As organizations accelerate their shift toward AI-led operating models, the focus is increasingly turning to the most crucial driver of success: people. HCLTech’s latest research, The Blueprint to AI-led Operating Model, sheds light on talent's central role in enabling this transformation and the challenges leaders must overcome to harness it effectively.
In a recent HCLTech Trends & Insights Podcast, Satish Srinivasan, AVP of Digital Business Services at HCLTech, offered strategic insights for enterprise leaders navigating this shift.
The people problem: Structural inefficiencies and frustrated teams
The research reveals that a staggering 95% of decision-makers are dissatisfied with their current team structures. According to Srinivasan, this dissatisfaction stems from three core challenges: "One is [that] making changes takes too long, especially in the process...37% of people that we researched are saying this. The second point is managing growth and scale...35% of them are saying that. And the third is leadership engagement or inadequate leadership...20% of them are saying that."
Legacy structures often can't keep pace with business needs, and outdated hierarchies hinder agility and collaboration. Addressing these issues demands not only rethinking roles and workflows but also re-centering the organization around value delivery.
From silos to value streams: Rethinking organizational design
Transitioning to a product-aligned model begins with customer-centricity.
"The fundamental factor is, how close are we to customers, right? Do we understand the customer well, and are we aligned with the right goals to solve the most relevant customer problems," asked Srinivasan.
The solution lies in value stream alignment, a model that organizes work around customer value rather than departmental silos. But many organizations are still struggling:
"64% of the respondents in our research said that their organization doesn't understand the value alignment...If we align to value stream thinking and customer needs, that will significantly be the first step to improve collaboration."
Equally critical is role clarity, particularly in fluid, cross-functional teams. Clear responsibilities combined with hierarchical OKRs (Objectives and Key Results) ensure every role is contributing toward measurable customer outcomes.
Tackling resistance to change: Principles over processes
Organizational change often stalls due to resistance at all levels. The report finds 37% of employees are frustrated with slow change processes. Srinivasan suggests overcoming this with a mindset shift.
"Principles need to be prioritized over processes in the product-aligned operating model," he says.
Resistance stems from three factors: lack of personal incentive, fear of failure and a disconnect from purpose. Leaders must communicate the “what’s in it for me” for every stakeholder, foster a safe environment for experimentation and clearly link individual contributions to broader customer outcomes.
"How do we bring down the fear of failure and give a little bit of freedom," asked Satish. "Prioritize innovation over predictability."
Driving cross-functional collaboration and trust
Rigid governance models do not support the fluidity needed in product-aligned environments. Instead, businesses must focus on building trust and enabling open communication across functions.
"Over 32% of the people we surveyed said increasing trust is fundamental...and over 39% said they need better communication channels to drive better collaboration," highlighted Srinivasan.
To break down silos, leaders must ensure transparency across customer insights, product performance and team outcomes. Sharing this information builds mutual trust and enables timely, data-informed decisions.
"We need to ensure that better communication channels are set all the way across...improving trust with transparency, collaboration will automatically happen," he said.
The role of leadership: From alignment to activation
Leaders must go beyond setting direction. Instead, they must actively align product goals with business outcomes. Yet, 51% of organizations believe leadership could do more in this area. Srinivasan points to a critical enabler:
"One of the key developments they can leverage is, of course, AI...We can drive better customer insights...and understand how the product performs," he says.
Beyond insights, leadership engagement must be consistent and action-oriented. Notably, medium-sized companies are outperforming larger peers in aligning funding and strategy to value delivery.
"They should also be looking at data on what is working and what is not working...and make the right decisions to enable this," he says.
AI as a catalyst: Enabling strategy, observability and governance
From strategy and operations to governance, AI’s role extends across the transformation journey. Srinivasan outlines three primary AI application areas:
- Strategy and alignment: “We are starting to leverage data in terms of the customer goals...what we call the DFV framework, desirability, feasibility, and viability...Now it's becoming more empirical and more data driven.”
- Business observability: “We are implementing an observability-led solution... connecting application telemetry to business KPIs.”
- Governance and risk detection: “Even before a failure happens...we are able to leverage AI to understand these patterns...what we call this, the failure mode analysis.”
These capabilities offer leaders the ability to make proactive, data-backed decisions, which is critical for the speed and precision demanded by today’s markets.
Building an AI-augmented workforce
The transition to AI-led models necessitates a shift in workforce capability. According to Srinivasan, organizations must invest in both upskilling and cultural integration. “We are training our talent pool to do this...It's not about one versus the other. It's about one complementing the other.”
He outlines a maturity model of AI-assisted, AI-augmented and AI-automated work: "In the first model, AI gives insights. In the second, AI works collaboratively. In the third, tasks can be autonomously done by AI."
To thrive, employees must be equipped not just with technical skills, but with the confidence to trust and collaborate with AI agents, fostering a workplace where people and technology drive business value in tandem.
People-centered transformation
The shift to a product-aligned, AI-led operating model is not merely a technical challenge, it’s a people-centered transformation. As HCLTech’s research and Srinivasan's insights highlight, success depends on empowering teams with clarity, trust and alignment, backed by strategic use of AI.
Leaders must step into their role as enablers, championing value stream alignment, breaking down silos, embedding cross-functional collaboration and continuously investing in people. The organizations that do this well will not only survive transformation but also lead it.
