Rohit Kumar, SVP and Chief Operating Officer, Cognizant, on scaling AI from pilots to enterprise operations.
As one of the world’s leading professional services firms, Cognizant operates at the intersection of technology, operations, and large-scale talent transformation. With deep expertise across digital engineering, consulting, and managed services, the company continues to reshape how global enterprises run, adapt, and grow in an increasingly AI-driven environment.
As GenAI moves from isolated pilots to enterprise-wide deployment, Cognizant is reimagining operations not as a support backbone, but as a real-time, data-driven “strategic cockpit” that directly influences margins, responsiveness, and resilience. This evolution goes beyond automation, signaling a fundamental rewiring of operating models, governance frameworks, and workforce strategies at scale.
In a conversation with Jatinder Singh, Editor, CIO&Leader, Rohit Kumar, SVP and Chief Operating Officer, Cognizant, highlights how the company is industrializing GenAI across its value chain, embedding responsible AI governance, and redesigning talent into an intelligent, demand-responsive supply chain. He also explains why India remains central to Cognizant’s delivery and innovation engine, how Tier-2 expansion is reshaping the future delivery model, and the practical lessons CIOs can apply as they scale AI with trust, measurable ROI, and sustained business impact. Excerpts from the interview follow.
CIO&Leader: Cognizant’s operations are evolving from a support backbone to a “strategic cockpit.” How are you using data and GenAI to transform operations into a value-creation function that directly influences business outcomes such as margins, responsiveness, and resilience?
Rohit Kumar: Cognizant is fundamentally rewiring its operating model. We are moving from a traditional enabling function to a real-time strategic cockpit, where data, automation, and GenAI actively provide insights and enable faster decision-making by connecting the dots.
By embedding GenAI into core workflows, we are compressing cycle times, shifting manual effort to automated, self-optimizing processes, and enabling our teams to focus on higher-value decisions. This transition is not incremental; it is a structural shift designed to improve margins, enhance responsiveness, and deliver greater client value by converting operations into an intelligent orchestration layer.
CIO&Leader: With GenAI embedded across your value chain, what frameworks are in place to ensure AI decision-making remains explainable, ethical, and compliant—especially when automation impacts talent and delivery decisions?
Rohit Kumar: We have institutionalized a responsible AI governance fabric across the company, spanning model transparency, lineage tracking, bias audits, and compliance with emerging global regulatory requirements.
Automation and AI are designed to augment, not replace, critical human judgment. In our talent and delivery systems, GenAI-enabled work is always paired with clear accountability, explainability protocols, and ethical guardrails. This ensures that as we scale AI, we also scale trust.
We have institutionalized a responsible AI governance fabric across the company, spanning model transparency, lineage tracking, bias audits, and compliance with emerging global regulatory requirements.
CIO&Leader: You’ve described talent as central to operational transformation. How is Cognizant reimagining workforce planning, forecasting, and reskilling models to create an intelligent “talent supply chain” that adapts in real time to business needs?
Rohit Kumar: We are redesigning our global talent architecture around a skills-based, demand-responsive operating model. Workforce planning, forecasting, and deployment are increasingly algorithmic, enabling us to match the right skills at the right time with unprecedented precision.
Continuous reskilling at scale ensures our teams evolve in step with client needs and shifting technology trends. This is how we build a resilient, future-ready talent ecosystem that fuels our transformation as an AI Builder company.
CIO&Leader: India contributes nearly 70% of Cognizant’s delivery strength and is seeing rapid Tier-2 expansion. How does the “move work to talent” strategy reshape the delivery model, both in terms of cost optimization and regional innovation?
Rohit Kumar: India is the strategic engine of Cognizant. With nearly 70% of our delivery anchored here, India offers unmatched talent density, execution scale, and innovation depth. Our Tier-2 expansion strategy is not just a cost lever; it is a nation-building lever. By expanding into emerging cities, we are:
- Unlocking new, high-quality talent pools
- Improving delivery economics
- Building more resilient operations
- Creating local career opportunities by taking work to where people are
Continuous reskilling at scale ensures our teams evolve in step with client needs and shifting technology trends. This is how we build a resilient, future-ready talent ecosystem that fuels our transformation as an AI Builder company.
CIO&Leader: Many enterprises struggle to move from pilots to scaled AI deployment. How is Cognizant ensuring that AI industrialization is consistent, measurable, and embedded across operations?
