Turning AI Ambition Into Reliable Systems
Rohit Sant
SVP - Global Head Digital Services
Firstsource
Turning AI Ambition Into Reliable Systems
Rohit Sant
SVP - Global Head Digital Services
Firstsource
As AI shifts from experimentation to enterprise-grade adoption, the conversation has moved beyond building models to building systems that actually work in the real world. Organizations today are focused on operationalizing AI with precision, trust and measurable business value. This new phase requires leaders who can balance autonomy with accountability and create environments where people and technology strengthen each other. Among the leaders shaping this transition is Rohit Sant, SVP and Global Head of Digital Services at Firstsource, whose career reflects more than two decades of navigating complex transformation, global delivery and the evolution of digital-first operating models. In his professional journey, Rohit has worked in engineering-led environments, global collaboration structures, and enterprise-scale modernization programs that have enabled organizations to adopt new technologies responsibly. These milestones helped him develop a leadership style rooted in clarity, learning and real-world impact, whether he was guiding teams through AIdriven automation, cultivating cross-functional problem solving, or creating systems that deliver consistent outcomes at scale. This foundation continues to shape how he steers AI teams toward solutions that are reliable, accountable and aligned with business realities. In an exclusive interaction with TradeFlock, Rohit shares his journey, the milestones that shaped his approach and the possibilities that excite him most in the next era of AI.
What moments from your 27-year journey still shape how you lead AI teams?
Across nearly three decades, a few experiences have continued to shape how I lead AI teams. My early years at Infosys instilled in me an engineering-led discipline, characterized by rigor, quality, and structured problemsolving, which serves as the bedrock of innovation. Global delivery roles later taught me how distributed teams win through shared purpose, clarity, and trust. At Tech Mahindra, a culture of constant reskilling shaped how I think about leadership in fast-moving fields like AI: curiosity, adaptability, and accountability must grow together. Those experiences converged into three pillars that I still carry today: an engineering discipline, a global scale, and a learning-first mindset. They guide how I help teams build AI that is responsible, reliable, and ready for realworld impact.
Share a tough leadership moment and the simple habit that helped you stay steady.
One of my toughest phases came during a large transformation program where we pivoted an entire global delivery organization toward AI-driven automation. Redefining roles, reskilling thousands, and making decisions that impacted careers brought both intensity and responsibility. What kept me steady was a small daily habit. Every morning, before the day accelerated, I spent 15–20 minutes reflecting on three things: what mattered most, who needed clarity from me, and what I could learn from yesterday’s missteps. That quiet pause became my leadership anchor. It helped me replace urgency with empathy and pressure with purpose. Even today, in an AI landscape that moves by the quarter, that reflection ritual keeps me grounded and intentional.
Which emerging AI trend excites you most right now?
The convergence of outcome-centric GenAI and Agentic AI excites me most. It reflects the shift from copilots to co-workers that can reason, act, and close loops autonomously. Agentic systems connect intent to action, orchestrating tasks, invoking tools, validating outcomes, and learning from feedback in real-time. At Firstsource, we are building an Agentic ecosystem that blends GenAI’s creativity with operational intelligence, enabling AI to drive outcomes while remaining accountable and autonomous.
"It is a space where autonomy meets accountability, and it is redefining how AI delivers measurable business value."
Which AI trend in India feels like a true game-changer?
India’s most transformative shift is the rise of Small and Large Reasoning Models (SLMs and LRMs) and how seamlessly they are being embedded into business-centric Agentic AI platforms. The country is moving from experimentation to enterprise-wide transformation. SLMs are becoming the fast, secure, costefficient intelligence layer that enterprises can domain-tune for BFSI, telecom, healthcare, manufacturing, and retail. LRMs bring the deep reasoning and orchestration needed for complex decision chains. Together, powered through Agentic AI, they enable true end-to-end automation, augment human expertise, and unlock new productivity frontiers. In short, India’s AI revolution is shifting from pilots to platforms, and the synergy of SLM + LRM + Agentic AI is the true game-changer.
What lesson from outside work has shaped your leadership in AI?
A defining leadership lesson came from time spent observing wildlife. In nature, balance matters more than hierarchy; every species has its role, and progress comes through interdependence. That perspective fundamentally changed how I lead in the tech and AI sectors. Just as ecosystems thrive on harmony, AI teams thrive when empathy, diversity, and respect shape how we build and collaborate. Whether it is data scientists, designers, or engineers, the goal is to create an environment where each person can flourish at their own rhythm. The biggest insight nature taught me is simple: progress is collective. And in a world increasingly driven by algorithms, staying grounded in human connection is what makes technology truly meaningful.
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