Nithin Kamath Says ‘We Use AI’ Is No Longer Enough: What Startups Should Focus On

Nithin Kamath on AI and startups: Zerodha founder and CEO Nithin Kamath has delivered a blunt message to startup founders who continue to make artificial intelligence the headline of their investor pitch decks. According to Kamath, simply saying “we use AI” is no longer enough to make a startup look innovative because artificial intelligence has increasingly become a basic expectation across the technology industry.

Kamath shared his views in a post on X, where he criticised the growing number of investment decks that begin by highlighting AI. He said the repetition has become so common that it can actually make investors lose interest rather than pay closer attention.

His comments have sparked fresh discussion around the AI startup boom and the question that increasingly matters to investors: What makes an AI startup genuinely different?

Nithin Kamath Says AI Is Now ‘Table Stakes’

Kamath’s central argument is that AI has moved from being a differentiating technology to something closer to a standard business tool.

In his post, the Zerodha chief described AI as “table stakes”, meaning that simply having AI capabilities is no longer enough to establish a competitive advantage. He compared bragging about a product using AI to bragging about an everyday activity, making the point that AI adoption by itself does not prove that a startup has built something valuable.

This is an important shift for founders preparing to raise venture capital. A few years ago, using machine learning or generative AI could immediately make a startup appear technologically advanced. Today, thousands of businesses can access similar foundation models, APIs and AI development tools.

As a result, investors may increasingly want to know what happens after the AI label.

Why ‘We Use AI’ May Not Impress Investors

The startup ecosystem has witnessed an explosion in AI-focused businesses. From customer service and coding to education, healthcare, finance and marketing, AI is being incorporated into products across almost every sector.

That creates a problem for founders.

If two startups use similar models and offer similar features, simply mentioning artificial intelligence does little to distinguish one company from another.

Kamath argued that repeatedly leading with AI can cause a pitch to blend into the crowd. He also noted that AI has made it easier to create polished-looking presentations, meaning that an impressive-looking deck is not necessarily evidence of an impressive business.

For investors, the focus therefore shifts from “Does this startup use AI?” to “Why does this startup deserve to exist?”

What Startups Should Focus On Instead

Kamath’s broader message points founders toward fundamentals that remain important regardless of the technology being used.

1. Solve a Real Problem

The first question for any startup should be simple: What problem are you solving?

AI should not be added merely because investors expect it. A company should be able to explain the customer pain point, how frequently that problem occurs and why existing solutions are inadequate.

A startup with a strong problem and an effective solution can be valuable even without an AI-heavy pitch.

On the other hand, a weak product does not automatically become a strong business simply because it incorporates a large language model.

2. Explain Why AI Is Actually Necessary

Founders should be prepared to answer another important question: Why AI specifically?

If the same customer experience can be delivered more reliably using conventional software, automation or a simpler algorithm, adding AI may not create meaningful value.

The strongest AI businesses are likely to be those where artificial intelligence enables something that would otherwise be difficult, expensive or impossible to deliver at scale.

That distinction can turn AI from a buzzword into a genuine product advantage.

3. Build a Competitive Moat

One of the biggest questions investors ask is what prevents another company from copying a startup.

Access to AI models alone may not provide a strong moat because competitors can often access comparable technology.

A stronger advantage could come from proprietary data, unique distribution, specialised workflows, customer relationships, intellectual property, brand trust or operational expertise.

The technology can change rapidly. A defensible business needs something that remains valuable even when the underlying AI model improves.

AI Has Made Pitch Decks Easier to Create

Another issue highlighted by Kamath is the growing use of AI tools to create presentation decks.

Modern AI systems can help founders generate text, structure presentations, create images and produce professional-looking slides in a short period.

That is useful, but it also creates a new challenge.

When everyone can generate a polished presentation using similar tools, visual quality becomes less useful as a signal of business quality.

A founder therefore needs to provide information that cannot easily be generated from a generic prompt.

Investors want to understand the founder’s insight, customer knowledge, market understanding and evidence that the business can actually execute.

Investors May Look More Closely at Business Fundamentals

As the AI startup market becomes more crowded, traditional startup fundamentals could become even more important.

These include:

• Revenue growth
• Customer retention
• Product-market fit
• Customer acquisition cost
• Lifetime value
• Gross margins
• Distribution
• Market size
• Cash runway
• Competitive advantage
• Execution capability

AI may improve several of these metrics, but founders still need to demonstrate measurable results.

For example, saying “our AI makes customer support faster” is less convincing than showing how much response time has improved, how customer satisfaction has changed and whether the business has reduced operating costs.

The difference is between describing technology and demonstrating business impact.

Security and Risk Also Matter

AI adoption creates another important area for founders to address: security.

