On this page
Glance bets on AI shopping agents to reshape discovery, selection and pricing
Our read
AI shopping agents will make product-data quality and fulfillment credibility as important to retail visibility as search ranking and marketplace advertising are today.
For operators
Prepare product catalogues, pricing and quality signals for machine readability as AI shopping agents increasingly determine discovery and recommendation visibility.
Watch
Major AI assistants introduce native checkout, product comparison or persistent shopping-agent capabilities.
The report,
InMobi founder Naveen Tewari says AI shopping agents will reshape product discovery, selection and pricing, requiring brands to optimise structured product data and quality for machine recommendations. Glance positions itself as an AI-powered commerce intermediary rather than an inventory-holding marketplace.
Reported figures
From the report. Source details below
- next decade
Other figures
- 200 brands
Why it matters to operators
Prioritize partnerships or acquisitions in structured product data, AI recommendation infrastructure and commerce intelligence to secure relevance in the emerging agent-led shopping stack.
What to watch next
- Retailers and brands publish standardized agent-commerce feeds or APIs for live price, inventory and fulfillment data.
- Evidence that AI-referred orders deliver lower search costs but higher returns, lower loyalty or weaker customer-data capture.
- Growth in paid agent recommendations, affiliate fees or ranking auctions.
- Consumer adoption of delegated purchasing for replenishment, electronics, travel-like comparison purchases and high-consideration categories.
- Regulatory scrutiny of sponsored AI recommendations, pricing transparency, data use and ranking disclosure.
Likely next moves
Our read of what comes next — analysis, not reported by the source.
- Build agent-readable product feeds covering specifications, variants, availability, delivery promises, return policies, certification and review quality.
- Create a product-data governance function linking merchandising, marketplace operations, pricing, inventory and customer-service data.
- Test AI-agent referral partnerships and measure incremental conversion, average order value, return rates and customer ownership loss.
- Shift retail-media strategy from keyword and display buying toward sponsored recommendations, structured product signals and conversion-quality bidding.
- Develop dynamic-pricing guardrails to prevent agent-driven price matching from eroding margin or violating channel agreements.
The counter-case
The case against this reading — not reported by the source.
AI shopping agents may improve search and recommendations without fundamentally displacing marketplaces, retailer apps, or search engines. Consumers still value trusted retail destinations, human browsing, loyalty benefits, delivery certainty, returns, and the ability to compare across merchants. Glance's intermediary position is also vulnerable: platforms with first-party purchase data, checkout control, ad budgets, and proprietary ecosystems can build or privilege their own agents. Machine-readable catalogues and quality signals may become table stakes rather than a defensible advantage, while agent-led price comparison could compress margins and push brands toward paid placement.
The source
Published
First seen