I keep hearing about AI search as if it’s become the norm for everyone—an inevitable shift in how we discover information. But in reality, it’s not so simple.
AI search is indeed on the rise, but it’s not being adopted equally. The real divide comes down to something rarely discussed: household income.
My agency started closely monitoring search behaviors back in early 2025. In our latest study, we took a closer look through the lens of household income.
The results? A significant divide emerged. While a general 27% of users claim to regularly use ChatGPT, income-specific data paints a different picture.
In essence, higher-income households are significantly more likely to use generative AI tools.
This major variation challenges the common assumption that AI adoption progresses uniformly across demographics.
We’re seeing a new layer of digital inequality in accessing information. This divide, visible across the UK, is adding to an existing digital skills gap.
AI adoption relies on more than just having the right tools. It’s also influenced by:
If you work in certain sectors like digital or corporate, you’re more likely to be encouraged to incorporate AI into your daily routines.
Capability plays a role, too. For some, using AI tools comes naturally. For others, it’s an intimidating process without proper guidance.
Then there’s confidence—trust in AI tools varies. In our research, users on platforms such as Perplexity report high levels of trust, but they remain niche.
These disparities mean that AI literacy is quickly becoming another possible layer of the digital divide, augmenting the advantage of the digitally savvy.
For businesses, this division has tangible implications. Different audiences are developing distinct behaviors:
This isn’t a minor shift. Making incorrect assumptions about user behavior could lead to strategic missteps, like over-investing in one area and neglecting another.
Yet, there’s an upside. Fast adopters of AI are often the very decision-makers and high-income consumers that brands value most.
These users are frequently termed “digital explorers” and see AI as an integral part of their decision-making process.
Behavior and confidence are intertwined, shaping how far users will go with AI.
To respond to these fragmented behaviors, brands need to:
A comprehensive understanding of AI’s role at every step of the customer journey becomes essential.
Ultimately, as AI weaves deeper into our lives, the human element remains paramount in determining the future of search.
Ads in ChatGPT signify a major transition from focusing on keyword intent to understanding user behavior. This evolution changes how we approach relevance, creativity, and performance measurement.
Currently, ads are being tested in ChatGPT in the U.S., appearing to various users across different account types. For the first time, we see advertising stepping into an AI environment designed for answering queries, which fundamentally changes the game for marketers like me.
AI has been an integral part of ad creation and planning across platforms like Google and LinkedIn for years. However, placing advertisements inside an AI that people trust to assist with thinking, decision-making, and actions is a completely new challenge. It’s not just another channel in our existing media strategy.
The primary concern for us isn’t targeting, but understanding psychology. Replicating strategies successful in search or social may lead to disappointing performance or even damage trust.
To thrive, brands must comprehend why users engage with ChatGPT, and what implications that has for capturing attention and enhancing the customer journey.
ChatGPT is a Task Environment, Not a Feed
When people use ChatGPT, they have a purpose. Whether it’s:
Solving a specific problem.
Refining a shortlist.
Planning a trip.
Writing something.
Making sense of a complex decision.
Unlike feed-based platforms, where users passively scroll and consume content, ChatGPT users are goal-oriented.
In such a task-centered environment, behavior shifts:
Goal shielding: Users focus narrowly on finishing tasks, filtering out distractions that don’t contribute.
Interruption aversion: When focusing, unexpected distractions feel more annoying.
Tunnel focus: Clarity and speed take priority over exploration.
This means gaining clicks will be more challenging than some advertisers might anticipate. If ads don’t assist users in progressing their tasks, they’ll seem irrelevant, no matter how topically aligned they might be.
Considering trust in AI is still being established, tolerance for distracting ads is particularly low.
Behavior Over Search Volume: Designing a Strategy for ChatGPT
Traditionally, search volume has directed our planning.
Keywords informed us about what users sought, how often, and the level of demand competition. This framework informed both SEO and paid media strategies.
However, ChatGPT changes this model. Instead of searching for keywords, users describe situations, ask detailed questions, and pursue outcomes beyond mere information.
Without query data to optimize, our success depends on understanding:
The task the user aims to complete.
The journey stages they’re outsourcing to AI.
The specific help they need at that moment.
This is where behavioral insights replace keyword demand as the foundational strategy.
Transitioning from Keyword Intent to Behavioral Targeting
Instead of centering our plans around queries, we should focus on behavior modes, representing the mindset of users when they turn to ChatGPT.
We can consider these modes as follows:
Explore mode: Users seek inspiration or shape a perspective.
