E-commerce marketplace Meesho is gearing up for a future where product discovery increasingly shifts to AI-powered chat assistants, even as adoption of these tools among its core users in small-town India remains uneven and continues to evolve.
To be sure, chat-based artificial intelligence (AI) assistants are gaining traction among a subset of users, especially in urban markets. However, it is still unclear how quickly they will become mainstream across the broader internet population, Sanjeev Kumar, co-founder and chief technology officer of Meesho, told Mint in an interview.
“It’s not either-or, it’s both,” Kumar said, referring to the company’s approach of building for emerging AI-driven discovery channels while continuing to strengthen its core in-app shopping experience.
On Wednesday, Meesho rolled out a conversational , “Vaani” (Hindi for voice), aimed at making online shopping more intuitive for users who prefer conversational, offline-style interactions.
The move reflects a broader shift in how the company is thinking about growth – not just in terms of adding new users, but also in how quickly those users become comfortable shopping online.
“For us, this goes beyond accessibility. There’s an opportunity to reimagine the shopping experience itself,” Kumar said.
“Such AI-led tools could act as an early enabler, especially for users in tier-II and tier-III markets who may need assistance with language, price comparison and navigation, helping expand the overall addressable market for e-commerce,” said Ankur Bisen, senior partner at The Knowledge Company, a consultant.
However, he said that adoption is still at an exploratory stage, with even tech-savvy users continuing to discover use cases.
The push comes at a time when e-commerce growth is becoming harder to sustain. Platforms are competing for a largely overlapping user base, while acquiring new customers, especially from smaller towns, remains slow and expensive. Retention is also a challenge, with users often switching platforms based on pricing and promotions.
Bisen added that while may initially drive engagement, they are unlikely to remain a differentiator for long. As more platforms adopt similar tools, these features could quickly become a baseline expectation or “hygiene factor”, much like faster delivery timelines did in the past.
Meesho’s bet on AI is aimed at both reducing friction for new users to transact, while making the experience engaging enough for existing users to stay, according to Kumar. Technology investment is a top priority for Meesho, with a large portion of its ₹4,250 crore fresh issue through the initial public offering earmarked for hiring and strengthening its tech stack, Meesho chief executive officer Vidit Aatrey told Mint in December.
At 12:06 pm, Meesho’s shares traded 1.6% higher at ₹153.10 apiece on the BSE.
Discovery beyond search
The company’s approach is shaped by how its users shop. Nearly 75% of orders on Meesho come from recommendations rather than search, indicating that many users browse without a clear purchase intent.
This has pushed the company to move beyond traditional search-led interfaces. Instead, it is experimenting with more interactive formats that allow users to explore products closer to how offline shopping works.
Kumar said such changes could help shorten the time it takes for new users to start transacting. “What would have taken months earlier… can now happen much faster,” he said.
Early data indicates a noticeable impact. Meesho said users engaging with its conversational assistant show a 22% higher conversion rate, besides fewer returns and cancellations.
The company’s AI systems also track shifts in user behaviour, such as changes in price sensitivity or category preferences, and adjust recommendations accordingly. These insights feed into supply decisions as well, influencing the kinds of products and price points the platform prioritises.
Kumar said scale strengthens this approach. With data from over 250 million users, Meesho is able to refine its understanding of customer behaviour and apply it to similar cohorts.
At the same time, the company is addressing marketplace challenges such as ensuring fair visibility for sellers and handling products with limited data. Its algorithms are designed to reduce bias and improve how such products are surfaced, Kumar said.
Even as Meesho prepares for an AI-led shift in discovery, broader adoption trends remain mixed. A recent survey by non-profit organisation JanAI found that 55% of rural youth use almost daily, suggesting growing familiarity, though usage is still concentrated in areas such as learning and communication rather than commerce.