Founder/CEO
The founder/CEO cohort is the largest in our survey and the most illuminating. These are the people making investment decisions, setting strategic direction, and ultimately deciding how deeply AI will embed in their companies.
The founder/CEO cohort is the largest in our survey and the most illuminating. These are the people making investment decisions, setting strategic direction, and ultimately deciding how deeply AI will embed in their companies.
The view from the top: how 90 startup CEOs (99% of whom are founders) are thinking about, investing in, and building with AI.
The view from the top: how 90 startup CEOs (99% of whom are founders) are thinking about, investing in, and building with AI.
The view from the top: how 90 startup CEOs (99% of whom are founders) are thinking about, investing in, and building with AI.
The founder/CEO cohort is the largest in our survey and the most illuminating. These are the people making investment decisions, setting strategic direction, and ultimately deciding how deeply AI will embed in their companies.
// HIGHLIGHT 01
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// HIGHLIGHT 01
Founders are past the AI hype, but into the messy middle.
Founders are past the AI hype, but into the messy middle.
Founders are past the AI hype, but into the messy middle.
We asked founders to react to five provocative statements about AI to understand their mindset about AI. Their responses reveal a cohort that has firmly moved past the hype cycle, but hasn’t yet figured out all the operational details.
The verdict is in: AI is a force multiplier.
The verdict is in: AI is a force multiplier.
The verdict is in: AI is a force multiplier.
The verdict is in: AI is a force multiplier.
“AI tools are more hype than substance right now.”
The hype narrative is effectively dead among this founder base. They’ve seen enough real-world results to dismiss it
“AI tools are more hype than substance right now.”
The hype narrative is effectively dead among this founder base. They’ve seen enough real-world results to dismiss it
“AI tools are more hype than substance right now.”
The hype narrative is effectively dead among this founder base. They’ve seen enough real-world results to dismiss it
“AI gives startups an unfair advantage over incumbents.”
Founders have moved past the belief that AI works. They claim it disproportionately benefits them. AI amplifies the speed, scrappiness, and the lack of legacy baggage that define startups.
“AI gives startups an unfair advantage over incumbents.”
Founders have moved past the belief that AI works. They claim it disproportionately benefits them. AI amplifies the speed, scrappiness, and the lack of legacy baggage that define startups.
“AI gives startups an unfair advantage over incumbents.”
Founders have moved past the belief that AI works. They claim it disproportionately benefits them. AI amplifies the speed, scrappiness, and the lack of legacy baggage that define startups.
“AI will replace most knowledge workers within 5 years.”
The people closest to AI implementation are the most sceptical of the narrative that AI will replace humans. They see augmentation, not substitution. AI makes teams more capable, but it doesn’t replace the judgment, context, and creativity that humans bring.
“AI will replace most knowledge workers within 5 years.”
The people closest to AI implementation are the most sceptical of the narrative that AI will replace humans. They see augmentation, not substitution. AI makes teams more capable, but it doesn’t replace the judgment, context, and creativity that humans bring.
“AI will replace most knowledge workers within 5 years.”
The people closest to AI implementation are the most sceptical of the narrative that AI will replace humans. They see augmentation, not substitution. AI makes teams more capable, but it doesn’t replace the judgment, context, and creativity that humans bring.
“AI tools are more hype than substance right now.”
Founders believe AI is real, that it benefits their companies, and that its impact will elevate human capability rather than eliminate it.
VERDICT
Founders believe AI is real, it benefits their companies, and its impact will elevate human capability rather than eliminate it.
VERDICT
Founders believe AI is real, it benefits their companies, and its impact will elevate human capability rather than eliminate it.
The conviction is strong. The playbook isn't.
The conviction is strong. The playbook isn't.
The conviction is strong. The playbook isn't.
The conviction is strong. The playbook isn't.
“Our company has a clear AI strategy.”
The same founders who overwhelmingly reject the idea that AI is hype are simultaneously admitting they don’t have a structured plan for deploying it. Conviction has outpaced codification.
“Our company has a clear AI strategy.”
The same founders who overwhelmingly reject the idea that AI is hype are simultaneously admitting they don’t have a structured plan for deploying it. Conviction has outpaced codification.
“Our company has a clear AI strategy.”