Ads here should ignite ideas, offer options, or reframe the problem.
Reduce mode: Users aim to narrow choices effectively.
Ads should clarify differences, simplifying decisions.
Confirm mode: When users want reassurance, trust trials such as reviews or guarantees matter most.
Act mode: Users aim to complete the task, so ads that eliminate friction, like clear pricing, will succeed.
These modes correspond with recognized human drivers in search behavior: forming perspectives, informing, reassuring, and simplifying. ChatGPT condenses these moments into one interface.
The key shift is that relevance in ChatGPT is not merely about a match but about functionality.
An ad can align with a category but still fall short if it doesn’t help users with their tasks. Anything creating extra work or that distracts from goals feels frustrating in a task environment.
High-performing ads are likely to act less like traditional ads, and more like:
Tools.
Templates.
Guides.
Checklists.
Shortcuts.
Decision aids.
Such ads integrate seamlessly into user workflows.
Generic brand ads, mere awareness messages, and content serving as detours are likely to underperform.
The assets that create compelling ChatGPT ads—guides, frameworks, and reassurance-focused content—do more than boost paid performance. They enhance authority for SEO, earn media coverage for digital PR, and strengthen brand trust across social and owned channels.
Here, silos can break performance.
Paid media teams cannot create “helpful ads” in isolation while SEO focuses on authority, PR works on trust signals, and brand teams shape voice independently. AI-driven discovery blends these signals.
The best-performing ads may rely on:
Brand voice for consistency.
Trusted voice from reviews, experts, or validation.
Amplified voice through media coverage and authority.
The line between advertising, content, and credibility is increasingly blurred.
Rethinking Measurement
Evaluating ChatGPT ads purely on click-through rates risks missing their broader influence. These ads might sway decisions without triggering immediate clicks, aiding in brand recall or re-entry through different channels.
More significant indicators might include:
Shortlist inclusions.
Brand recall.
Assisted conversions.
Branded search increases.
Direct traffic improvements.
Conversion boosts further down the line.
This underscores the need for cross-department collaboration. If performance spans the customer journey, so too must measurement and accountability.
This is not just a new ad format; it’s a shift in behavior. Brands that succeed will deeply understand:
What people use ChatGPT for.
Journey stages being shifted to AI.
How to support these moments without losing trust.
We should revisit jobs-to-be-done thinking, mapping actions leading up to a purchase, inquiry, or commitment, and identify where AI reduces effort, uncertainty, or complexity.
This approach empowers us to ask, not simply, “how do we advertise here?” but “how can we be genuinely helpful when it counts most?”
Adopting this mindset will not only shape performance in ChatGPT but influence the broader future of AI-led discovery, where understanding behavioral intent will surpass the old focus on keywords.
When I came across Google Search Advocate John Mueller’s response to a Reddit user’s query about SEO’s relevancy in the age of AI, I found it incredibly enlightening. The question was whether traditional SEO is still sufficient or if there’s a need to pivot towards generative engine optimization (GEO).
His advice was strikingly straightforward: the labels we use are less significant than the reality we face.
“If you have an online business that thrives on referred traffic, it’s essential to see the bigger picture and prioritize your strategies accordingly. The name you give it isn’t critical, but AI isn’t disappearing anytime soon,” Mueller emphasized.
While Mueller didn’t delve into whether GEO will become its own field, he made it clear that AI’s presence is a constant we need to accept.
Google remains skeptical about treating AI optimization as separate from traditional SEO, as seen in several instances:
I realized that it’s crucial to ignore the surrounding buzz and focus on how our audience truly behaves. Mueller’s recommendation was to examine practical data, like:
How many of our audience members are using AI tools?
How does AI usage compare to search engines, social platforms, or other traffic sources?
What implications does this have for allocating our time and resources?
The takeaway for me is that while SEO continues to be a significant traffic and revenue driver, it doesn’t guarantee AI visibility. We need to remember that not all SEO practices align with GEO.
To quote Mueller from his Reddit comment:
“If you have an online business that makes money from referred traffic, it’s definitely a good idea to consider the full picture, and prioritize accordingly. What you call it doesn’t matter, but ‘AI’ is not going away, but thinking about how your site’s value works in a world where ‘AI’ is available is worth the time. Also, be realistic and look at actual usage metrics and understand your audience (what % is using ‘AI’? what % is using Facebook? what does it mean for where you spend your time?).”
If you’re interested, you can check out the complete Reddit discussion here.
