Will the RBA regulate the role of AI in making payments?
Artificial intelligence may soon do more than recommend what you buy. It could make the payment as well.
This emerging system is called agentic commerce. A consumer could tell an AI agent to find the cheapest flight to Melbourne, choose an acceptable departure time and complete the purchase — without the consumer manually visiting websites or entering payment details.
The Reserve Bank is now considering what that could mean for Australia's payments system.
Its latest payments review identifies four potential problems.
First is competition. An AI agent may choose which card network or payment provider processes a transaction. If commercial arrangements cause an agent to favour Visa, Mastercard or a particular payments provider, merchants could lose some ability to choose cheaper payment routes. That could undermine policies such as least-cost routing.
Second is cost. AI inserts another intermediary between the consumer and merchant. One submission cited reports that an AI-enabled purchasing channel had imposed an additional 4% merchant fee. The RBA has not established that such fees will become standard, but the example illustrates the risk of another payments layer adding costs.
Third is liability. Suppose you authorise an AI agent to spend $500 but it spends $800. Who bears the loss — the customer, bank, merchant, card network or AI provider? Existing chargeback arrangements were not designed for autonomous software making purchasing decisions.
Fourth is security. An AI agent could be manipulated, hacked or impersonated and then initiate unauthorised transactions.
Importantly, industry submissions generally advised the RBA not to regulate yet. Agentic commerce remains immature, evidence of actual harm is limited and premature rules could inhibit useful innovation. Stakeholders instead favoured monitoring and industry standards covering authority, transaction identification and liability.
The RBA will announce its regulatory priorities by the end of 2026.
The underlying question is new but fundamental: when software starts spending our money, who decides what it is allowed to do — and who pays when it gets the decision wrong?
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