For most of retail’s history, the customer at the end of the transaction was human. They clicked, they compared, they second-guessed.
What is now emerging from the convergence of artificial intelligence, stablecoins, and open payment protocols is something categorically different: a buyer that is software, moves at machine speed, and settles money autonomously.
The Agentic Economy Report by blockchain firm Morph calls this shift “agentic commerce“, and the numbers it cites suggest the shift is not coming. It is already here.
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During a single Cyber Week in December 2025, Salesforce counted US$67 billion in global spend that AI agents directly influenced, out of US$336.6 billion in total retail volume. Adobe, tracking the same holiday season, recorded a 693 per cent year-on-year surge in generative AI-driven retail traffic. McKinsey, which has been sizing this market for two years, now puts the total addressable opportunity at US$1 trillion in US B2C retail revenue and US$3 to US$5 trillion globally by 2030.
The Morph report makes a specific, falsifiable prediction: agent-influenced commerce will cross US$500 billion in global gross merchandise value by the end of 2028. The arithmetic, it argues, is not aggressive. It requires the category to compound at roughly the pace Cyber Week already demonstrated, across two more holiday cycles.
The anatomy of an agentic transaction
Understanding why this matters for Asia requires understanding what actually happens in an agentic transaction.
When an AI agent buys something on a user’s behalf, it must solve four sequential problems.
- Identify itself to the merchant (identity)
- Prove the human actually authorised the purchase (mandate)
- Negotiate cart, tax, shipping, and returns (checkout)
- Move money (settlement).
Each of these layers now has at least one credible open standard in production. Google shipped the Agent Payments Protocol (AP2) with more than 60 launch partners, including a native extension for stablecoin settlement. Stripe and OpenAI released the Agentic Commerce Protocol, which can be implemented as a RESTful API or a Model Context Protocol (MCP) server. Shopify’s Universal Commerce Protocol, co-developed with Google, is the first cross-merchant cart standard, enabling a single agent to combine products from multiple sellers in a single session. On Ethereum, ERC-8004 went live on mainnet in January 2026, giving agents a portable identity that is not owned by any single platform.
The structural implication is significant. In the card era, Visa and Mastercard owned the token and, therefore, the customer relationship. In the mobile era, Apple and Google extracted rent through the wallet. In the agentic era, as the Morph report puts it, “no single company owns the primary customer relationship. The agent becomes the wallet. The protocol becomes the network.”
What this means for Asia’s merchants
For Southeast Asian and broader pan-Asian merchants, the consequences of this shift are both an opportunity and a threat. On the opportunity side, agentic commerce collapses the friction that has historically disadvantaged cross-border commerce in the region. An agent shopping on behalf of a user in Jakarta or Bengaluru faces the same latency and checkout friction as one shopping in San Francisco — none, by design.
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Walmart in the United States has already pulled its Q1 2026 integration from OpenAI’s Instant Checkout to embed its AI assistant Sparky directly into ChatGPT and Gemini, bypassing the traditional search results page. Salesforce reports AI-channel conversion rates running 700 per cent above social commerce and 200 per cent above organic search.
The high-intent commercial query, the moment a consumer decides to buy, is migrating away from search engines and into AI chat interfaces. Asia’s merchants, many of whom have built their entire growth models on Google Shopping and Meta performance marketing, have not yet reconfigured for this reality.
The Morph report’s Prediction 6 is perhaps the most alarming for brand-heavy categories common across Asia’s consumer markets: agents, it argues, will collapse the brand premium. Comparison-shopped goods, it predicts, will see real-price declines of 10 per cent or more within the prediction window.
BCG research already finds that large language models directly influence up to 20 per cent of purchasing decisions and that agents compare products across a far broader range of price, review, and delivery-speed signals than human shoppers practically can. When a machine with near-perfect information shops on a consumer’s behalf, brand equity, bundling strategies, and choice paralysis stop functioning as pricing defences.
The last time comparison transparency rose this quickly, during the first wave of e-commerce, it took roughly 15 per cent off consumer electronics margins within a decade. Agents, the report warns, will compress a similar shift into a two-year window in comparison-heavy categories.
The habit is forming faster than merchants realise
Consumer readiness is further ahead than most merchants in the region assume. US adult AI tool usage is already estimated to be above one-third, with ChatGPT alone reporting hundreds of millions of weekly active users. Prediction 10 in the Morph report states that by 2028, 1 in 10 US households will regularly allow an AI agent to complete a purchase on their behalf. The comparison drawn is instructive: smartphone penetration crossed 20 per cent of US households roughly 30 months after the iPhone launched. Consumer agent purchases are tracking a faster adoption curve from a higher starting base.
Asia’s mobile-first consumer base, where app-based commerce, super-apps, and social commerce have already compressed multiple technology cycles, is arguably even more primed for this transition. The infrastructure question is not whether agents will buy on behalf of Asian consumers. It is whether Asian merchants, payment rails, and platforms will be ready to accept them when they arrive.
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Cart abandonment, the Morph report notes drily, will stop being a useful KPI. “Agents do not abandon carts. They switch merchants.”
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