The same founders who overwhelmingly reject the idea that AI is hype are simultaneously admitting they don’t have a structured plan for deploying it. Conviction has outpaced codification.
“Data quality is a bigger bottleneck than AI capability.”
When founders try to operationalise their AI ambition, the first wall they hit is the data underneath. This tracks with what we’ve heard: the models are impressive, but feeding them clean, structured, context-rich data remains an unsolved problem for most early-stage companies.
“Data quality is a bigger bottleneck than AI capability.”
When founders try to operationalise their AI ambition, the first wall they hit is the data underneath. This tracks with what we’ve heard: the models are impressive, but feeding them clean, structured, context-rich data remains an unsolved problem for most early-stage companies.
“Data quality is a bigger bottleneck than AI capability.”
When founders try to operationalise their AI ambition, the first wall they hit is the data underneath. This tracks with what we’ve heard: the models are impressive, but feeding them clean, structured, context-rich data remains an unsolved problem for most early-stage companies.
“AI tools are more hype than substance right now.”
Founders believe AI is real, that it benefits their companies, and that its impact will elevate human capability rather than eliminate it.
VERDICT
Conviction doesn’t equal readiness. There’s a tension between an overwhelming confidence in AI’s potential and the acknowledged gaps in strategy and data readiness. It tells us where the ecosystem needs help.
VERDICT
Conviction doesn’t equal readiness. There’s a tension between an overwhelming confidence in AI’s potential and the acknowledged gaps in strategy and data readiness. It tells us where the ecosystem needs help.
// HIGHLIGHT 02
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// HIGHLIGHT 02
Skeptics are extinct. What remains is a spectrum.
Skeptics are extinct. What remains is a spectrum.
Skeptics are extinct. What remains is a spectrum.
When we asked founders to assess their organisation’s AI maturity, the results fell into an almost perfect three way split. The majority have moved beyond experimentation into structured deployment, but at different depths.
Instead of a binary story of “adopters vs laggards,” this is a continuum where nearly everyone has crossed the starting line. The gap between “Application” & “Transformation” is where the next wave of competitive differentiation will play out.
WHERE DOES YOUR ORGANISATION CURRENTLY STAND ON AI ADOPTION MATURITY?
WHERE DOES YOUR ORGANISATION CURRENTLY STAND ON AI ADOPTION MATURITY?
WHERE DOES YOUR ORGANISATION CURRENTLY STAND ON AI ADOPTION MATURITY?
// HIGHLIGHT 03
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// HIGHLIGHT 03
AI's biggest dividend is speed, and founders are cashing in twice
AI's biggest dividend is speed, and founders are cashing in twice
AI's biggest dividend is speed, and founders are cashing in twice
When asked where AI has delivered the most measurable business impact, founders are unequivocal: increased productivity, followed by faster time-to-market. Together, 82% of all measurable impact is in some form of “doing things faster.”
Only 9% point to increased sales or conversions. The revenue impact, founders believe, is coming but hasn’t landed yet.
When asked where AI has delivered the most measurable business impact, founders are unequivocal: increased productivity, followed by faster time-to-market. Together, 82% of all measurable impact is in some form of “doing things faster.”
Only 9% point to increased sales or conversions. The revenue impact, founders believe, is coming but hasn’t landed yet.
WHERE HAS AI DELIVERED THE MOST MEASURABLE BUSINESS IMPACT FOR YOU SO FAR?
WHERE HAS AI DELIVERED THE MOST MEASURABLE BUSINESS IMPACT FOR YOU SO FAR?
WHERE HAS AI DELIVERED THE MOST MEASURABLE BUSINESS IMPACT FOR YOU SO FAR?
But the real story is
in AI’s unexpected
upside.
But the real story is in AI’s unexpected upside.
But the real story is
in AI’s unexpected
upside.
For the majority, the standout surprise is faster experimentation. 45% say they can now test 10x more ideas than before.
This reframes AI’s core value from efficiency (doing the same work cheaper) to acceleration (doing far more and far faster). For founders who live and die by their ability to iterate, test, and pivot, AI has expanded the frontier of what a small team can attempt.
“Our PMs can launch [interactive content] in a day without any developer need. Previously, it took a minimum of 7 days and 1 developer.”
