The acquisition of AI search is divided by revenue lines

Everyone talks about AI search as if it’s already universal – as if collectively we’ve moved forward, users have changed and discovery has changed for everyone. But the truth is not straightforward at all.

While AI search is growing rapidly, it is not being equally embraced. The gap is increasingly created by something we don’t often discuss in search: household income.

My agency has been tracking how people search since the beginning of 2025. Looking at household income, we found a clear and significant difference. Overall, about 27% of people say they use ChatGPT regularly. But when you break that down by income, the picture changes dramatically.

• Households £25-30k: ~ 18% consumption
• £50-60k households: ~30% of consumption (UK median household income in this bracket based on financial year ending 2024)
• Households £70-80k: ~49%
• £100k+ households: ~48–58%

In other words, households with higher incomes are twice as likely to use productive AI tools. This is not a small difference. It challenges one of the biggest assumptions that shape search strategy: that AI adoption happens at the same pace for everyone.

We are witnessing the emergence of a new type of digital inequality in the way people access information and make decisions. This separation does not exist separately.

Across the UK, FutureDotNow found 52% of working-age adults are able to complete all the essential digital tasks required at work. The adoption of AI is placed on top of a digital skills gap that is already shaping who can confidently access, explore and act on information.

As author William Gibson said, “The future is here – it’s not evenly distributed.”

AI adoption is not just about access to tools. It is made up of human behavior, especially:

• Access.
• Power.
• Confidence.

Access: Who is exposed to AI in their daily lives?

If you work in a digital, business or knowledge-based role, chances are you will be encouraged or expected to use AI. It becomes part of your workflow. This is reflected in our data, where sectors such as IT and business consistently lead in acquisitions, reinforcing how exposure to work accelerates behavior.

If you are not, your exposure may be limited to news articles, media narratives, or informal experiences. That creates a very different starting point.

Skill: Do you know how to use it?

For those who use AI regularly, awareness becomes second nature. You learn to refine, challenge and build on output. For some, that first contact can feel strange, even intimidating. Without guidance, many don’t get started.

Trust: Do you trust it enough to rely on it?

This is where things get really interesting. Trust varies not only by platform, but also by concept. In our research, platforms like Perplexity score high on reliability, but they are still niche.

Which raises an important question: Are the early adopters of these tools the most confident in navigating and validating AI results?

It is possible. It reinforces a larger point: AI adoption isn’t just a technology curve, it’s a human one.

With AI embedded in the way people search and decide, AI literacy risks becoming the next layer of the digital divide, increasing the profits of those who are already digitally confident.

Search is fragmenting, and that has real business implications

Different audiences create different behaviors:

• Early adopters of AI → Assigning tasks, summarizing, shortlisting.
• AI-assisted users → Validate across platforms.
• Users avoiding AI → Trusting Google, vendors and communities.

This behavior is not fixed. The same person might use AI to write a formal letter, but still turn to Google when doing product research.

Habits take time to build, and right now, people are trying. This means that we don’t just switch from one search journey to another; rather, we see discovery breaking down into several different ways.

This separation is not just a change in behavior. It has direct commercial consequences. If you assume that your audience behaves like early adopters, you risk making the wrong strategy calls.

Over-investing in AI development can mean a lack of traditional users, while over-targeting Google can mean a loss of AI-led users. Ignoring confidence gaps can also destroy trust.

Opportunity: Your most important audience may already be AI-first

There is real upside to this division. The audience that uses AI most quickly is often informed by multiple brands: decision makers, professionals and high-income consumers.

Our data shows that these users generally correspond to what we define as “digital explorers,” early adopters who have already submitted decision-making components to AI by comparing options, summarizing information and shortlisting before visiting a website.

Behavior is only one layer. Underneath it lies confidence, which determines how far users are willing to go with AI.

When you count behavior through this lens, three clear patterns emerge:

• Users with high confidence → Can’t surrender to AI.
• Users with moderate confidence → Likely to explore platforms across the board.
• Users with low confidence → Trust in familiar places.

Different behaviors, journeys, expectations and content needs matter.

How to respond to a segmented search

Because these high-value, AI-first users are sending decisions earlier, the goal will now be understood, revealed and recommended by AI tools – before a click even happens.

1. Part with behavior, not just demographics

Age or income may define who your audience is, but not how they decide. To get this right, you need to go beyond high-level classification and build an understanding of acquisition behavior, including both quantitative and qualitative understanding.

Quantitative data shows you patterns on a scale:

• What platforms are used.
• How often.
• What are the audience groups.

Reasonable understanding explains why:

• What people trust.
• Where they feel confident.
• What causes them to switch between platforms.

People are not loyal to one search method. They adjust their behavior to match the work they are doing.

Someone might turn to AI to narrow down options, use Google to confirm specifics and go to TikTok or Reddit for real-world context, all in the same trip.

Your segment needs to be mapped in the customer journey, including where AI plays a role, where people want confirmation and where they need human proof, as the same person can be AI-first at the beginning of the journey and avoid AI when the decision is made.

If you don’t understand those shifts, you risk designing a strategy that only works for part of the journey. This is where brands lose their value.

2. Travel design for multiple acquisitions

Once you understand how your audience behaves, the next step is to design a strategy that reflects that.

In our research, 51% of users say they turn to social media to find information in their preferred format, such as photos and videos, while 40% of information comes from real people. That tells us how people want to get information: through visual, digestible formats, through human input and real-world context.

AI is a response tool, while social is always a place of human context. Platforms like TikTok and Instagram are important parts of the search journey, especially in the early stages of exploration. At the same time, AI is used to summarize and simplify, while traditional search engines are still relied on for verification and information.

It is important to appear at the right times, with the right content, in the right format and in the right voice.

3. Prepare for clarity

Users are now more specific, conversational and sophisticated in what they search for, especially in the areas of AI.

That’s why your content needs to be organized in a way that answers real, nuanced questions, information from people and machines that can interpret. If your content is unclear, it may not be displayed at all.

4. Build trust and efficiency

AI does not replace the need for validation, because even when people use it to quickly narrow down options, they still look for signals that help them feel confident about a decision, including reviews, authority, real-world verification and brand credibility.

We are already seeing this reflected in the review summaries and recommendations generated by AI. Good performance may get you shortlisted. Trust is what you choose.

The future of search is human

AI will evolve and platforms will change, but the defining factor isn’t the technology — it’s how people use it.

The future of search will be defined by human behavior. To win, don’t just prepare platforms — understand the people behind them: how they think, search and decide.