In the not-so-distant future, the majority of customer-brand interactions may not involve customers at all – at least not directly. Instead, software agents acting on behalf of individuals will search, compare, decide and transact across the digital economy. The implications for business are profound, if underappreciated.

Rather than a chatbot or a smart speaker with a pleasant voice, the AI personal assistant of the near future is likely to be an autonomous agent with memory, preferences, goals, and an expanding capacity for judgement. It will be more capable than a search engine, more loyal than an app, and more demanding than either.

For consumers, the appeal is obvious: no more navigating sluggish websites or installing yet another app to buy pet food. For brands, the reality is more complex. They will need to adapt their content, systems, and interfaces to a new kind of customer – one that does not browse, but interrogates.

Intermediaries with Initiative

The notion of “AI agents” is no longer theoretical. Several large firms have begun deploying them internally. Walmart recently introduced “Sparky”, an AI system capable of understanding natural-language queries and surfacing relevant products in its app. Visa is reportedly exploring payment protocols designed specifically for autonomous agents that initiate transactions on behalf of individuals. Amazon and Salesforce are experimenting with agent-based routing of customer support requests, often without the customer ever speaking to a human.

The agents in question are not merely automated scripts. They combine large language models with memory and goal-orientation. Their capacity for inference is improving quickly, and so is their ability to coordinate multiple steps – searching for a product, evaluating options, comparing prices, reading reviews, and placing an order – all without human supervision.

This raises a pressing question: if a brand’s primary customer becomes a machine, how should the brand respond?

Making Brands Legible to Machines

The first imperative is structural clarity. A conventional website, designed for human attention, may suffice for casual visitors. It will not serve a machine tasked with decision-making. The agent requires access to structured product data, clear categorisation, and predictable endpoints. In short: it requires everything modern websites have tended to obscure in the name of aesthetics or marketing.

Firms should assume their content will be read – and judged – by machines. This is not unprecedented. Google, after all, has been doing something similar for years. But generative agents demand more precision: content must be queriable, transactional, and reliable. Sites that depend on JavaScript-heavy interactions, dynamic content loading, or hidden APIs will struggle to be understood.

From Interface to Infrastructure

If content must be structured, the systems behind it must be open – though not necessarily public. Application programming interfaces (APIs), long considered a developer concern, will become a brand’s primary sales surface. Agents will favour those services that respond cleanly and quickly to their requests. Inventory availability, delivery timelines, returns policies and payment methods must all be machine-accessible.

This is, in some sense, a reversal of the past decade’s trend. Whereas businesses once sought to control every aspect of the customer experience – from homepage to payment gateway – they must now cater to autonomous agents that cut straight to the answer. Control gives way to interoperability.

Identity, Trust, and the Machine Consumer

The agent, like the customer it represents, must be known. That means firms must invest in identity resolution: the ability to associate users with preferences, histories, and permissions across systems. Fragmented CRMs and siloed data sources will undermine this effort.

The more agents act independently, the more trust becomes an engineering challenge. Agents will need to understand provenance: where information comes from, and how reliable it is. Brands, in turn, must develop mechanisms for explainability – not just to reassure the user, but to inform the agent. A product recommended without justification will likely be ignored, even if it is suitable.

Does Design Still Matter?

The implications for user experience (UX) design are not trivial. The rise of agent-mediated interaction may diminish the importance of visual design altogether. If most customers no longer see your homepage, does it matter how it looks?

In this new model, the brand’s “experience” is mediated through its APIs, data models, and transaction logic. “Brand voice” may become literal – defined not by copywriters, but by how agents interpret the firm’s structured metadata. But core content like text, images and videos will be more important than ever, as they will be presented to the customer by AI agents.

Not Just a Technical Shift

It is tempting to treat this as a purely technical transformation. It is not. If autonomous agents are to act as proxies for real people, then questions of consent, transparency, and governance follow. What happens when an agent misrepresents a user’s intentions? Who is liable when it transacts improperly? These are problems not of UX, but of political economy.

Still, the near-term questions are more operational:

• Can your systems speak clearly to AI intermediaries?
• Is your data structured, accessible, and current?
• Are your core content assets optimised for AI?
• Are your APIs documented, consistent, and monitored?
• Do your recommendations make sense – when evaluated by logic, not emotion?

The brands that answer these questions well will not merely retain visibility. They will become the default choices for agents tasked with finding “the best option.”

Whether those agents are human or artificial may soon be beside the point.