GCCs double down on building talent

< />Today, the challenge is no longer just about how fast a firm can scale a 1,000 member team. As AI reshapes engineering work, skill requirements are changing faster than ever, and <a id=” captionrendered=”1″ data-src=”https://etimg.etb2bimg.com/photo/131849657.cms” height=”442″ href=”http://hr.economictimes.indiatimes.com/tag/gccs” keywordseo=”GCCs” loading=”eager” source=”Orion” src=”https://hr.economictimes.indiatimes.com/images/default.jpg” type=”General” weightage=”20″ width=”590″></img>GCCs are being forced to rethink how they build talent from within.</p>
<p>These themes took centre stage at <em>ETGCCWorld <a href=GCC Growth Summit 2026 at Conrad, Pune, where GCC leaders discussed what it takes to create deep engineering talent pipelines in this rapidly changing era.

“The shelf life of a role has diminished significantly. The job description, when you are within the role, changes in six months, so you need to hire not only for the depth of specialty but also for the breadth of learning,” said Saurabh Gupta, general manager and site head, Sulzer Business Services, Pune.

Hiring for the future

Sandeep Poddar, chief architect, Kimberly Clark GCC Pune, said organisations must balance current business requirements with future capabilities.

“We need to have a nice blend of hiring for now and transition into hiring for the future,” Poddar said.

According to him, organisations can no longer rely on static job descriptions. Instead, they must look for professionals who combine business acumen, AI fluency, and the ability to understand how their decisions impact broader organisational outcomes.

“It is more about creating somebody who can do transformation. Transformation is somebody who’s able to deliver long-term business outcomes by knowing the impact that a decision can have,” he said.

Ashfak Shaikh, senior director, Domo India, said future engineering leaders will be identified less by tenure and more by their ability to solve problems and work directly with customers.

“Leaders of the future need to be the ones who understand the product, who have customer empathy, are data curious, and understand foundational systems engineering,” Shaikh said.

Beyond technical skills

Veena Khandke, SVP and managing director, Ensono India, noted that the evolution of GCCs from delivery centres to strategic business partners has fundamentally altered what organisations too expect from its employees.

“When we started off, it was important for people to understand the SOPs, make sure you’re executing at the fastest level, at the most accurate level, and making sure it is happening at a low cost,” Khandke said.

For service-oriented organisations in particular, he added, understanding customer priorities and aligning work to business goals has become increasingly important.

“Now we are looking at creating value, creating business outcomes. That definitely requires a very different perspective,” he said.

Diwakar Rai, country head retail software & GCC, Diebold Nixdorf India, felt organisations should focus less on replacing talent and more on expanding employee capabilities.

“What we need to give them is a new role, a new model, a new thought process. I did not throw away the talent that I had. What we did is we changed the mindset and gave them a new growth objective,” said Diwakar Rai,.


Building AI-ready talent

Gupta described a three-layer mantra focused on AI literacy, cross-functional exposure, and applied learning.

“First and foremost is to have people be AI citizens. That is AI literacy,” Gupta said.

Khandke compared this journey to learning a new language.

“If you don’t know the alphabets, you’re not going to understand the language,” she said, explaining why foundational AI education has become a priority for many organisations.

Poddar argued that success in the AI era will depend not just on technical expertise but on understanding how technology can be applied to solve the right business problems.

“Technology depth can solve problems, but process intelligence and using technology to advantage can solve the right problems,” he said.

Gupta offered a cautionary note, suggesting that overreliance on AI could eventually limit innovation.

“We need to limit AI usage not only from a perspective of cost but also from a perspective of protecting the innovation engine of any organisation,” he said.

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