E-commerce won’t be the same again once AI Agents start shopping for us

Data from developed markets suggests that this shift is already meaningful, with 25–40% of users in the US engaging AI tools for product discovery, comparison and decision-making.

It is critical to distinguish between AI-assisted and AI-executed commerce. While fully autonomous agent-led transactions are still early, the influence layer—where AI shapes decisions—is already at scale. This matters because influence precedes monetization. Once decision-making shifts, value pools follow.

Unlike earlier digital shifts, Agentic AI is not building new infrastructure—it is riding on existing rails. Payments, logistics, merchant networks and digital behaviour are already in place.

Here’s a realistic adoption curve—Near term (0–2 years): AI-led discovery and recommendations scale; medium term (2–4 years): Early agent-led transactions in repeat categories; long-term (4–6 years): Scaled autonomous commerce.

The speed of this transition is likely to outpace the original e-commerce adoption cycle in India and other global markets.

The most immediate economic impact is improved conversion. Early evidence suggests higher conversion rates and revenue per visit from AI-origin traffic, in some cases exceeding traditional channels.

But this efficiency comes at a structural cost. E-commerce has historically monetized human attention—time spent browsing, comparing and discovering. AI collapses this layer. As decisions move from screens to systems, engagement declines and the value of traditional discovery weakens.

This shifts the role of platforms from demand influencers to execution engines. Fulfilment rather than discovery becomes the primary driver of differentiation.

Advertising, a key profit pool for e-commerce platforms (more than 80% operating profits for Indian as well as global e-commerce platforms are driven by advertisements), is directly exposed to this shift. The traditional model depends on visibility—sponsored listings, banner ads and search placement. In an AI-mediated environment, visibility is replaced by selection.

While hard financial disclosure is still limited, the direction is clear. As AI compresses decision-making, ad inventory tied to browsing becomes structurally less valuable. The monetization model won’t disappear but will evolve—from paid visibility to paid recommendation and algorithmic preference.

In the transition phase, platforms with high ad dependence may face pressure while those with stronger transaction-led monetization and first-party data are better placed.

Agentic AI fundamentally changes brand economics. In a discovery-led system, visibility could be bought. In an algorithm-led system, selection is earned. AI prioritizes measurable signals—ratings, repeat purchase behaviour, price-value equation and fulfilment reliability. This creates a structural advantage for trusted brands. Brand strength becomes more critical because it feeds into algorithmic decision-making.

Smaller brands are not excluded, but the success model changes. Growth shifts from marketing-led acquisition to product-led retention and credibility. Barriers to entry rise, even as digital access remains open. This could benefit large-scale brands with a higher recall value.

India lags developed markets in agentic commerce, but the gap may narrow faster than it did in traditional e-commerce. India’s e-commerce penetration (7% of retail) is below America’s (16%), but key enablers are in place: a large smartphone base, UPI payments and last-mile infrastructure. India does not need to build the rails; it needs to layer intelligence on top.

However, adoption will not be frictionless. India faces constraints around trust, data governance, language complexity and merchant readiness, which could moderate the pace of fully autonomous commerce.

As AI moves closer to execution, control over data becomes strategic. Consumers are already signalling caution—over 70% express concerns about how AI systems use their data. At the same time, platforms face a different risk: disintermediation.

If external AI layers control the interface, e-commerce players risk being reduced to back-end fulfilment providers. The long-term winners will be those who combine proprietary AI capability, strong first-party data and superior execution. This makes it necessary for large Indian consumer tech platforms to invest in AI initiatives.

Agentic AI is redefining competitive advantage in e-commerce. Discovery is being externalized, conversion is improving and monetization is shifting away from advertising towards transactions and data. The open questions are about speed of autonomy, ownership of customer relationships and the redistribution of value pools.

E-commerce is not ending, but discovery-led commerce is. In the next phase, success will not depend on capturing attention, but on being selected by the algorithm.

The author is executive vice president, Elara Capital.