across their businesses.

The study finds that the top 15% of surveyed organisations, described as “AI leaders”, are 2.5 times more likely than peers to post revenue growth above 10%. These organisations are also more than three times more likely to achieve profit margins of at least 15% from AI initiatives.

The findings are set out in NTT DATA’s 2026 Global AI Report, which the company describes as a playbook for senior decision-makers. The research draws on a survey of 2,567 senior executives across 35 countries and 15 industries, including technology, manufacturing, banking, financial services, healthcare and consumer sectors.

Respondents included C-suite leaders, senior executives and other senior staff. Only 15% of participating organisations met the criteria for AI leadership. The classification is based on the presence of a clear AI strategy, a mature operating model and evidence of focused execution.

Yutaka Sasaki, President and CEO of NTT DATA Group, said the findings underline the strategic nature of AI decisions at large companies.

“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.”

The report says AI leaders embed AI into core business strategy rather than running isolated experiments. These organisations treat AI as a primary growth driver. They rework strategic plans and resource allocation around that view.

One pattern is tight alignment between AI projects and business objectives. The research states that leading companies match AI investments to specific strategic priorities. These companies also move more quickly from concept to deployment.

The report describes a “flywheel effect” in these organisations. Initial AI investments generate early financial gains. Those results fund further AI work across additional domains.

AI leaders also concentrate on a small number of high-value areas. They select business domains that can unlock disproportionate economic value. They then redesign processes and workflows in those areas from end to end with AI embedded throughout.

Another feature is a focus on rebuilding core applications. Leading firms integrate AI into the foundations of critical systems. They do not confine AI usage to surface-level add-ons or isolated tools.

The research highlights differences in execution between leaders and the rest of the sample. It finds that advanced organisations invest in secure and scalable AI infrastructure. They address capacity constraints in data platforms, compute and networking.

Some leaders localise or relocate AI infrastructure. The report links this trend to demand for private or sovereign AI environments and data controls.

Human capital is another distinguishing factor. NTT DATA says leaders apply AI first to amplify the work of experienced and highly skilled employees. These companies design AI systems that extend expert judgement and productivity instead of aiming for direct replacement.

The report states that adoption is treated as a company-wide change programme. Leading organisations bring in structured change management. They tackle resistance, training and new ways of working as integrated elements of AI deployment.

Governance is more formalised among AI leaders. The study finds that these firms centralise AI oversight across the enterprise. They put in place common policies on risk, ethics, compliance and performance measurement.

Many of these organisations create a dedicated Chief AI Officer (CAIO) role. This executive owns AI-related risk and coordination. The role also aligns innovation efforts with business outcomes across departments.

Partnerships feature heavily in the approach of top performers. The research notes that leaders work with strategic external collaborators across the AI value chain. Some adopt outcome-based gain-sharing agreements that tie partner rewards to measurable AI-driven results.

Abhijit Dubey, CEO and CAIO, NTT DATA, Inc., said companies that move beyond pilots and proofs of concept are taking a selective approach to where they deploy AI at scale.

“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.”

NTT DATA said the research offers a benchmark for organisations that want to compare their progress with peers. The company stated that the report will inform its own work with clients on AI strategy, governance and infrastructure over the coming years.