Companies handling sensitive customer information need to explain how data is stored, processed and protected. Businesses operating in regulated sectors face even greater scrutiny.

Kamath’s comments have been widely discussed alongside questions around security, evaluation and operational responsibility in AI systems. Reports on his remarks note that founders should be ready to explain why AI is being used, how security risks are managed and how AI outputs are continuously evaluated, particularly when decisions have significant consequences.

This is particularly important for fintech, healthcare, legal and other high-stakes applications.

An AI feature may look impressive during a product demonstration, but investors also need to know what happens when the system makes a mistake.

Zerodha’s Own Approach to AI Offers an Interesting Example

Interestingly, the philosophy behind Kamath’s comments is broadly consistent with how Zerodha has approached AI.

A 2025 report on Zerodha’s AI strategy said the company does not follow a top-down mandate requiring teams to use artificial intelligence. Instead, tools are adopted when they solve a problem better than available alternatives.

Zerodha’s approach has focused on practical applications rather than using AI simply for publicity.

For example, the company has used AI to analyse customer-support calls, allowing more conversations to be reviewed than would be practical through manual sampling. AI has also been used in software development and debugging, with human oversight remaining important.

This illustrates an important distinction: AI can be valuable without being the entire product story.

AI Should Support the Product, Not Replace the Product Story

For startup founders, perhaps the biggest lesson from Kamath’s comments is that AI should generally be presented as part of the solution rather than the solution itself.

Instead of saying:

“We are an AI-powered company.”

A stronger pitch might explain:

“We solve this specific problem for this specific customer, and AI allows us to deliver the solution faster, cheaper or more accurately than existing alternatives.”

That approach gives investors context.

The technology becomes a reason the business works rather than the only reason the business exists.

What a Strong AI Startup Pitch Could Look Like

A compelling startup presentation could answer several straightforward questions.

What problem are you solving?
Explain the customer pain point clearly.

Who has this problem?
Identify the target market and demonstrate that the market is large enough.

Why existing solutions are insufficient?
Show what customers dislike or cannot achieve with current products.

Why is AI necessary?
Explain the specific role AI plays.

What makes your solution different?
Identify the product, data, workflow, distribution or technology advantage.

What evidence do you have?
Show customer numbers, revenue, retention, usage or other measurable traction.

What happens when AI models improve?
Explain whether your advantage becomes stronger or disappears as technology becomes cheaper and more accessible.

How do you manage risk?
Address privacy, security, reliability, hallucinations and human oversight where relevant.

These questions can produce a much stronger investor conversation than simply announcing that the startup uses AI.

AI Is Becoming Infrastructure

Kamath’s comments also reflect a broader change in the technology industry.

Artificial intelligence is increasingly becoming infrastructure that businesses can integrate into existing products and workflows.

Just as having a website eventually became a normal requirement for many businesses, AI capabilities could increasingly become an expected component of software products.

The competitive advantage therefore moves elsewhere.

It could be the data a company owns, the customers it serves, the workflow it understands, the distribution network it controls or the speed at which it can execute.

This does not mean AI is becoming less important. Instead, it means AI itself may become less distinctive.

What This Means for Indian Startups

For India’s startup ecosystem, Kamath’s warning comes at an important time.

India has seen rapid growth in AI-focused businesses, with founders building products for domestic and international markets. Easier access to cloud computing and foundation models has reduced some of the technical barriers that previously existed.

But lower barriers to entry also mean more competition.

Indian founders therefore need to think beyond creating another AI wrapper or adding a chatbot to an existing product.

The real opportunity could be combining AI with deep knowledge of a specific industry, strong distribution and an understanding of local customer behaviour.

In sectors such as finance, logistics, healthcare, education and commerce, domain expertise can become just as important as the underlying AI technology.

The Bigger Message From Nithin Kamath

Nithin Kamath’s comments are not necessarily an argument against AI. Instead, they are a warning against confusing technology adoption with innovation.

AI can dramatically improve productivity, reduce costs and enable new products. But simply mentioning AI does not prove that a startup has found product-market fit or built a sustainable company.

For founders, the message is clear: don’t make AI the headline unless AI itself is the breakthrough.

Investors increasingly want to understand the problem, the customer, the economics, the execution and the competitive moat.

Final Takeaway

Nithin Kamath’s warning that “we use AI” is no longer enough highlights a major change in the startup ecosystem. Artificial intelligence has moved rapidly from a cutting-edge feature to a widely available technology.

For founders, this means the pitch needs to go deeper.

Instead of focusing primarily on which AI model is being used, startups should explain the customer problem they solve, why their solution is different, what measurable results they have achieved and what makes the business difficult to copy.

AI can still be a powerful competitive advantage—but only when it creates genuine value.