// FOUNDER SPOTLIGHT - Early-stage founder
“Our PMs can launch [interactive content] in a day without any developer need. Previously, it took a minimum of 7 days and 1 developer.”
// FOUNDER SPOTLIGHT - Early-stage founder
What’s been the most unexpected benefit of AI adoption?
What’s been the most unexpected benefit of AI adoption?
45%
Faster experimentation - can test 10x more ideas than before
45%
Faster experimentation - can test 10x more ideas than before
22%
Competitive advantage - we're moving faster than competitors
22%
Competitive advantage - we're moving faster than competitors
05%
Improved employee satisfaction
05%
Improved employee satisfaction
03%
Attracted better talent
03%
Attracted better talent
14%
Better decision-making - AI surfaces insights we'd have missed
14%
Better decision-making - AI surfaces insights we'd have missed
14%
Better decision-making - AI surfaces insights we'd have missed
12%
Reduced burnout - team working smarter, not harder
12%
Reduced burnout - team working smarter, not harder
12%
Reduced burnout - team working smarter, not harder
// HIGHLIGHT 04
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// HIGHLIGHT 04
Starting with AI is hard because teams are stretched. Scaling it is hard because tools aren't ready.
Starting with AI is hard because teams are stretched. Scaling it is hard because tools aren't ready.
Starting with AI is hard because teams are stretched. Scaling it is hard because tools aren't ready.
We asked CEOs two pressing questions:
We asked CEOs two pressing questions:
1.
1.
What's stopping you from adopting AI
What's stopping you from adopting AI
What's stopping you from adopting AI
2.
2.
What's stopping you from scaling it?
What's stopping you from scaling it?
What's stopping you from scaling it?
Together, the answers tell a more honest story about where the ecosystem is stuck.
Together, the answers tell a more honest story about where the ecosystem is stuck.
Together, the answers tell a more honest story about where the ecosystem is stuck.
We asked CEOs two pressing questions:
The barrier to getting started is a resourcing trap.
The barrier to getting started is a resourcing trap.
The barrier to getting started is a resourcing trap.
The barrier to scaling to the limitations of AI
Bandwidth is the dominant blocker at 53%. Teams are too busy to implement the thing that would make them less busy. It's a classic catch-22: you need capacity to build capacity.
The cultural blocker is fading fast. Only 25% cite cultural resistance to AI adoption. That’s one of the lowest-ranked barriers and almost certainly lower than it was 18 months ago. The ecosystem has stopped arguing about whether to adopt AI. The conversation is now entirely about how.
Bandwidth is the dominant blocker at 53%. Teams are too busy to implement the thing that would make them less busy. It's a classic catch-22: you need capacity to build capacity.
What's striking is how evenly distributed the remaining blockers are. Technical infrastructure, pace of change, data quality, and budget all cluster tightly between 33–37%. There's no second villain. It’s a market facing several blockers simultaneously, all at comparable intensity.
What's striking is how evenly distributed the remaining blockers are. Technical infrastructure, pace of change, data quality, and budget all cluster tightly between 33–37%. There's no second villain. It’s a market facing several blockers simultaneously, all at comparable intensity.
The cultural blocker is fading fast. Only 25% cite cultural resistance to AI adoption. That’s one of the lowest-ranked barriers and almost certainly lower than it was 18 months ago. The ecosystem has stopped arguing about whether to adopt AI. The conversation is now entirely about how.
What Are the Top 3 Barriers to AI Adoption in Your Organisation?
WHAT ARE THE TOP 3 BARRIERS TO
SCALING AI IN YOUR ORGANISATION?
What Are the Top 3 Barriers to AI Adoption in Your Organisation?
What Are the Top 3 Barriers to AI Adoption in Your Organisation?
The barrier to scaling is the limitations of AI tools.
The barrier to scaling is the limitations of AI tools.
Once founders move from “starting” to “scaling,” the profile changes entirely.
When asked about barriers to scaling AI adoption, the runaway answer is manual context requirements. 54% of founders believe AI tools demand too much hand-holding to work reliably at scale. Waiting for tools to mature (48%) and output quality concerns (48%) are close behind. These are capability gaps.
