AI adoption is widespread, but only 18% of enterprises see meaningful revenue gains: HCLTech report

Artificial intelligence is becoming a part of day-to-day business operations across enterprises, but most companies are yet to translate those investments into meaningful business returns, according to HCLTech’s latest global research report.

The study, conducted with Raconteur among 500 enterprise decision-makers, found that 90% of organizations said generative AI and agentic AI are transforming workflows. Another 91% reported better access to data, while 90% said AI has improved productivity and knowledge sharing. Despite that, only 18% said AI has had a significant impact on revenue.

According to the report, “a persistent gap remains between what they expect AI to deliver and what they can realistically achieve.” It adds that this gap extends beyond technology to leadership, ownership and an organization’s ability to drive change.

AI Leaders pull ahead

The report classifies only 18% of surveyed organizations as AI Leaders, while 60% fall into the AI Followers category. It says AI Leaders are not simply reducing costs through AI, but are using the technology to drive growth, innovation and better customer experiences. AI Followers, meanwhile, continue to lag in adopting higher-value use cases.

Nearly 73% of AI Leaders said AI projects begin with clearly defined business objectives and measurable outcomes, compared with 22% of Followers. Similarly, 63% of Leaders said senior management actively champions AI adoption, versus 36% of Followers. “This visible sponsorship does more than signal intent; it helps align priorities, unlock investment and create the conditions for AI initiatives to move beyond isolated pilots. Where leadership is less engaged, AI efforts are more likely to remain fragmented, with weaker links to business outcomes and limited momentum,” the report noted.

The report also notes that AI Leaders are four times more likely to scale agentic and autonomous AI across the enterprise. “The winners are not simply those deploying more models or launching more pilots, but those using AI to redesign the enterprise itself,” it says.

 Companies still judge AI by efficiency

Many organizations continue to measure AI through operational gains rather than business transformation, as about 28% of respondents said they evaluate AI using process speed, while 23% focus on cost savings and productivity improvements. According to the report, this gives only a partial picture of AI’s value, especially in areas such as revenue growth, product innovation and long-term competitiveness.

Overall, 60% of organizations said their AI investments are meeting expectations, while 18% reported returns that significantly exceeded expectations. Companies with annual revenue exceeding $10 billion were almost seven times more likely to report AI returns above expectations.

Legacy systems remain a hurdle

The report identifies legacy enterprise applications as one of the biggest barriers to scaling AI. ERP systems were cited most frequently, with 35% of respondents saying they significantly limit AI adoption. Finance systems followed at 32%, while supply chain systems stood at 26%. AI Followers reported greater challenges than Leaders across these core applications.

“Organisational readiness adds a second layer of constraint. Leaders are significantly more likely than Followers to believe they are investing sufficiently in organizational and talent readiness (67% vs. 37%), highlighting a clear divide in how prepared organizations feel to support AI-driven change,” the report noted.

The maturity of core enterprise applications is limiting organisations’ ability to adopt and integrate AI. The most significant bottlenecks sit within systems that underpin core business operations, particularly ERP (35%), finance (32%) and supply chain (26%), where legacy architectures and tightly coupled processes make integration more difficult.

Whereas functions such as CRM (20%) and product development and innovation tools (20%), where systems are typically more modular and already closer to customer-facing use cases, are less likely to act as constraints. “This suggests that organisations are making faster progress in areas where AI can be layered onto existing workflows, but face greater friction where deeper integration into core systems is required.”

Leaders report slightly fewer constraints across most systems, particularly in supply chain (17% vs. 29%) and finance (24% vs. 37%), indicating a greater ability to navigate or modernize complex environments.

Organisations are more comfortable with AI that assists or augments human work such as content generation or customer experience optimization than with deploying more autonomous systems. While Agentic AI is attracting significant attention, fewer than half (45%) say they are using it effectively for workflow automation and orchestration, rising to 71% among Leaders but just 44% of Followers.

Workforce readiness remains uneven

While 79% of organizations said they are confident about training employees for AI-driven roles, only 33% have a company-wide workforce transformation strategy. The gap is wider between Leaders and Followers, with 93% of Leaders having structured upskilling programmes compared with just 20% of Followers.

“AI has entered a decisive phase, and success will come down to how well organizations bring people, data and technology together. The organizations pulling ahead are not just running more pilots; they are rethinking how the business works, embedding AI into everyday decisions and workflows. It is this coordinated shift across leadership, culture and foundations that turns AI from a tool into real, long-term advantage,” said Pawan Vadapalli, Corporate Vice President and Global Head, Digital Business Services at HCLTech.