As Generative AI (GenAI) continues its rapid rise, enterprises are grappling with a fundamental question: how do you operationalize this powerful technology across the entire organization? For many, the answer lies in a shift toward a product and platform-led operating model, which integrates AI into the fabric of decision-making, value delivery and innovation.

HCLTech’s latest research report, The Blueprint to AI-Led Operating Model, outlines a compelling vision for how organizations can build the foundations for AI at scale. We sat down with Sadagopan Singam, Executive Vice President and Global Head of SaaS and Enterprise Platform Edge Services at HCLTech, to explore how enterprises are making this shift and what’s holding some of them back.

“The revolution of GenAI inside enterprises is going to be fundamental,” said Singam. “It is going to develop deep roots, and it’s going to touch every part of the organization through its power, versatility and robustness.”

But where should organizations begin? When asked whether technology readiness, leadership alignment or cultural transformation should come first, Singam is unequivocal: none can succeed in isolation. “All three need to happen in parallel,” he explains. “There isn’t anything that can be prioritized better than one another in this case.”

Technology, of course, remains the engine. Enterprises must make foundational choices about large language models, security frameworks and how to manage open, reliable data environments. But even the best tech infrastructure falters without leadership alignment, especially in a world where process change and speed of execution are just as important as the tools themselves. As Singam put it, “Looping the decision with the outcome becomes a critical skill in the new era.”

Perhaps the most crucial is the cultural piece. Singam describes it as “adapting not only once but adapting permanently.” In his view, a GenAI-powered culture requires every individual in the organization to wear a “futuristic lens,” one that embraces continuous change, experimentation and a willingness to let go of legacy thinking.

Funding transformation, not just technology

While the promise of AI is vast, the mechanisms to fund it often remain rooted in the past. HCLTech’s research reveals that only 34% of large enterprises connect funding with value delivery. Singam believes this gap is both a warning sign and an opportunity.

Legacy funding models are a primary obstacle. Project-centric approaches don’t translate well in a GenAI-driven world where outcomes emerge quickly and often unpredictably. “This is progress on steroids,” he said. “You’ll be able to get to the outcomes much faster than what you were even ready for.”

He also points to the challenge of measuring return on investment in a way that reflects AI’s exponential pace. Traditional ROI models are too slow and rigid. Bridging this gap means fostering tighter business-IT alignment and developing a capacity for real-time adaptability. These two traits more common among the minority of organizations successfully scaling AI today.

Why feedback loops matter more than ever

The report highlights that 70% of product-aligned enterprises prioritize customer feedback loops. For Singam, this isn’t just a stat, it’s a signal of a much deeper shift in how work gets done.

Enterprise platforms, he said, are critical to embedding these loops into everyday decision-making. With GenAI’s reach spanning every function, data must flow seamlessly and teams must work collaboratively. That means dismantling silos, integrating performance data in real time and enabling systems that constantly evolve based on new insights.

“The pace of deployment, development and change has shifted,” said Singam. Organizations need to synchronize around that new rhythm. Done well, he added, this kind of feedback-rich environment creates a cycle of continuous improvement, where GenAI supports and shapes outcomes.

The misconceptions about product-centric thinking

Moving to an AI-led, product-aligned operating model requires more than reorganizing teams or tweaking KPIs. It demands a deep rethinking of how decisions are made and outcomes are measured.

Singam often sees organizations underestimating the degree of change required. “Even the organizational charts and the operating models will have to completely change,” he said. Rather than managing by hierarchy, successful enterprises are empowering agile teams that can respond to real-time data and make strategic calls quickly.

Another misconception lies in what he calls “fake agile,” where teams appear to be output-focused but are in fact operating within legacy constraints. These setups might deliver local wins, but they fall short of the enterprise-wide transformation GenAI requires. From talent and tooling to time, true product alignment connects strategy with execution, across every resource and decision point.

Redefining leadership for the AI era

As GenAI reshapes business models, it also reshapes leadership. One of the most striking findings from the report is that 64% of decision-makers believe their leadership doesn’t fully understand how to measure value flow. Singam sees this as a call to action.

The first step, he explained, is to define the organization’s strategic intent around AI as clearly and concisely as possible. From there, it’s about building outcome-based goals and creating interdependencies between teams, functions and systems that reflect real-world value creation, not theoretical metrics.

Leadership, too, must evolve. “Soft is hard and hard is soft inside enterprises,” said Singam, pointing to the increasing importance of empathy, humility and emotional intelligence. Transparency and adaptability are no longer optional. They’re essential traits in a world where GenAI is constantly surfacing new insights and success depends on a leader’s willingness to act on them.

At the same time, mental agility is paramount. As AI automates and accelerates decision-making, executives must raise their own game and make faster, sharper interventions, as well as embracing a level of strategic responsiveness that matches the pace of the technology itself.

Platforms as enablers of a culture of experimentation

One of the most powerful enablers of AI transformation is the enterprise platform itself. Singam believes that platforms democratize access to AI and in doing so, nurture a culture of experimentation that’s vital to long-term success.

“GenAI, by itself, democratizes access,” he said. Tools like low-code/no-code platforms have opened AI development to non-technical users, while the rise of citizen developers and process evangelists has begun to decentralize innovation across the enterprise.

He describes a future where feedback from the frontlines, whether it’s a call center, a supply chain node or a customer success manager, feeds directly into the product roadmap. “GenAI provides an opportunity to get from the street to the boardroom,” he said. “We’re seeing cohorts of citizen developers shaping strategic thinking in real time.”

To make this real, progressive enterprises are investing in sandboxes for safe experimentation, personalized employee experience platforms and self-service tools that allow teams to test, learn and adapt quickly. Knowledge management systems, meanwhile, ensure that insights aren’t lost but shared, which will scale organizational intelligence in step with the AI itself.

The future is product-led, platform-enabled and AI-driven

As the conversation drew to a close, Singam left us with a clear message: GenAI will not just automate the enterprise; it will reinvent it. But getting there requires courage, clarity and a willingness to rethink long-standing norms.

“Organizations must develop a certain ethos,” he said. “One that allows them to get the best value out of GenAI, not just at the center, but at the edges too.”

For those ready to embrace the future, HCLTech’s Blueprint to AI-Led Operating Model offers insights and instruction. And for the leaders willing to transform not only how they operate but how they think, the payoff is nothing short of enterprise reinvention.

Read the full report here