The story so far
A year ago, the conversation around AI in Indian startups was charged with possibility but tempered by uncertainty. Founders were excited, but cautiously so. Models were impressive in demos but unpredictable in production. The question was never whether AI would matter, but whether it was ready to matter now.
That question has been answered.
REPORT HIGHLIGHTS
Founders are putting
money where their mouth is
Over four in five founders report being more excited about AI than they were twelve months ago. Investment intent closely tracks this excitement, with an overwhelming majority (86%) planning to increase their AI spend in 2026. For the first time, excitement and action are moving in lockstep. This isn't the frothy enthusiasm where every pitch deck had an AI slide. Founders are citing real results — faster shipping cycles, tangible productivity gains, successful internal deployments — as the reason for their growing conviction.
How do you expect your AI investment to change over the next 12 months?
Productivity is the proving ground, and founders are doubling down
Over half of all founders point to productivity as the single biggest win.
And it’s not just where they’ve seen results, it’s where they want to go deeper. When asked about strategic AI priorities for 2026, boosting team productivity tops the list at 75%, well ahead of every other option.
The logic is intuitive but worth articulating: founders have found their first clear proof point in productivity, and it’s become the proxy through which they expect other positive outcomes to materialise. Think faster product cycles, better products, stronger market positioning, and eventually revenue impact.
Where has AI delivered the most measurable business impact for you so far?
The adoption curve is steeply uneven among functions
AI adoption across functions is not a rising tide lifting all boats. It’s a steep gradient.
Engineering is at the front, with 85% of companies already in some form of production deployment. Product is close behind at 75%. Marketing (48%) and operations (40%) sit in the middle where they’re adopting, but not yet at scale. Then comes a sharp drop in customer support, sales, finance, and HR.
This unevenness maps to the maturity of available tools. For functions like HR, Finance, and Legal, the AI product ecosystem is still nascent. And this is a signal for builders: the next wave of AI-native companies will be those that build for the functions still left behind.
WHAT IS THE CURRENT AI ADOPTION STATUS FOR EACH
FUNCTION IN YOUR ORGANIZATION?
The workforce recalibration has already begun
Nearly half of all founders are either freezing hiring in specific functions or actively reducing team sizes.
That said, this isn’t a dramatic restructuring. Nobody is mass laying off teams in the name of AI. What’s happening is subtler and more structural: founders are realizing that the same team size (or even a smaller one) can produce meaningfully more.
The calculus of headcount is being rewritten in real time, one function at a time
The evangelists are no longer in the C-suite
When asked how AI adoption is being driven in their organisation, the most common answer among founders was “bottom-up adoption by individual employees.”
A year ago, one of the most commonly cited barriers to AI adoption was cultural resistance within teams. Today, our survey shows a remarkable inversion: adoption is now being driven primarily from the bottom up, by individual employees who are discovering, testing, and championing AI tools on their own.
For founders, the internal sell is done. What remains is the operational plumbing.
What is the current AI adoption status for each function in your organization?
AI is moving from the back office to the product
The strategic priorities data shows a signal that we can’t overlook: launching customer-facing AI features is the #2 priority for 2026, selected by 69% of founders, nearly as high as productivity.
What’s driving this? As consumers grow accustomed to AI-powered experiences in search, shopping, and support, they likely expect similar intelligence and personalization. And founders are responding to this latent demand by putting AI features on their product roadmaps.
Another driving factor is that 45% of founders consider faster experimentation and the ability to test 10x more ideas than before as the most unexpected benefit of AI adoption. This accelerated experimentation cycle allows teams to prototype, test, and iterate on AI features at a pace that would have been impossible even a year ago.
