In under two years, more than 100 startups have emerged across the country with a singular focus—creating AI systems that not only understand prompts but also take autonomous actions. In a country with over 750 million smartphone users, only a minuscule percentage are using the AI agents.

While there is a need for coding copilots or workflow agents for autonomous QA testers in startups and enterprises, direct-to-consumer products face almost no demand at all.

Despite this, India’s agentic AI landscape is growing fast. Startups claim there’s a consumer boom, but there’s no reliable data to prove the same. Besides,  retention or monetisation is a concern in India. 

There are now 109 active agentic AI companies in India, according to data from Tracxn. These startups are working on tools that can not only generate text or images but also act on behalf of users, completing tasks, automating workflows, and mimicking decision-making. 

On paper, it sounds like the future. In practice, there’s one big missing piece: users. 

India’s Real AI Use Cases Are Still Enterprise

In recent months, companies like Krutrim, Fractal, Sarvam, Puch AI, and Gnani AI have started positioning themselves as pioneers of consumer-facing agentic AI. They’ve launched assistants, image generators, and voice bots aimed at India’s “mobile-first” population.

Krutrim, backed by Ola’s Bhavish Aggarwal, unveiled Kruti, a personal AI agent that can book cabs, order food, generate images, and conduct research. 

Fractal, traditionally an enterprise player, launched tools like Kalaido and Vaidya. Gnani entered the fray with Inya AI, which lets users create plug-and-play voice/chat agents.

Most agentic tools today are proof-of-concept apps masquerading as consumer products. There is little public data on active user numbers, retention, or monetisation. Nearly all platforms remain in beta, offered for free, or targeted at developers and enterprise teams rather than end consumers.

Even Bhashini, the government’s flagship voice translation tool, remains in beta with limited traction, underscoring how even well-funded public efforts have yet to achieve sustained consumer usage.

The consumer-agentic AI story in India remains aspirational, built more on pitch decks than on product-market fit. 

Contrary to the emerging B2C narrative, most agentic AI traction in India is still occurring within enterprises, albeit at a slower-than-expected pace. Companies like Meritto and RevRag are building agents for education and BFSI workflows, not for end-users. 

These agents manage lead qualification, sales automation, or perform call centre support tasks that seldom appear in consumer apps. Even as these companies talk about eventual B2C relevance, their paying users remain institutions, not individuals.

Even selling B2B comes with challenges. Ashutosh Singh, co-founder and CEO of RevRag, had earlier told AIM in India that the sales cycles are slow and decision making is layered with bureaucracy. 

However, one of the biggest myths Singh wants to dispel is that Indian clients don’t pay. “It’s not about inferior tech or lack of money. It’s a game of volume and patience,” he said. “You invest first, like Zomato did, and then you start getting money once the volume kicks in.”

A great example of this is Sarvam. The company has developed the Samvaad platform to enable companies to create conversational voice agents in Indic languages for their platforms, which include WhatsApp and on-call features. 

There is a demand among enterprises and small businesses, but Sarvam did not launch a consumer app, as that requires scaling for the population, which is often better left for companies to do themselves.

Agentic Means Scale

For agentic AI to succeed in India at scale, it requires two key components: infrastructure and interfaces. India lacks widely adopted platforms where agents can plug in. 

To be sure, even the world’s leading startups, such as OpenAI and Anthropic, have not yet successfully launched agents that can perform everyday tasks on a user’s behalf. For example, Perplexity has a shopping agent which can order things for users. However, arguably, it remains easier for people to head to Amazon and order items.

Similarly, the typical Indian consumer juggles a dozen apps, none of which are built to support AI-driven autonomy. Paytm recently announced that it is becoming an AI-first company, with a model that resembles a Superapp. However, even with the Perplexity integration, not much has been achieved in terms of agentic AI transformation.

Furthermore, consumer trust and understanding of autonomous systems remain low. While generative AI tools like ChatGPT and image generators continue to grow in demand, there’s little evidence of persistent usage for AI agents like Kruti, especially outside English-speaking urban clusters.

For example, AIM tested Krutrim’s Kruti app during the launch, and while it looks promising, the issue remains that it is a separate app which only orders through Ola services as of now, such as food and ordering cabs. 

For most users, switching apps to book the same cab makes no sense. And Kruti’s promise of autonomy feels like a detour, not a shortcut.

As AI enthusiasm surges globally, Indian startups are rushing to position themselves as leaders in the agentic wave. But without sustained local adoption, many risk becoming export-oriented tech demos, building for users halfway across the world, or worse, building for a market that doesn’t exist at all.

Until Indian consumers demonstrate a real need for autonomous agents and a willingness to pay, agentic AI in India may remain more fiction than function.

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