Talent, Data, and Funding: Deep Dive Into Indian Mix For AI With a unique blend of talent, abundant data, and a lower cost structure, Indian entrepreneurs are not just building solutions for local challenges but also for the world.

By Jatin Desai

Opinions expressed by Entrepreneur contributors are their own.

You're reading Entrepreneur India, an international franchise of Entrepreneur Media.

Freepik

India's AI startup ecosystem is witnessing unprecedented growth, propelled by advancements in the technology stack. With a unique blend of talent, abundant data, and a lower cost structure, Indian entrepreneurs are not just building solutions for local challenges but also for the world.

THE INDIAN VANTAGE

One of India's most significant and most obvious advantages is its manpower. Over the years, we have seen the number of engineers, data scientists, and AI researchers grow exponentially. More than a third of the AI/ML engineers today in India have over three-five years of experience in the field. With the plethora of training programs being made available, we see this pool of talents continue to grow rapidly, with skilled individuals coming in from various domains. This means that Indian startups have lower operational costs and a competitive edge over other regions. Furthermore, India is a data-rich nation with over a billion people generating vast amounts of data from digital payments, e-commerce, and transportation every day. We have a diverse and complex society with unique opportunities for AI innovation- from solving logistical challenges in rural areas to optimizing urban pollution management, from addressing traffic congestion to improving agricultural productivity. The country provides an unparalleled testing ground for Indian startups to refine and enhance their algorithms more effectively.

By catering to the domestic market, these startups can gain valuable insights into consumer preferences and behavior, enabling them to tailor their products to specific needs. The success of these solutions in India can serve as a springboard for expansion into international markets, leading to a continued trust of investors, evident from the fact that in 2023, the investment in AI in India reached 1.4 billion U.S. dollars, making India one of the top 10 leading countries in AI investment.

ENTERING THE ECOSYSTEM

AI is being integrated into nearly every industry- in many cases resolving long-standing hurdles. However, founders should understand that following the meta is not the right approach. We need AI solutions born out of a deep understanding of industries.

For example, over 19,000 dialects are spoken across India- an accessibility challenge being taken up by startups with NLP. They are developing AI models that recognize dialects across a multitude of Indian languages, facilitating better user experiences in regional markets, customer support systems, and government interfaces. This experience and technology can further power tools for global markets. AI has the potential to address crucial vulnerabilities across sectors. Founders should start with conversations with the right audience, to gain insights, and find unique problems that can be solved with AI/ML. Focus should be on building data assets, creating systems that encourage ongoing improvement, and paying attention to distribution channels. Implementing MLOps and having good model governance will help companies build real applications while keeping ethical concerns in mind.

THE PRODUCTIZED APPROACH

High scalability of AI products have resulted in a surge in venture capital interest, particularly in start-ups offering productized AI solutions, tailored for specific domains, demonstrating strong value propositions. When choosing products, enterprises value outcomes as much as the technology behind the product. Hence, when over 70 per cent of executives endorse the application of AI, it is because of its value proposition as a product that solves specific problems and integrates seamlessly into existing systems. There is a greater demand for productized AI models that offer exponentially greater reliability and efficiency over general-purpose AI. The future of AI will be dominated by use-case specific models. Having a moat that is not just data but also a unique approach or innovation in conjunction with the data is going to be recognized and rewarded by the market.

Jatin Desai

Managing Partner, Inflexor Ventures

Business Ideas

70 Small Business Ideas to Start in 2025

We put together a list of the best, most profitable small business ideas for entrepreneurs to pursue in 2025.

Branding

Creating a Brand: How To Build a Brand From Scratch

Every business needs good branding to succeed. Discover the basics and key tips to building a successful brand in this detailed guide.

Innovation

It's Time to Rethink Research and Development. Here's What Must Change.

R&D can't live in a lab anymore. Today's leaders fuse science, strategy, sustainability and people to turn discovery into real-world value.

Marketing

How to Better Manage Your Sales Process

Get your priorities in order, and watch sales roll in.

Business News

AI Agents Can Help Businesses Be '10 Times More Productive,' According to a Nvidia VP. Here's What They Are and How Much They Cost.

In a new interview with Entrepreneur, Nvidia's Vice President of AI Software, Kari Briski, explains how AI agents will "transform" the way we work — and sooner than you think.

Starting a Business

Passion-Driven vs. Purpose-Driven Businesses — What's the Difference, and Why Does It Matter?

Passion and purpose are both powerful forces in entrepreneurship, but they are not the same.