AI demands more than investment, it demands understanding

Investing in AI requires more than just capital; it demands deep domain expertise.

By Rahul Agarwalla

The AI boom is real. But booms, by nature, attract indiscriminate capital. Investors are rushing to get exposure, often throwing capital into anything with ‘AI’ in the pitch deck. Yet, not every AI company is built equal, and the market is beginning to separate real innovation from noise.

Take the example of InVideo AI, a prosumer video-editing platform that has become one of India's fastest-growing AI-first companies, with explosive revenue growth. These are the kinds of enterprises redefining scale and profitability at speeds previously thought impossible.

In every emerging wave, early winners build moats not just with capital but with hard tech, proprietary data advantages, and a deep understanding of solving real-life problems with the help of AI. In AI, these moats are harder to see from the outside.

AI’s Ascent Is Faster and Bigger Than the Internet

Every revolution follows a curve. For the internet, it took nearly 25 years to build the trillion-dollar digital economy. AI is doing it in the blink of an eye. What the internet achieved in decades, AI is compressing into years. The scale and speed of this transformation are not just unprecedented; they are exponential.

In the last year alone, global investments in AI startups have surged past $100 billion. India, too, has seen over $1.3 billion invested in AI startups—a staggering figure considering the nascency of the ecosystem. These are not just numbers on a spreadsheet; they are indicators of an industry undergoing hyper-acceleration, rewriting the playbook across sectors from manufacturing to defence, healthcare to finance.

Why AI Investing Needs More Than Capital

AI is not a sector; it is a foundational technology reshaping every industry. Yet, the lack of public market analogues makes it harder for traditional investors to benchmark. Unlike the consumer internet wave, where public listings offered clear signals, India’s AI landscape has no Infosys or TCS equivalent. The best AI-native startups are still private and highly technical.

This asymmetry creates risk. It’s not just about identifying a company riding the AI wave; it’s about finding companies building the wave. Companies that are AI-native—those architected from Day Zero to leverage AI's full capabilities—tend to outperform mere adopters who treat AI as a bolt-on feature.

In such a landscape, access to market insights, deep technical due diligence, and founder evaluation frameworks become non-negotiable. This is where venture firms with an AI-first focus—those embedded in the technical evolution of the field—play a critical role. They aren’t just capital providers; they are curators and accelerators of what will become tomorrow’s AI champions.

Smart Investing Is About More Than FOMO

The velocity of AI's growth has created a pervasive fear of missing out (FOMO). But investing on impulse is a quick route to getting burned. In AI, moats are technical, invisible, and require a deep appreciation for how models evolve, how data is captured and utilised, and how defensibility is sustained as open-source models become increasingly commoditised.

Today’s best AI companies understand this nuance. They invest heavily in proprietary datasets, deploy fine-tuned models, and build vertical AI stacks that serve highly specific markets with deep expertise. These are not features one can discern from a glossy pitch deck. They require domain understanding and early, hands-on engagement with founders.

Beyond Capital: The Real Value Lies in Strategic Support and Timing

Investing in AI requires more than just capital; it demands deep domain expertise. The startups that win aren’t chasing trends—they’re solving real problems with AI, creating deep moats. Many companies fail because they compete in spaces where big tech can easily dominate. The real opportunity lies in identifying solutions to complex, niche problems that are too difficult for the giants to conquer.

But investment is just the starting point. The true value comes in the exit. The journey from investment to exit—especially in early-stage ventures—is riddled with challenges. Success isn’t just about making the right investment; it’s about guiding startups, mentoring founders, and ensuring the right exit at the right time. This support and the strategic exit often matter more than the initial investment.

This is how investors lose money. It’s not enough to just invest in a startup; you need to actively support it through its growth. And organised, domain-focused funds with deep AI expertise are critical to navigating this fast-evolving landscape and ensuring success.

Cut Through the Clutter, Get a Piece of the Action

We are in the early innings of what will be the most transformative technology cycle in modern history. But unlike past waves, AI’s curve is steeper, faster, and less forgiving. In a world where advantage compounds rapidly, hesitation is costly.

Investing in AI isn’t optional anymore. It’s existential. The only question is whether you’re chasing the noise or charting a strategic roadmap. In the AI gold rush, it’s not enough to dig blindly. The true winners will be those who know exactly where to dig, how deep, and when to strike.

(Rahul Agarwalla, Managing Partner at SenseAI.)

Views are personal, and do not represent the stance of this publication.