AI Everywhere, Differentiation Nowhere? Nithin Kamath Says Founders Need a Better Pitch
Artificial intelligence has become one of the most common words in startup pitches. But according to Zerodha founder and CEO Nithin Kamath, simply saying that a company uses AI is no longer enough to make a business stand out.
Kamath’s latest comments highlight a growing problem in the startup ecosystem: when everyone claims to be AI-powered, AI itself stops being a differentiator. For founders seeking investors, the real challenge is increasingly about explaining what makes their product valuable, defensible and different.
Recent coverage of Kamath’s remarks says he believes AI has effectively become “table stakes” for many startups, rather than a unique selling point. He has also questioned the growing use of AI-generated presentations that can make startup pitches look polished without necessarily demonstrating a strong underlying business.
Why “We Use AI” Is Losing Its Impact
A few years ago, adding AI to a product could immediately make a startup sound innovative.
Today, the situation is very different.
Generative AI tools have made it dramatically easier for founders and developers to build prototypes, automate workflows and add AI features to existing products. As a result, investors are seeing an increasing number of companies describing themselves as AI-first, AI-powered or AI-enabled.
That creates a differentiation problem.
If dozens of startups can build similar AI features using broadly available models and APIs, simply having an AI layer may not provide a durable competitive advantage.
For investors, the more important questions become:
What problem is the startup solving?
Who urgently needs the solution?
Why will customers pay for it?
What makes the product difficult to copy?
Does the company have distribution, proprietary data, technology or a strong network effect?
What evidence shows that customers actually want it?
In other words, AI may be the technology, but it cannot automatically be the business model.
Nithin Kamath Has Been Skeptical of AI Hype Before
Kamath’s latest position also fits with his earlier comments about technology hype.
In 2021, he publicly discussed why Zerodha had not aggressively adopted AI, machine learning or blockchain simply because they were fashionable technologies. He said the company had not found a meaningful use case that required them at the time.
Zerodha’s CTO Kailash Nadh similarly argued at the time that many “powered by AI” claims were more marketing than meaningful technological differentiation.
The important lesson is not that AI is unnecessary.
Rather, it is that technology should solve a real problem before it becomes a marketing slogan.
That distinction is becoming even more important as AI becomes cheaper and easier to integrate.
What Investors Actually Want to Hear From AI Startups
A stronger startup pitch would not stop at saying, “We use AI to automate X.”
It would explain why the business can win.
For example, consider two hypothetical startups.
Startup A says:
“We are an AI-powered platform helping small businesses manage invoices.”
Startup B says:
“We help small manufacturers reduce invoice-processing time from two days to 20 minutes. Our system is trained on industry-specific workflows, integrates with existing accounting software and has already converted 500 paying businesses.”
Both may use AI.
But the second pitch communicates something much more valuable: a specific customer, a measurable problem, a business outcome and evidence of traction.
The AI is part of the solution rather than the entire story.
Differentiation Is Becoming More Important in the AI Era
The irony of the AI boom is that AI can make differentiation harder.
When software development becomes faster, competitors can reproduce features more quickly. A feature that once required months of engineering may now be prototyped in days or weeks.
That means founders increasingly need advantages outside the basic technology layer.
These could include:
Proprietary Data
A company with unique, high-quality data may be able to build better systems than competitors using the same underlying AI models.
Distribution
A great product can still fail if customers cannot be reached efficiently.
A startup with strong partnerships, an established community or an efficient customer-acquisition engine may have a significant advantage.
Deep Industry Knowledge
AI models can be widely available, but understanding a complicated industry is not.
A startup that deeply understands healthcare, manufacturing, finance, agriculture or logistics may build products that generic competitors struggle to replicate.
Customer Trust
In areas involving money, personal information or critical business operations, customers may care more about reliability and trust than whether the product has the latest AI model.
Workflow Integration
The strongest AI products may not simply answer questions. They can become embedded in a company's daily operations.
That creates switching costs and makes the product harder to replace.
Zerodha Offers an Interesting Example
Kamath’s own company provides a useful example of why a business does not need to lead with fashionable technology to build a powerful competitive position.
Zerodha says it was founded in 2010 after Kamath experienced the problems faced by traders. The company describes its approach around reducing barriers in brokerage rather than simply selling technology as an end in itself.
In a recent 2026 conversation, Kamath also described Zerodha’s unusual operating model: the company has not raised external capital, does not advertise in the conventional manner, has no sales team with sales targets and has kept its employee count relatively stable even as the business expanded substantially.
That illustrates a broader startup lesson.
The competitive advantage is not always the technology. Sometimes it is the way the entire business is designed.
AI-Generated Pitch Decks Create Another Problem
There is another issue behind Kamath’s comments: AI can make almost any presentation look professional.
A founder can now generate slides, market summaries, graphics and polished explanations within minutes.
That is useful, but it also creates a new problem for investors.
When presentation quality becomes easier to manufacture, the content underneath becomes more important.
A beautiful pitch deck cannot compensate for weak customer demand, poor unit economics or an unclear competitive advantage.
For founders, this means the pitch should not simply demonstrate that they know how to use AI tools. It should demonstrate that they understand the market better than their competitors.
What This Means for Indian Startups
India’s startup ecosystem is entering a period where access to technology is becoming less exclusive.
That could be positive for entrepreneurship because smaller teams can build products faster and with lower initial costs.
But it could also increase competition.
If hundreds of companies can launch similar AI products, investors may become more selective about where they put capital. Metrics such as revenue growth, retention, customer acquisition costs, margins and product usage could matter more than an “AI-first” label.
This does not mean investors will stop funding AI startups.
Instead, the bar for a convincing AI startup may rise.
The strongest companies are likely to be those that combine AI with something harder to replicate: distribution, proprietary data, domain expertise, customer relationships, infrastructure or a genuinely differentiated product.
What Founders Should Watch Next
The AI startup story is gradually moving from “Can you build it?” to “Can you build a durable business around it?”
That shift could influence fundraising conversations over the coming years.
Founders may increasingly need to demonstrate actual customer traction and explain why competitors cannot easily copy what they have built.
For investors, meanwhile, the key distinction will be between companies that are merely adding AI features and businesses where AI creates a meaningful economic advantage.
Bottom Line
Nithin Kamath’s message is less about rejecting AI and more about rejecting AI as a substitute for differentiation.
In a market where almost every startup can claim to use artificial intelligence, the words “AI-powered” may no longer be enough to capture an investor’s attention.
The stronger pitch is likely to answer a harder question: Why should this business win even when everyone else has access to AI?
That is where product quality, customer traction, proprietary advantages and execution start to matter.
For founders, the lesson is straightforward: use AI to build a better business, not merely a better pitch deck.
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This article is for informational and educational purposes only and should not be considered investment advice
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