As India moves into a new financial year, Ashnik’s Deputy CEO Ravi Papnoi shares his perspective on where enterprises truly stand in the GenAI era — and what it will take to move from conversation to consequence.
Closing a financial year is a good time to pause, reflect, and review performance — and to plan for what comes next. Looking into the rear-view and trying to make decisions for the future in the GenAI era is a fool’s errand. And yet, here is an interesting observation I have had in the past year: you read about the latest world-changing developments in AI, and then go back to see people still struggling with the same issues they did a few years ago.
The gap between what technology at the frontier has become capable of, and where the impact actually is — that gap is real, and large. Bridging it is the main work that will keep happening in the foreseeable future.
This makes me feel that the cycle for IT services companies may not be too different from what it has been in the past. We have reached the point where the debate around whether GenAI will make a meaningful difference to our lives is more or less settled. The phase of applying it for concrete benefits has begun — and that changes everything about how enterprises need to think and move.
Another question I am genuinely excited to see play out is: where do large enterprises’ strategic multi-year projects go from here? Many of them were designed and conceptualized before the dawn of the GenAI era. How these projects benefit from the shift in technology is now on the minds of every senior executive.
What I find particularly telling is this — the same enterprises that would take years to decide on a new technology, and then again some more time planning its adoption, are now casually and confidently talking about open-source technologies for enterprise use cases. Even relatively new ones, without a decades-old ecosystem. This signals something important: customers are gaining confidence in communities, and in their own ability to handle large-scale deployment of niche technologies — if those technologies genuinely solve the problem better than established OEMs.
This shift may cause consternation within teams used to doing things a certain way, particularly in large enterprises. But it is the only path to benefiting from the explosion in performance gains that the GenAI era promises. The incremental gains of the earlier technology era were something enterprises could choose to live without if change meant instability. That calculation no longer holds. The meaningful and quick adoption of newer technologies will define success — or stagnation — in the days ahead.
The question is no longer whether to change. It is whether you will lead that change, or be caught flat-footed by it.
