Q1. Could you start by giving us a brief overview of your professional background, particularly focusing on your expertise in the industry?

I have spent my career at the intersection of technology, digital transformation, workforce management, Automation involving AI and smart factories, and global operating models, working closely with enterprises on technology strategy, product engineering, Global Capability Centers (GCCs), and IT services. My experience spans helping organizations scale engineering capabilities, modernize legacy technology, adopt AI, and build high-performing global teams. Over the years, I’ve worked with both service providers and enterprise technology leaders, giving me a balanced perspective on how the industry is evolving from traditional outsourcing toward innovation-led partnerships. My core industry expertise revolves around BFSI, Automobile, engineering, Energy, Oil and Natural Gas, and setting up and scaling GCCs.

Q2. What structural shifts are driving the rapid expansion of the GCC market, and do you see this momentum continuing over the next five years?

The growth of GCCs is being driven by several long-term structural factors rather than cyclical trends.
First, enterprises increasingly view technology as a strategic differentiator rather than just a support function. They want direct ownership of critical engineering, AI, cybersecurity, and digital product capabilities.
Second, access to specialized talent has become a competitive advantage. Countries like India offer not only scale but also deep expertise across cloud, AI, semiconductors, and product engineering.
Third, GCCs have evolved significantly—from cost optimization centers to innovation hubs responsible for global products, platforms, and business outcomes.

Finally, advancements in collaboration technologies and distributed operating models have made globally integrated teams far more effective.
I believe this momentum will continue over the next five years. However, the next phase will focus less on creating new GCCs and more on increasing the sophistication of existing ones through AI, automation, and higher-value engineering work.

Q3. How is Generative AI reshaping customer expectations for IT services, product engineering, and managed services providers?

Generative AI is fundamentally changing what customers expect from technology partners.
Previously, clients evaluated providers based on delivery quality, scale, and cost efficiency. Today, they increasingly expect measurable business outcomes, faster innovation, and AI-enabled productivity improvements.

In product engineering, customers want AI embedded into software development—from code generation and testing to documentation and DevSecOps.
In managed services, they expect autonomous operations, predictive incident management, intelligent service desks, and proactive optimization rather than reactive support.
The biggest shift is that clients now expect service providers to be AI transformation partners, helping redesign business processes instead of simply delivering technology projects.

Q4. How is competition changing as consulting firms, hyperscalers, IT services companies, and GCC specialists increasingly target the same enterprise opportunities?

The competitive landscape has become much more fluid.
Traditional boundaries between consulting, technology implementation, cloud infrastructure, and managed services are disappearing.
Consulting firms are strengthening their engineering capabilities. Hyperscalers are expanding into consulting and implementation through partner ecosystems. IT services companies are investing heavily in AI platforms and industry solutions. Meanwhile, GCC specialists are helping enterprises build and operate captive innovation centers.

As a result, competition is shifting from selling isolated services to delivering integrated transformation capabilities.
The winners will be organizations that combine strategic advisory, domain expertise, engineering excellence, AI capabilities, and long-term execution—not just technical delivery.

Q5. How important are industry expertise, governance capabilities, and ecosystem partnerships compared with pricing in today’s buying decisions?

Pricing remains important, but it is no longer the primary differentiator for large enterprise engagements.
Organizations increasingly prioritize providers that understand their industry, regulatory environment, and business processes. Deep domain expertise significantly reduces execution risk and accelerates value realization.
Governance has also become critical as engagements involve multiple vendors, AI adoption, cybersecurity requirements, and complex compliance obligations.

Equally important are ecosystem partnerships—with cloud providers, AI platform companies, cybersecurity vendors, and enterprise software providers—which enable faster innovation.
Ultimately, enterprises are optimizing for long-term business value rather than simply selecting the lowest-cost provider.

Q6. Looking ahead, how do you expect enterprise sourcing strategies to evolve as AI, automation, and geopolitical considerations reshape global delivery models?

Enterprise sourcing strategies are becoming more diversified and resilient.
Rather than concentrating work in a single geography or provider, organizations are building multi-location, multi-partner operating models that balance talent availability, geopolitical risk, regulatory compliance, and operational resilience.

AI and automation will also change sourcing decisions by reducing dependence on labor-intensive delivery models. Providers will increasingly be evaluated on their ability to automate work rather than supply talent.
We’re also likely to see greater adoption of hybrid models, where GCCs own strategic capabilities while service providers contribute specialized expertise, scalable delivery, and innovation.
The future sourcing model will emphasize flexibility, resilience, and business outcomes over labor arbitrage.

Q7. If you were an investor looking at companies within the space, what critical question would you pose to their senior management?

The question I would ask is:
“What sustainable competitive advantage will your business have in an AI-driven services market where productivity is increasing and traditional labor-based revenue models are under pressure?”
This question gets to the heart of long-term value creation.

Investors should understand whether management has a credible strategy to leverage AI for growth rather than defend existing business models. That includes how the company is reinventing its delivery model, developing proprietary IP and AI assets, strengthening client relationships, expanding industry expertise, and maintaining margins as automation changes the economics of technology services.
The companies that succeed will be those that transform from labor-led service providers into AI-enabled, outcome-driven business partners.