Rohit Kumar: The industry’s biggest challenge is not AI adoption, it is AI industrialization. At Cognizant, we have moved well beyond isolated pilots to a modular, enterprise-level framework built on standardized tools, delivery playbooks, and AI maturity protocols aligned with work archetypes.
AI is now woven into multiple layers of delivery, allowing us to scale use cases predictably and convert productivity gains into measurable business value.
CIO&Leader: Could you elaborate on the Gen-C talent model, how it combines human potential with GenAI tools, certifications, and ecosystem partnerships to create a future-ready workforce?
Rohit Kumar: At Cognizant, creating opportunities for new talent is fundamental to building the future of both our company and our industry. As technology evolves, we see it as our responsibility to ensure the next generation of digital natives enters the workforce with the skills, confidence, and platforms needed to thrive.
Our Gen-C talent model reflects this philosophy. It brings together campus graduates, experienced delivery leaders, certified AI practitioners, and a strong ecosystem of technology and academic partners to create an integrated, future-ready workforce.
We have redesigned the entry experience for Gen-C graduates, who:
- Are trained on GenAI tools and certifications from day one
- Work in AI-enabled delivery pods
- Collaborate with senior practitioners early in their careers.
- Gain exposure to applied client work far earlier than traditional models.
This creates a multi-layered, AI-fluent talent engine that blends fresh thinking with deep expertise.
CIO&Leader: As operations become increasingly AI-driven, where do you see the enduring value of human judgment and creativity? How do you design systems that balance automation with human oversight?
Rohit Kumar: Even as we automate more processes, human judgment remains irreplaceable. The opportunity ahead lies in designing AI-augmented operating systems that amplify AI’s speed and scale by leveraging creativity, contextual judgment, and ethical reasoning.
We balance automation with human oversight to ensure agility without compromising trust. We also assess the risk–benefit impact of decisions to determine the appropriate level of human involvement—an approach that aligns with how we expect regulatory frameworks to evolve.
CIO&Leader: From your experience transforming operations at scale, what lessons can CIOs apply to drive AI-led efficiency, operational resilience, and data-driven decision-making?
Rohit Kumar: The most important lesson is to anchor AI investments to strategic value pools rather than pursuing isolated or experimental use cases. AI delivers the most significant impact when it is directly tied to core business outcomes, such as margin improvement, service quality, speed, and resilience.
Equally critical is building high-performance, cross-disciplinary teams that bring together IT, data, operations, and business leaders around shared objectives. AI transformation cannot sit within silos; it requires tight alignment between technology and business decision-makers to scale effectively.
Finally, strong data governance and clarity in decision ownership are non-negotiable. Without consistent data standards, accountability, and transparent decision-making frameworks, AI initiatives tend to fragment, limiting their enterprise-wide impact. Institutionalizing these foundations ensures AI-driven insights translate into confident, repeatable decisions at scale.
At Cognizant, we have moved well beyond isolated pilots to a modular, enterprise-level framework built on standardized tools, delivery playbooks, and AI maturity protocols aligned with work archetypes.
AI is now woven into multiple layers of delivery, allowing us to scale use cases predictably and convert productivity gains into measurable business value.
CIO&Leader: How should CIOs integrate GenAI into IT and business processes without creating silos or overwhelming teams, while still ensuring measurable ROI?
Rohit Kumar: GenAI adoption must be treated as an operating model transformation, not a technology rollout. This requires cross-functional collaboration, elimination of redundant interfaces, and a focus on high-value use cases that deliver measurable returns.
Strong change management, transparent governance, and continuous feedback loops help prevent organizational overload while ensuring benefits are realized systematically.
CIO&Leader: Cognizant leverages ecosystem certifications, hyperscaler partnerships, and acquisitions to strengthen delivery capabilities. How can CIOs emulate this approach?
Rohit Kumar: Differentiation will increasingly come from ecosystem advantage. Cognizant continues to invest in scaled AI certifications, fundamental research—we hold 61 patents—proprietary frameworks, and deep partnerships with hyperscalers and emerging AI innovators, including Microsoft, Google, and others.
This ecosystem-led approach strengthens innovation capabilities and enables us, our partners, and our clients to build a resilient, future-ready IT landscape.