HCLTech Study: How Businesses Drive Revenue Impact with AI

While a staggering 90% of organisations acknowledge that generative and agentic AI are transforming workflows, a mere 18% report that the technology is delivering a significant impact on revenue. 

This stark contrast exposes a critical disconnect between operational progress and tangible business outcomes.

The findings stem from HCLTech’s research report, The Blueprint for AI Leadership, which surveyed 500 business and IT leaders. 

In the study, HCLTech categorises the high-performing 18% as ‘AI Leaders’, whilst the remaining 82% are designated as ‘AI Followers’.

According to the report, AI Leaders are four times more likely to scale agentic and autonomous AI and 63% more likely to secure senior leadership sponsorship. 

Conversely, AI Followers, the lagging enterprises adopting AI without extracting meaningful business value, remain trapped by evaluating AI through narrow efficiency and cost lenses alone.

Pawan Vadapalli, Corporate Vice President and Global Head of Digital Business Services at HCLTech, explains: “The gap between AI Leaders and AI Followers isn’t a single tool, model or platform decision. It’s the ability to make value real for the business, build confidence across the workforce and scale responsibly on modern foundations.”

The blueprint for success

Unlike their lagging counterparts, AI Leaders have seamlessly integrated AI into their core business strategy, established data readiness, and taken a decisive lead in workforce transformation. 

A striking 93% of AI Leaders have implemented structured upskilling programmes, compared to just 20% of AI Followers.

Furthermore, nearly nine in 10 AI Leaders possess an organisation-wide strategy for retraining and upskilling employees, building a far stronger foundation for technology adoption. 

Over half (54%) actively encourage their teams to experiment with AI tools and explore new ways of working.

Sebastian Reiche, Professor of People Management at IESE Business School, says: “Workers are often more willing to adapt than assumed, particularly when they are empowered to shape how tools are integrated into their roles and can see a clear vision of how their work will evolve. In many cases, deeper structural issues are at play.”

Building trust and modern foundations

Confidence in underlying infrastructure also plays a pivotal role in driving outcomes. 

AI Leaders are eight times more likely to trust that their data can support gen AI efforts, highlighting the necessity of data readiness in accelerating progress.

Ultimately, moving from operational experimentation to revenue impact requires a holistic transformation.

Pawan adds: “The organisations 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.”