You built a great website, but my agent doesn’t care!

Today, efforts are being made to enable AI agents to browse websites, mimicking human interaction. But this is an interim step, not the end goal. Agents don’t care about typefaces, hero images, or clever copywriting. They care about structured knowledge, trust signals, and transactional capability. Instead of scrolling through pages, my agent will simply retrieve relevant information and make decisions based on my preferences.

For example, I would no longer need to wade through Google search results, open multiple airline sites, and compare options to book a flight. My agent knows my seating preferences, budget, and travel history. To get the best match, it doesn’t need a website; it requires a direct interface to airline agents.

The Death of Human-Centric Marketing?

If agents become the primary interface for decision-making, traditional advertising methods such as eye-catching visuals, emotional storytelling, and brand recognition may lose their power.

My agent doesn’t care about a Super Bowl ad. It cares about trust signals, price, and service reliability. Brands today compete for human attention. In an agent-first world, they will compete for agent selection.

This introduces a new challenge: how do you persuade an AI agent to prioritise your offering over another?

Agent Marketplaces: The Future of Discovery

Google currently ranks websites for human search. It could pivot to ranking agent knowledge and transactional capability in the future. Instead of SEO (search engine optimisation) for humans, businesses might optimise for agent discoverability.

Factors like:

• Trust verification – Independent validation of claims, similar to verified reviews today.
• Transactional readiness – Businesses offering seamless API-based transactions may rank higher.
• Performance-based ranking – Agents may prioritise brands based on fulfillment rates and customer satisfaction data.

Google Reviews, for example, could evolve into structured trust signals that agents use to assess service quality, moving beyond human testimonials to verified performance metrics. Will businesses rely on centralised platforms (Google’s agent rankings) or decentralised protocols? The answer could dictate whether the agent economy is open or monopolistic.

The Rise of  Proactive Agents

Today’s AI assistants are primarily reactive and perform tasks when asked. However, agents will become proactive as AI advances, anticipating needs based on context. If my anniversary is coming up, my agent might automatically search for a getaway within my budget, knowing my wife’s preferences. It would return not just with options, but with the best-matched offer, ready for approval.

This raises deeper questions: How much autonomy should agents have? Should I allow my agent to book the trip automatically, or do I still want to approve every step? Over time, as agent performance improves, I may delegate more decision-making.

Codifying Human Emotion as Preference Points

Branding is deeply tied to human emotions—luxury brands, for example, invoke feelings of trust, status, and exclusivity. But how does an AI agent discern these intangible qualities? The challenge lies in transforming these emotional cues into actionable data for the agent.

Can we codify emotions by associating them with preference points? For instance, luxury brands may be assigned higher preference weights in categories such as trustworthiness, reliability, scarcity, opulence and status.  The agent will then learn to factor these emotional undercurrents into decision-making processes. As the agent gathers more data on your preferences, it will better understand the subtle ways you prioritise specific values, whether that’s a brand’s heritage or its sustainability practices.

Assigning preference weights to emotions may create the potential for biases, so much care must be given to how this bias can be managed.

The Agent Interface: Your Portal into a New World

The agent interface will be your primary point of interaction.

In the 1950s, Lieutenant Gilbert Daniels exposed a fatal flaw in design thinking. When the U.S. Air Force built cockpits for the “average pilot,” they discovered that no actual pilot fit the average. Daniels proved that designing for the middle meant designing for nobody—a lesson ignored by today’s web. Websites are built for the “average user.” They bury critical details in endless menus, default to one-size-fits-all layouts, and bombard you with features you’ll never use.

In contrast, your agent’s interface won’t be bound by these averages. It will dynamically present the most relevant, personalised UI for each specific task—whether you’re purchasing, researching a topic, or planning a trip. Instead of navigating static websites, you’ll engage with a fluid, adaptive agent designed around you.

This shift begs the question: Where will your agent interface come from? Certain ecosystem players are already well-positioned due to the “real estate” they own. Google and Apple dominate mobile with Gemini and Siri. Microsoft controls the workplace through Windows and Copilot. Amazon owns the home with Alexa. Meta has embedded its agent into WhatsApp, and X is tying users into its ecosystem with Grok. Each of these companies wants to be your agent, because owning that interface means controlling your interactions—and, by extension, your data and transactions.

