Artificial intelligence (AI) has become a significant part of consumer reality. Many of us are spending more time talking to AI assistants like ChatGPT to draft communications and build knowledge, interacting with AI customer support agents while buying products or escalating customer issues and consuming AI-generated content—often without consciously realising it.
We see a lot of excitement alongside healthy scepticism. Are we retrofitting AI into existing consumer solutions or building AI-native solutions to consumer problems? Is AI really adding any value or is it just a buzzword? The answers are becoming clearer.
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2 March 2026
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From the user’s perspective, new consumer AI start-ups have dramatically improved affordability and personalisation across many services. Historically, services like personal assistants, stylists or wealth advisers are premium offerings due to high human costs. AI changes this equation by making these affordable to the mass market while enabling consistent quality outcomes.
More importantly, AI enables personalisation at scale. Instead of blanket solutions designed for cohorts of “similar” users, products can adapt to the individual—learning from past behaviour and preferences.
Though price sensitivity is high in india, growing middle-class and time-rich consumers are creating deep opportunity pools for consumer AI
Think of an AI tutor that adjusts its teaching style based on how you learn rather than how the class learns. We believe Indians are just starting to see the potential of how AI can make their lives better.
Another recurring question that comes to mind is—do users really care if a product is AI-first or AI-enabled? Maybe not. Adoption happens when AI quietly runs in the background and solves real problems significantly better than existing alternatives. But what are the right problems for AI to solve? We believe AI has a natural advantage in areas where expertise is scarce, expensive and/or specialised and can often enhance the effectiveness of human specialists.
Reshaping Life
We are seeing early verticalisation across several themes like education, content, companionship and commerce.
In education, perhaps the most obvious frontier, learning is inherently feedback-driven and traditionally reliant on human attention—making it expensive and difficult to scale while maintaining quality. AI changes this by enabling real-time assessment, correction and personalised learning journeys at scale. Language learning and exam preparation are especially promising with start-ups like Supernova and Disha AI leveraging AI well for personalising user journeys.
The rise of multimodal AI has also reshaped content. AI tools can now generate, remix and personalise content across formats—entertainment, learning, shopping, etc. We recently invested in Chai Shots, which uses AI to create micro drama series. The line between creators and consumers is also blurring due to AI democratising content creation.
AI assistants are also emerging as companions offering conversation, guidance and emotional support without social friction and fear of judgement. We invested in Rumik AI, which has seen massive adoption. It has strong engagement and retention since its AI companion has a plethora of context about its users and converses with empathy. In professional settings, it is reshaping networks by improving access to experts, enabling faster discovery of relevant individuals, and accelerating hiring and collaboration.
When it comes to commerce, AI’s role is increasingly about curation and decision support. Traditional marketplaces have solved access but created clutter. AI can help users navigate abundance—by recommending what is 'right for me', acting as stylists or personal shoppers.
We are also seeing similar capabilities in categories like health coaches, financial advisers, accountants, travel agents—where the value of informed, personalised decision-making is high. We invested in 30Sundays, an AI-run platform that provides personalised holiday planning and booking to mass affluent users. It is seeing a strong consumer net promoter score with referrals and repeats.
Changing the Game
Notably, a new generation of Indian consumer AI founders is building global platforms from day one, with a promising cross-border traction. For example, we are investors in Shoppin, which is an AI-powered global social platform for fashion discovery and commerce with personalised feeds with the US as its largest market. Start-ups like Airlearn and Lingopanda are also changing the game in language learning for overseas learners.
Despite the excitement, monetisation and financial viability remain open questions. Consumer AI products face high server, distribution and talent costs. Only a small fraction globally has achieved strong engagement, retention and monetisation. In India, price sensitivity is high, though a growing middle class and time-rich consumers create deep opportunity pools.
When building an AI product is so easy, the bar for quality becomes much higher to truly break out. And then maintaining the differentiation while building on data and context needs the team to be always ahead in innovation and execution. Legal and ethical considerations are critical—especially where users may not know they are interacting with AI or risk becoming addicted to AI personas.
At Info Edge Ventures, we remain deeply excited about consumer AI. The intelligence is here, exceptional founders are building and consumers are experiencing delightful products and services than ever before.
(The writer is partner, Info Edge Ventures)
