Amazon, Flipkart & Meesho’s AI Focus Shifts To Seller-Side Stacks

For much of the past two years, the AI race in Indian ecommerce revolved around the consumer. 

That meant the likes of Amazon, Meesho, Flipkart invested heavily in AI-powered search, personalised recommendations, conversational shopping assistants and customer support aimed at making product discovery easier and improving conversion rates.

As generative AI matured, companies increasingly positioned these tools as the next evolution of online shopping.

These ecommerce giants are now racing to build AI for the seller side instead, in the hope that locking in sellers to their platforms and creating deeper relationships can become a competitive advantage. 

From marketplace algorithms gradually replacing keyword search optimisation, to automated advertisement targeting, to AI-generated digital product catalogues, the marketplaces are now competing to lure millions of sellers, many of them first-time, non-metro entrepreneurs, onto an in-house AI stack, with the promise of better business outcomes.

This shift, according to the industry analysts and executives we spoke to, could also lead to the next lever of growth as consumer acquisition through conventional marketing and advertising have become increasingly expensive and competition for online shoppers remains intense.

Marketplaces’ focus on improving the efficiency of millions of sellers, meanwhile, has the potential to improve catalogue quality, product discovery and conversion across the entire marketplace, which eventually could scale seller/marketplace revenues.

Meesho, Amazon, Flipkart Race To Build AI Seller Stack

Amazon, ahead of its Prime Day Sales 2026, launched an AI-powered seller assistant for its 1.7 Mn Indian sellers, built on Amazon Bedrock using Amazon’s own Nova models alongside Anthropic’s Claude.

Instead of clicking through multiple pages in Seller Central, a seller can ask, in plain English or Hinglish, for help with onboarding, catalogue creation, inventory management, business insights, or expanding to a new country.

“Today, a small seller operating from a single room has access to the same state-of-the-art intelligence that powers the world’s largest commerce operations. What excites us most about this Prime Day is that we are not simply giving sellers new tools—we are building AI that works alongside them, helping them start, manage, and grow their businesses,” said Abhijit Kamra, director of seller experience for emerging markets for Amazon India, in an earlier statement.

Amazon says sellers using the tool have cut listing errors by 10% and routine operational work by nearly 70%.

Rival Meesho’s AI voice system for sellers now handles up to 300,000 calls a day, per the company’s Q1 FY27 shareholder letter, helping sellers through onboarding, catalogue creation and sale-event participation.

Meesho also said that its annual transacting seller base stood at 1.04 Mn, up 81% year-on-year, with Tier 2-and-smaller towns making up 45% of the base.

Meesho cofounder and CTO Sanjeev Barnwal told Inc42 that AI has changed the pre-sales and post-sales journeys of sellers, with cost efficiency as the biggest lever. Right from product discovery — which product gets shown to which shopper — Meesho is letting AI decide the listings.

“In our company, for instance, the core marketplace ranking effort started about five years back,” Barnwal added, describing it as the only realistic way to run a marketplace at Meesho’s scale.

Eliminating human intervention in product rankings, he said, also means balancing metrics like relevance, fairness, new-seller inclusion, revenue and quality against each other — a live tension on horizontal marketplaces, where third-party sellers have long alleged that some platforms favour their own brands’ listings.

In particular, Amazon India had come under fire for leveraging data from D2C brands sales and customer engagement to launch private label brands in the past. For many sellers, the algorithm is where the buck stops. 

Barnwal argued that investment in ranking algorithms can be a genuine unlock for sellers who have little-to-no sales history. Such brands and sellers would otherwise stay buried among tens of thousands of listings, but this raise the question of algorithm bias, particularly when ecommerce companies are pitching AI stacks for sellers.  

Flipkart has spun out its AI-centric seller stack to third-party sellers as a product. Flipkart Commerce Cloud (FCC), the group’s retail tech arm, sells an “AI-ready commerce stack” to other retailers, which is built on scale-tested data from billions of Flipkart transactions.

The ecommerce giant, through its native AI tools, has focussed on sellers from the smaller cities, assisting them with access to demand forecasting, pricing intelligence, and trend analysis previously unavailable to businesses of their scale.

Sellers on the platforms can make various business-related decisions like inventory storage, manufacturing and product pricing, based on the insights from marketplace AI models.

Flipkart stated that initial pilots of giving access to simplified AI dashboards to sellers have proven to be a success, especially for retailers from Tier 2, 3 towns and beyond, as processes like seller onboarding and day-to-day operations became more efficient. The company claims to have seen a growth of 80-85% in new seller onboarding from Tier 3, 4 towns this year compared to last year, with AI tools integration.