But what if you don’t want to be locked into a single ecosystem? If your agent is truly your primary interface, it could also serve your social media feeds, messages, and interactions—without the need for apps like WhatsApp or X. This creates a power struggle: Do platforms become mere data sources that your agent pulls from? If so, how do they monetise attention when you no longer interact with their native UIs? Would they try to block agent access or force users back into their apps?

If users interact with multiple front-end agents (on mobile, desktop, or home devices), will they have to “train” each one separately? Or is there a model where agent backends are interoperable—a single agent “brain” that stores preferences, payment integrations, and history, while allowing users to switch between front-end interfaces?

Suppose my agent dynamically serves me the best interface for every task, tailored to my needs and preferences. Why would I ever visit websites or engage with platforms designed for the average user? And if my agent, not the platforms, curates my experience, how will businesses compete for attention in a world where AI, not humans, drives discovery, decision-making, and transactions?

What Enterprises Need to Do to Prepare

As AI agents take over search, discovery, and transactions, businesses must rethink their operations. The shift isn’t just about making information accessible—it’s about adapting business models to an agent-first world.

• New Business Models for the Agent Era – How will businesses monetise if AI agents drive discovery and transactions? Will ad-driven models collapse? Will success depend on direct partnerships with AI providers, subscription-based access, or performance-based agent incentives?
• Enterprise Knowledge & Taxonomy – Is your information structured for agent consumption, or is it locked in human-centric formats that AI struggles to interpret?
• Tacit Knowledge Capture – Agents need institutional expertise, not just documented FAQs. How will businesses surface critical, unwritten knowledge?
• APIs & Infrastructure – Are you ready for agent-to-agent transactions, or is your business still built around human web navigation?
• Knowledge Freshness – Who ensures product, pricing, and service details are up to date so agents make decisions based on accurate data?
• Strategic Timing – How fast will this shift happen? Will your business adapt early, or struggle as AI agents bypass outdated models?

Most businesses are unprepared, and legacy systems will struggle. You better get started.

Conclusion:

Businesses today invest heavily in human-centric experiences, but much of this effort becomes meaningless in an agent-first world.

Much like how R2D2 seamlessly plugged into systems to retrieve data and perform tasks, my agent will plug into an ecosystem of knowledge and transactions. There will be no need for traditional visual branding elements or user interfaces; the agent UI will serve as the bridge to the agent’s interactions with the world. This represents a new paradigm where knowledge retrieval and decision-making are done on your behalf, and the agent's interface adapts to provide only the most relevant data.

So, the Internet Is Changing and My Agent Doesn’t Care

• Spent weeks designing that beautiful UI component? → My agent doesn’t care. It just wants structured data.
• Crafted the perfect landing page copy to persuade customers? → My agent doesn’t care. It processes facts, not emotion-driven messaging.
• Optimised the above-the-fold experience with a stunning hero image? → My agent doesn’t care. It doesn’t “see” websites the way humans do.
• Designed an award-winning brand color scheme to build recognition? → My agent doesn’t care. Trust signals matter more than aesthetics.
• Spent millions on Super Bowl ads to increase awareness? → My agent doesn’t care. It evaluates products based on reviews, performance, and price—not emotional storytelling.
• Implemented lazy loading, parallax scrolling, and micro-interactions for a slicker experience? → My agent doesn’t care. It fetches data instantly and moves on.
• Created a multi-step lead capture form to collect user details? → My agent doesn’t care. It wants seamless, API-based transactions, not friction.

We are entering a world where AI agents, not humans, drive digital interactions. The companies that recognise this shift and optimise for agent-first engagement—not just human persuasion—will define the next era of commerce. The question isn’t whether AI should browse websites; it’s whether websites will even matter in an agent-driven world.

Because at the end of the day, my agent doesn’t care—it just gets the job done.

Will your business power the agent economy or get left behind?