Agentic AI and consumers

Source: Competition and Markets Authority (UK) · 2026-03-09

Definitions vary but these include AI agents that can be instructed in natural language to achieve a goal autonomously, navigating some complexity in the environment, planning, coordinating, and taking actions – potentially across multiple services.

AI agents that can plan and act with a degree of autonomy are already being deployed by businesses, but primarily in bounded and controlled ways. Deployment is concentrated in domains where scope and oversight can be tightly managed, including customer operations and service, commerce and sales workflows, software and IT operations and internal business process automation. In these settings, agents are used to progress multi step tasks – such as handling customer service requests, processing refunds or coordinating transactions – rather than simply providing information. Consumer facing authority remains limited and escalation to humans is common. Deployment in high stakes or fully consumer autonomous contexts remains limited.

In the near term, agentic AI may become more visible to consumers as systems move beyond single tasks towards goal oriented assistance. Plausible developments include forms of agentic commerce – where agents monitor prices, availability or contract terms over time and initiate defined actions – and more integrated personal assistants that coordinate activity across multiple services on a consumer’s behalf within clear boundaries.

Many everyday consumer activities and decisions – identifying relevant offers and good deals, switching providers, understanding tariffs, managing subscriptions, resolving complaints – are time consuming and cognitively demanding. These frictions disproportionately affect households with less time, confidence or capacity to engage, contributing to poorer outcomes (especially for vulnerable consumers) and potentially reduced trust in markets.

While the potential benefits of agentic AI are significant, the technology also raises important risks, many of which build on existing evidence about AI‐enabled systems but may become more acute as autonomy increases. Managing these will be crucial to adoption at scale.

The use of algorithms and AI in pricing is already widespread and can deliver significant benefits, including faster responses to demand, lower costs, and more efficient matching of supply and demand.

However, the CMA has previously highlighted that algorithmic pricing can also increase the risk of more coordinated market outcomes, even in the absence of explicit communication between businesses, particularly where algorithms learn from and react to each other in concentrated markets.

Agentic AI could intensify these risks. Where multiple businesses deploy autonomous agents that optimise pricing or commercial strategies, there is a risk that interaction between these systems could dampen competitive pressure. We have discussed this topic and considerations for businesses elsewhere, including in our latest blog post on AI and collusion.

UK consumer protection law has long applied to businesses’ use of technology and digital design, and recent enforcement shows that it is the effects on consumer decision‐making, not the novelty of the technology, that matter most. Under the UK’s consumer protection framework – now strengthened by the Digital Markets, Competition and Consumers Act 2024 – businesses must not mislead, manipulate or exert undue pressure on consumers, regardless of whether those outcomes are driven by human decisions, algorithms, or interface design.

As consumer interactions increasingly involve AI driven and agentic systems – capable not just of presenting options but potentially of acting on a consumer’s behalf – the same consumer protection principles apply. For instance, if an AI agent steers, pressures or misleads consumers in ways that harm their economic interests this is likely to be unlawful.

Businesses exploring AI approaches including agentic AI, should ensure they comply with consumer law and competition law.

A central principle remains unchanged: businesses are responsible for how they engage with consumers, regardless of whether that is through people or AI systems. And consumer law requires you to treat your customers fairly.

One such enabler is data mobility. Agentic systems are only as effective as the information they can access, yet today consumer data remains fragmented across businesses, sectors and formats. Smart data initiatives have the potential to reduce this friction, allowing agents to act on up to date, user authorised information and to operate across providers without repeated manual intervention. From a competition perspective, portability is not simply a convenience: it is a structural condition for dynamic markets. If consumers can’t give their agents direct access to their data (including preferences, broader context) or if their agents can’t move across ecosystems, easily, there will be a risk that they experience `lock-in’ to incumbent agentic ecosystems rather than able to switch around freely, and that this undermines competition and the potential for agentic innovation to drive household prosperity and growth.

Agentic AI has the potential to reshape how consumers interact with markets, delivering meaningful benefits for households and supporting productivity, innovation and growth across the economy. By moving from tools that assist decisions to systems that can act on consumers’ behalf, agentic AI could significantly reduce friction, lower cognitive burdens, and help consumers achieve better outcomes in complex markets.