Does AI Guarantee Real Returns For Sellers?

For years, ecommerce platforms competed primarily on traffic and customer acquisition.

Sellers, in turn, invested considerable effort in understanding marketplace algorithms, manually improving catalogue quality, experimenting with keywords, adjusting prices and running advertising campaigns to improve visibility.

Increasingly, AI is taking over many of those operational tasks.

“Marketplace AI is changing the economics of building a consumer brand. Earlier, better execution often depended on having larger teams or bigger budgets. Today, platforms like Amazon, Flipkart and Meesho are embedding intelligence directly into the seller ecosystem, making it easier for brands to make faster decisions around listings, advertising, pricing and demand. That makes these tools genuinely valuable, especially for emerging brands that need to do more with leaner teams,” Neel Gogia, cofounder of IPLIX Media and Layers, which recently launched the fragrance brand Sarkar, said.

One of the major challenges facing ecommerce brands/sellers previously used to be the listing anomalies and concerns on some private-label brands/sellers being prioritised on listings/rankings by marketplaces.

“The real impact of marketplace AI is that it raises the standard for everyone. If every brand has access to similar optimisation tools, execution stops being a competitive advantage and becomes the baseline. The brands that win will be the ones that combine technology with great products, consistent consumer experiences and a point of view that’s difficult to replicate. AI can make brands more efficient, but it still can’t make them distinctive,” Gogia added.

Apurv Agrawal, cofounder of the women’s health brand Avni Wellness, describes a similar shift.

“We believe AI will fundamentally redefine what it means to be a successful marketplace seller over the next few years. Platforms like Amazon and Flipkart are no longer just enabling transactions, they’re building intelligent commerce infrastructure that can help businesses make faster and better decisions. This shift has the potential to level the playing field, allowing smaller brands to compete with much larger players by giving them access to capabilities that were once expensive and resource-intensive,” Agrawal said.

While the brands are still gauging the real sales impact driven by AI-led cost efficiencies, the sellers say that there is a huge leap in minimising time and workforce expenses on operations due to the adoption of AI tools.

“The real advantage is that it compresses time. What previously took teams of people days to accomplish creating optimised listings, managing ad campaigns, forecasting demand, or identifying pricing opportunities can now be achieved in a fraction of the time. For founders, time is often a more valuable currency than money, because it allows us to focus on building products, understanding customers, and scaling the business,” Agrawal of Avni Wellness said.

Where Are The Bottlenecks?

Sellers also flag that any AI tools being used by the ecommerce marketplaces should be as a co-pilot and not as an autonomous agent.

“Algorithms can optimise for clicks and conversions, but they cannot replace a founder’s intuition, customer empathy, or long-term brand vision. The brands that will win are those that combine AI-driven efficiency with authentic storytelling and a deep understanding of consumer needs which still remains relevant,” Agrawal noted.

Sellers also note that the mere access of the newest AI tools to the brands will not alone solve the challenge of scaling unless these small businesses intelligently leverage the tools to automate various monotonous tasks and uphold the customer trust at all levels.

According to Snapdeal’s recent Bharat Seller Report 2026, AI adoption among ecommerce sellers is gathering pace.

Nearly 46% of sellers said more than three-fourths of their business now comes through online channels, increasing their dependence on marketplace algorithms and platform decisions.

At the same time, almost half of respondents identified pricing and discounts as the primary driver of consumer purchases, suggesting that while AI may improve discoverability, it cannot fundamentally alter the economics of a highly price-sensitive market. Another 44% of surveyed sellers reported not using AI tools at all, indicating that adoption remains uneven despite rapid investment by marketplaces.

Despite increasing discussion around AI-driven advertising efficiency, none of the major marketplaces publicly disclose audited, India-specific data for returns earned by sellers on their advertising spend for ecommerce.

Amazon has shared operational improvements such as reduced listing errors and faster workflows, while Meesho speaks about AI improving seller ROI without publishing platform-wide benchmarks. Flipkart’s Commerce Cloud similarly highlights customer case studies rather than representative marketplace-wide outcomes.

AI is steadily moving from consumer-facing experiences to the operational backbone of ecommerce, influencing everything from product discovery and cataloguing to pricing, advertising and seller support. What remains less certain is the magnitude of the commercial advantage these systems ultimately create for sellers.

For now, marketplaces appear to agree on one thing. The next phase of competition in ecommerce may not be won solely by attracting more shoppers, but by making it easier for millions of businesses to sell more intelligently.

[Edited By Nikhil Subramaniam]

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