The blockers to getting started are about what founders have (bandwidth, budget, infrastructure). The blockers to scaling are about what the tools can do.
The two converge on one truth: the ambition exists, the tools haven’t fully caught up.
Once founders move from “starting” to “scaling,” the profile changes entirely.
WHAT ARE THE TOP 3 BARRIERS TO
SCALING AI IN YOUR ORGANISATION?
WHAT ARE THE TOP 3 BARRIERS TO
SCALING AI IN YOUR ORGANISATION?
WHAT ARE THE TOP 3 BARRIERS TO
SCALING AI IN YOUR ORGANISATION?
// HIGHLIGHT 05
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// HIGHLIGHT 05
The math is straightforward: junior roles are shrinking, and AI budgets are growing.
The math is straightforward: junior roles are shrinking, and AI budgets are growing.
The math is straightforward: junior roles are shrinking, and AI budgets are growing.
The math is straightforward: junior roles are shrinking, and AI budgets are growing.
Nearly half of all founders (52%) are either freezing hiring in specific functions or actively reducing team sizes. Another 23% are in wait-and-watch mode. Only 29% say there’s no change and that AI is augmenting their team, not replacing.
Nearly half of all founders (52%) are either freezing hiring in specific functions or actively reducing team sizes. Another 23% are in wait-and-watch mode. Only 29% say there’s no change and that AI is augmenting their team, not replacing.
Nearly half of all founders (52%) are either freezing hiring in specific functions or actively reducing team sizes. Another 23% are in wait-and-watch mode. Only 29% say there’s no change and that AI is augmenting their team, not replacing.
HOW WILL AI IMPACT YOUR ORGANISATION'S HIRING PLANS OVER THE NEXT 12 MONTHS?
How will AI impact your organisation’s hiring plans over the next 12 months?
How will AI impact your organisation’s hiring plans over the next 12 months?
No change - AI is augmenting our team, not replacing anyone
No change - AI is augmenting our team, not replacing anyone
No change - AI is augmenting our team, not replacing anyone
Too early to determine - waiting to see productivity gains play out
Too early to determine - waiting to see productivity gains play out
Too early to determine - waiting to see productivity gains play out
Reducing junior/entry-level hiring but increasing senior AI specialist hiring
Reducing junior/entry-level hiring but increasing senior AI specialist hiring
Reducing junior/entry-level hiring but increasing senior AI specialist hiring
Hiring freeze in specific functions that AI can now handle
Hiring freeze in specific functions that AI can now handle
Hiring freeze in specific functions that AI can now handle
Actively reducing team size by 10-20% in AI-enabled functions
Actively reducing team size by 10-20% in AI-enabled functions
Actively reducing team size by 10-20% in AI-enabled functions
No change - AI is augmenting our team, not replacing anyone
Too early to determine - waiting to see productivity gains play out
Reducing junior/entry-level hiring but increasing senior AI specialist hiring
Hiring freeze in specific functions that AI can now handle
Actively reducing team size by 10-20% in AI-enabled functions
So, which functions are feeling it the most?
So, which functions are feeling it the most?
So, which functions are feeling it the most?
So, which functions are feeling it the most?
For nearly half the respondents, engineering is the #1 cited function for hiring reductions. Marketing is a close second, followed by Customer Support and Operations. “Junior” and “entry-level” roles are bearing the highest brunt.
For nearly half the respondents, engineering is the #1 cited function for hiring reductions. Marketing is a close second, followed by Customer Support and Operations. “Junior” and “entry-level” roles are bearing the highest brunt.
This restructuring also aligns with the founders’ budget allocation patterns.
This restructuring also aligns with the founders’ budget allocation patterns.
CEOs are directing 45% of their AI budget to Engineering, Product, and Data, the functions where adoption is highest and where the tools are most mature. Sales and Marketing receive 21%. HR, Finance, and Operations sit in single digits.
CEOs are directing 45% of their AI budget to Engineering, Product, and Data, the functions where adoption is highest and where the tools are most mature. Sales and Marketing receive 21%. HR, Finance, and Operations sit in single digits.
Money and headcount are moving in the same direction: toward the functions where AI delivers, and away from those where it doesn’t yet.
Money and headcount are moving in the same direction: toward the functions where AI delivers, and away from those where it doesn’t yet.
