Eight years ago, I made a hiring decision that didn’t follow the usual rules. In today’s AI era, where tools can already assist with much of the work that we do, that decision feels even more relevant in hindsight. I was hiring for a fast-growing fintech company. The shortlist was what you’d expect: candidates from top universities, strong academic records, and big brand internships. On paper, most looked solid.

But one candidate stood out for a very different reason. He didn’t have a strong degree. But when we gave him a problem to solve, something clicked. He broke it down clearly, asked the right questions, and explained his thinking in a simple, structured way. He was fast, practical, and very focused on outcomes.

Our HR process didn’t allow us to hire him directly. We had to get special approval from leadership. We hired him anyway.

Within a few weeks, it was clear we had made the right call. He delivered faster than many experienced hires, not because he “knew more,” but because he could think clearly and adapt quickly. That moment changed how I look at talent.

What AI is changing right now in hiring

Today, that experience feels even more relevant. AI is now doing a lot of the work that used to help candidates stand out, right from basic research, writing first drafts, building summaries, and even structuring analysis.

We are seeing these changes across industries and, more importantly, across our own client ecosystem, where AI adoption is already becoming operational, not experimental.

For instance, BASIC Home Loan (a leading fintech) uses AI to simplify home loan journeys and reduce friction in early-stage processing, while KhiladiPro (sports tech startup), uses AI to make sense of large volumes of sports and engagement data. Both cases reflect something important: our clients are not just using AI; they are becoming AI-native in how they redesign workflows. And that changes what we value in people.

Also Read: What to actually prioritise when your board wants AI and everything feels urgent

This is not just a company-level shift. It is showing up in the broader labour market as well. The India Skills Report 2026 reinforces this transition: India’s employability stands at 56.35 per cent, even as demand rises sharply for digital and AI-related skills. India contributes about 16 per cent of global AI talent, positioning it as a key global supply hub; and by 2027, the country is expected to have 1.25 million AI specialists.

Taken together, the signal is clear: AI is not just changing tools inside companies, it’s changing how work is structured, and how talent is defined.

So what does a future-ready skill stack look like?

The hiring question has shifted. It is no longer: “Who has the best profile?” It is now: “Who can use new tools to think better and work faster?” Across teams, three shifts are becoming very clear—skills matter less than learning speed, thinking has become the real edge, and execution is now human + AI rather than either/or.

If that is how work is changing, the skill stack is also changing—from isolated abilities to a few connected strengths that work together.

Industry knowledge + AI fluency: Understanding your sector’s economics, policy shifts, and blind spots is still important, but it now works best with strong AI fluency. The real edge is knowing how to use AI to speed up work, improve decisions, and sharpen thinking—not just to generate output.
Thinking, data and storytelling: AI can process data, but it cannot decide what matters. The ability to find signals in data, simplify complexity, and turn it into clear, decision-ready storytelling is what helps people influence outcomes.
Collaboration + communication: As more work becomes AI-assisted, human skills matter more in how teams align and move together. The ability to build trust, persuade, and coordinate across people is becoming a key leadership skill.
Creativity: Automation improves efficiency, but it does not replace originality. In fact, as execution becomes easier, the ability to think differently becomes even more valuable.

Also Read: Think with AI: The new skill for social entrepreneurs

If I were hiring today

I would still make the same decision I made eight years ago. But I would add one more filter. Not “Which college?” Not “Which degree?”

Instead, I’d ask: Can this person learn continuously? Can they adapt as technology changes? Can they use AI to improve how they think and solve problems? Can they combine human judgment with machine capability? Because that is increasingly the real job.

Final word

The biggest talent shift in the AI era is not that degrees matter less. It’s that learning speed, adaptability, curiosity, and AI fluency now matter more than ever before. The strongest teams of the future will not simply be defined by credentials or polished resumes. They will be defined by how quickly they can learn, evolve, and work alongside AI to create meaningful outcomes.

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