AI won’t kill tech services, it will reset them: Mphasis CEO Nitin Rakesh

Stop hiring humans. AI employees are here.

That’s not my line. That’s the dystopian message screaming from billboards in New York City! Outraged netizens fired off death threats to the founders, and the advertisement—much to the delight of those same founders—went viral. They cashed in on these 15 seconds of fame, raised millions, and now, irony of ironies, are hiring humans to make their AI better!

John McCarthy, who coined the term “Artificial Intelligence” with his team in 1956, must be pleased with the maelstrom they kicked off a full 75 years ago.


But how much of this is real? Is AI going to take away our jobs? Is this the beginning of a dystopian Matrix world?

I am no futurist or psychic to divine the truth. However, this is a question I get asked by investors, employees, and analysts for a different reason: Is this the end of the tech services era?

Recent headlines around autonomous AI agents have intensified the narrative that traditional enterprise software and services models are on the brink of collapse. Absolutely not. These new tools are seemingly disruptive. But they are just that. Tools. Without enterprise context and engineering depth, they do not dismantle operating models built over decades. Markets may react to signals. Enterprises operate on accountability.

Yes, AI is powerful, and yes, it will automate tasks. But let’s apply Amara’s Law here: We overestimate the impact of technology in the short term and underestimate it in the long term.

In the near term, AI is not replacing an entire workforce. It is augmenting them. It needs data, governance, integration, and domain expertise. Enterprises cannot simply “plug in” AI and let go of their employees. They need partners to deploy it responsibly, ethically, and effectively.

In the long term, AI has the potential to transform industries, albeit not without human involvement. The world of The Matrix will stay on the big screen, not in your boardroom. So, if Artificial General Intelligence (AGI) is not here yet, what does this mean for the tech services industry that keeps the global enterprise humming?

Here’s the simple truth. Tech services are not dying. They are becoming the essential bridge between raw AI capability and genuine business outcomes.

AI tools are advancing rapidly. Some can now write code, generate workflows, and simulate decision-making at impressive speed. But enterprise technology is not a series of isolated tasks. It is a web of compliance controls, governance frameworks, audit trails, integrations, and legacy dependencies built over decades. Demonstrating capability is not the same as assuming accountability. That distinction matters.

Who will ensure compliance? Who will train models on enterprise-specific data? Who will design workflows that combine human judgement with machine speed? Who will bring all the legacy forward, without which you cannot harness the power of AI?

That’s where our industry thrives in every new tech adoption cycle. AI won’t kill tech services—but it will kill companies that stand still (not just in tech services). Let’s be clear: AI is not a rising tide that will lift all boats equally. Like in earlier generational shifts in technologies and value migrations, there will be winners and losers. What will separate winners from losers is execution. This calls for a shift in thinking, from people arbitrage to tech arbitrage, from FTE-based models to outcome-based ones, to changing incentive models and organisational structure. Old-school structures that rewarded headcount and hierarchy? They are history.

A big impediment to change for some companies will be the impact on existing portfolios. How do you transform as you deliver quarterly results? Large companies with massive “run the business” portfolios are already grappling with this. At the same time, there are opportunities for the willing. Players who are hampered by size or economies of scale will now benefit from the reset of the start line and the erasure of the value of economies of scale.

Additionally, large enterprises continue to spend on technology and transformation. Firms with strong engineering DNA and a focus on “change the business” initiatives will be the ones best positioned to capture this spending.

Creating this advantage will mean investing in building IP, engineering talent, and better distribution networks. That same investment, when applied to existing portfolios and shared sensibly with customers, will create operating leverage. Executing all of this still requires people, and those people need new skills.Companies that combine engineering rigour with AI fluency will dominate. Those who can stitch together business outcomes—not just proofs of concept—will own the future.

If you are leading a tech services company—or any enterprise, this is not the time to panic. The winners will be those who blend human judgment with machine intelligence. Clients don’t care about AI for AI’s sake. They care about outcomes, whether that means lower costs, higher revenues or reduced risk.

Stop reselling tools. Build proprietary frameworks and governance models that make AI trustworthy, compliant and ready for large-scale deployment.

AI is not the endgame of tech services. It is a reset that will define the next decade. Those who cling to old models will lose. Those who embrace AI as a force multiplier, and who strengthen their capabilities in cloud, data and domain knowledge, will lead the future.