// HIGHLIGHT 06
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// HIGHLIGHT 06
Indian founders don't want to rent the AI layer. They want to own it.
Indian founders don't want to rent the AI layer. They want to own it.
Indian founders don't want to rent the AI layer. They want to own it.
Indian founders don't want to rent the AI layer. They want to own it.
Given a choice between building AI capabilities in-house, buying from vendors, or going hybrid, the hybrid approach is the pragmatic default. Founders want to use vendor tools when they’re good enough, and build custom when they’re not.
Given a choice between building AI capabilities in-house, buying from vendors, or going hybrid, the hybrid approach is the pragmatic default. Founders want to use vendor tools when they’re good enough, and build custom when they’re not.
Given a choice between building AI capabilities in-house, buying from vendors, or going hybrid, the hybrid approach is the pragmatic default. Founders want to use vendor tools when they’re good enough, and build custom when they’re not.
But what stands out is the strength of the in-house contingent. More than a third of founders want to build everything themselves. This speaks to the startup DNA: control, customisation, and the belief that proprietary AI capabilities will become a competitive moat.
But what stands out is the strength of the in-house contingent. More than a third of founders want to build everything themselves. This speaks to the startup DNA: control, customisation, and the belief that proprietary AI capabilities will become a competitive moat.
But what stands out is the strength of the in-house contingent. More than a third of founders want to build everything themselves. This speaks to the startup DNA: control, customisation, and the belief that proprietary AI capabilities will become a competitive moat.
The Indian startup founder it appears wants to own the AI layer or at least co-own it. This has implications for the vendor ecosystem. Pure-play SaaS AI tools may find that their best customers also want to compete with them.
The Indian startup founder it appears wants to own the AI layer or at least co-own it. This has implications for the vendor ecosystem. Pure-play SaaS AI tools may find that their best customers also want to compete with them.
The Indian startup founder it appears wants to own the AI layer or at least co-own it. This has implications for the vendor ecosystem. Pure-play SaaS AI tools may find that their best customers also want to compete with them.
WHAT IS YOUR PRIMARY AI IMPLEMENTATION
APPROACH?
WHAT IS YOUR PRIMARY AI IMPLEMENTATION APPROACH?
"With a very small team and use of the right AI agents/tools, we are able to build a good early-stage bootstrapped business."
// FOUNDER SPOTLIGHT - Bootstrapped founder
"With a very small team and use of the right AI agents/tools, we are able to build a good early-stage bootstrapped business."
// FOUNDER SPOTLIGHT - Bootstrapped founder
// HIGHLIGHT 07
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// HIGHLIGHT 07
73% of founders aren't in emergency mode when it comes to competitive AI pressure.
73% of founders aren't in emergency mode when it comes to competitive AI pressure.
73% of founders aren't in emergency mode when it comes to competitive AI pressure.
When asked how much competitive pressure is driving their AI adoption, the majority project calm. This isn't a market paralysed by fear of disruption. It's one moving on conviction.
The reason is simple: it's hard to feel behind when you're already building. With 95% of founders past the exploration phase and in active deployment, competitive anxiety has naturally given way to competitive confidence. They're no longer watching AI from the sidelines.
The 12% who do feel existential pressure are worth watching closely. They likely operate in sectors where AI-native startups are attacking the business model directly.
HOW MUCH IS COMPETITIVE PRESSURE
DRIVING YOUR AI ADOPTION?
HOW MUCH IS COMPETITIVE PRESSURE
DRIVING YOUR AI ADOPTION?
33%
Moderate - AI is important but we have other competitive advantages
16%
Significant - we need AI to maintain competitive parity
12%
Not a factor - we’re driving AI for internal efficiency, not competition
22%
Minimal - we’re ahead of most competitors in AI adoption
18%
Not a factor - we’re driving AI for internal efficiency, not competition
Moderate - AI is important but we have other competitive advantages
33%
Minimal - we’re ahead of most competitors in AI adoption
22%
Not a factor - we’re driving AI for internal efficiency, not competition
18%
Significant - we need AI to maintain competitive parity
16%
Existential - AI-native competitors are threatening our business model
12%
HOW MUCH IS COMPETITIVE PRESSURE
DRIVING YOUR AI ADOPTION?
// HIGHLIGHT 08
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// HIGHLIGHT 08
The bets are getting bigger in 2026, and they're going in two directions at once.
The bets are getting bigger in 2026, and they're going in two directions at once.
The bets are getting bigger in 2026, and they're going in two directions at once.
The bets are getting bigger in 2026, and they're going in two directions at once.
Founders’ AI priorities for 2026 converge around a
clear two-part bet:
Boosting internal team productivity (75%)
Launching customer-facing AI features (69%)
These two tower above everything else, and the narrow gap between them (just six points) is telling.
Founders’ AI priorities for 2026 converge around a clear two-part bet:
Boosting internal team productivity (75%)
Launching customer-facing AI features (69%)
These two tower above everything else, and the narrow gap between them (just six points) is telling.
Founders’ AI priorities for 2026 converge around a clear two-part bet:
Boosting internal team productivity (75%)
Launching customer-facing AI features (69%)
These two tower above everything else, and the narrow gap between them (just six points) is telling.
Founders are not choosing between internal efficiency and external differentiation. They’re pursuing both simultaneously. Productivity is the proven playbook; embedding AI features in the product is the emerging frontier. The former creates the capacity (faster teams, fewer bottlenecks) that makes the latter possible.
What are your top 3 strategic AI priorities for 2026?
What are your top 3 strategic AI priorities for 2026?
What are your top 3 strategic AI priorities for 2026?
75%
Boost internal team productivity
69%
Launch customer-facing AI features
43%
Automate repetitive processes
35%
Generate new revenue streams
31%
Reduce operational costs
24%
Build AI talent capabilities
12%
Strengthen AI governance/safety
12%
Modernize data infrastructure
75%
Boost internal team productivity
69%
Launch customer-facing AI features
43%
Automate repetitive processes
35%
Generate new revenue streams
31%
Reduce operational costs
24%
Build AI talent capabilities
12%
Strengthen AI governance/safety
12%
Modernize data infrastructure
And how will they deploy this investment?
And how will they deploy this investment?
And how will they deploy this investment?
Primarily through organic, bottom-up adoption: 43% report AI is being driven by individual employees discovering and championing tools on their own. Function-level champions (33%) and centralised AI teams (25%) play supporting roles, while only 12% have ad-hoc or no formal structure at all.
The operating model for AI in early-stage startups has moved away from a top-down mandate to a philosophy of “letting a thousand experiments bloom.”
The operating model for AI in early-stage startups has moved away from a top-down mandate to a philosophy of “letting a thousand experiments bloom.”
What Would 10x
AI Adoption
What Would 10x
AI Adoption
What Would 10x
AI Adoption
We asked founders about the one thing that would accelerate their AI journey the most. From 48 responses, three enablers dominate:
Lower cost with maintained quality is the #1 ask.
Founders want premium model capabilities at price points that work for startup unit economics. Rate limits, trial credits, and cost-optimised inference all come up repeatedly.
Better context integration across tools is the #2 theme.
Founders describe a fragmented landscape where AI tools don’t “know” the company context. The ability for AI to seamlessly connect across CRM, codebase, internal docs, and communication tools - without manual context-stuffing - is seen as the next major unlock.
Talent and culture readiness rounds out the top three.
From training team managers to become AI champions, to building internal AI expertise, to shifting leadership mindsets, founders see human readiness as a key multiplier. The tools are good enough; the question is whether teams are prepared to use them at full capacity.
Tool maturity, data security, and real-world proof points (case studies showing 10x impact in comparable companies) complete this wishlist.
And how will they deploy this investment?
Primarily through organic, bottom-up adoption: 43% report AI is being driven by individual employees discovering and championing tools on their own. Function-level champions (33%) and centralised AI teams (25%) play supporting roles, while only 12% have ad-hoc or no formal structure at all.
Explore By Roles
Deep-dive into the data that matters most to your function
AI Adoption Survey Report · Indian Startups 2026
Explore By Roles
Deep-dive into the data that matters most to your function
AI Adoption Survey Report · Indian Startups 2026
Explore By Roles
Deep-dive into the data that matters most to your function
AI Adoption Survey Report ·
Indian Startups 2026
ELEVATION