As we see the changes in our own behaviour around how we search for information, business owners are correctly starting to question whether they should still use channels like Google ads now that people’s attention is shifting elsewhere.
I think that misses what is actually happening. An important observation we have made is that search volumes on Google are not dropping. So if people are still searching for solutions there then it is still a relevant channel. But the fact remains that most of us spend as much time or even more time using AI engines to find information.
So what is going on? We have a theory.
In B2B services, buyers are not simply replacing Google with tools like ChatGPT, Perplexity, or Gemini. They are using AI to speed up research, shape requirements, and build shortlists, then using Google to validate what they have found, compare vendors, and sense-check credibility. The current evidence points much more strongly to combined behavior than outright substitution: Google and National Research Group’s 2025 B2B buyer journey study found that 60% of B2B buyers used AI tools during the purchase process, yet 94% of online-searching buyers still used Google Search, and among AI users, 63% used Google to validate or cross-check AI outputs.
That matters because it helps explain why so many companies feel that Google Ads is becoming less central while search volumes do not seem to be collapsing. My theory is that AI is changing where discovery happens first, not eliminating Google’s role in the buying journey. The result is a shift in the shape of search behavior rather than a simple drop in search demand.
The new buying journey
For B2B buyers, AI is a very efficient first pass. It can summarise options, explain trade-offs, suggest vendors, and help a buyer clarify what to ask before speaking to sales. That is exactly the kind of work that used to require a string of broad Google searches and many tab opens.
But that shortcut does not remove the need for validation. In the same Google/NRG research, buyers reported using Google Search, vendor websites, and analyst reports to verify AI-generated information, which suggests that AI accelerates research but does not replace trust-building. Forrester’s analysis reaches a similar conclusion: AI-powered search is shifting discovery and consideration toward contextual answers, but authority, proof, and post-click experience matter more, not less, as buyers move toward a decision.
So the new journey often looks something like this:
- Ask AI to understand the category.
- Use AI to generate a shortlist.
- Search Google for brand names, reviews, comparisons, pricing, and proof.
- Visit websites and third-party sources to validate the shortlist.
- Contact the suppliers that feel credible.
That is not a dead Google. It is a Google that has become more important as a validation layer.
Why Google Ads still appears resilient
This also explains why Google Ads may still hold up better than many expected. If AI absorbs more of the broad, exploratory research phase, then Google can still retain a large share of high-intent, evaluation-stage searches. Buyers may do fewer generic “what is X” style searches, but still search heavily for vendor names, competitor comparisons, service-specific terms, and trust signals when they are getting closer to action.
At the same time, the click environment has clearly become harder. Seer Interactive found that by September 2025, organic CTR on queries with AI Overviews had fallen 61%, while paid CTR on those same queries had fallen 68%; even queries without AI Overviews saw meaningful CTR declines. That means stable demand does not necessarily produce stable traffic. Businesses can still be present in search behavior while receiving fewer clicks and weaker attribution.
This is why many companies feel the market is changing before they can prove it cleanly in analytics. The demand may still be there, but it is being filtered differently.
The signal I would watch: branded vs non-branded search
If this theory is right, the most useful signal to watch is not total search volume alone. It is the relationship between branded and non-branded search.
The logic is simple. If AI tools are increasingly doing the early, generic discovery work, then buyers may arrive in Google later in the process with more specific vendor names already in mind. In that scenario, generic research queries may weaken or flatten while branded and navigational searches remain stable or grow. Google’s rollout of a native branded queries filter in Search Console makes this much easier to monitor because it now separates branded and non-branded traffic without relying on manual regex workarounds.
That matters strategically. A business that sees rising branded search alongside weakening non-branded informational traffic may not be losing demand at all. It may simply be seeing discovery happen elsewhere before Google is used for validation. In other words, AI may be pushing search behavior downstream toward brand confirmation rather than eliminating it.
How small businesses should decide what strategy is right for them
This is the part that matters most in practice.
A small business should not respond to AI search hype by cutting Google Ads across the board or by blindly investing in “AI SEO.” The right strategy depends on what the underlying data says about how buyers are currently finding and validating the business. Google’s branded queries filter in Search Console is especially useful here because it helps separate brand demand from discovery demand and gives a much clearer picture of what part of search is actually working.
The first set of indicators to look at is:
- Branded impressions and clicks in Search Console.
- Non-branded impressions and clicks in Search Console.
- CTR trends by query type, especially broad informational terms versus commercial and branded terms.
- Search term mix in Google Ads, particularly brand, competitor, and high-intent service queries.
- Direct traffic and assisted conversion patterns, which can capture journeys that begin in AI or other low-attribution channels before coming back through search.
- The frequency with which prospects mention ChatGPT, Perplexity, Gemini, referrals, or “I’d heard of you already” during lead intake, because analytics alone will miss some of this upstream behavior.
The important thing is not just to collect the numbers, but to read them in combination.
If branded search is rising while non-branded search is flattening or weakening, that is usually a sign that awareness and validation demand are healthy, even if traditional top-of-funnel traffic is softening. In that case, the right move is usually to protect branded demand, improve conversion assets, and invest in the kinds of proof that help buyers validate a shortlist quickly, such as case studies, testimonials, comparison pages, and strong service pages.
If non-branded visibility is still strong but CTR is falling sharply, especially on informational queries, that is a signal that AI Overviews or answer engines are intercepting more of the early-stage click path. In that case, the business should be careful about over-investing in generic content built purely for clicks and should focus more on high-intent content, bottom-funnel SEO, and brand recall.
If both branded and non-branded search are weak, the issue is probably not AI alone. It may indicate weak positioning, low awareness, limited demand in the niche, or poor differentiation. In that scenario, the answer is not simply “do more SEO” or “buy more ads.” The business may need a stronger category position, clearer messaging, or a more compelling point of view before channel performance improves.
A simple way to think about it is this:
- Rising branded, softer generic: focus on brand strength, validation content, and bottom-funnel capture.
- Stable branded, stable generic: maintain a balanced mix and improve trust assets.
- Weak branded, weak generic: fix positioning and visibility before scaling spend.
- Strong traffic, weak conversion: improve landing pages, proof, and offer clarity before buying more demand.
What this means for marketing budget
For small B2B service businesses, the implication is not to abandon Google Ads. It is to become more selective about what Google Ads is expected to do.
Paid search still makes sense where there is clear intent: brand terms, service-led commercial queries, high-conviction local searches, competitor terms, and searches where buyers are already in evaluation mode. What is under more pressure is broad, top-of-funnel query capture where AI can answer the question before a click happens.
That means budgets should usually shift toward a more balanced model:
- protect and capture high-intent search demand,
- invest in authority-building and proof-rich content,
- strengthen the assets that help buyers validate your credibility,
- and build a measurement layer that can detect whether AI is influencing discovery before Google ever enters the journey.
In practical terms, that often means fewer generic blog posts written to rank for broad informational terms, and more emphasis on case studies, comparison pages, pricing guidance, founder expertise, review generation, and structured service content. Those assets help with traditional search, AI citation, and conversion at the same time.
The bigger shift
The bigger shift here is that search visibility is no longer enough on its own.
What matters now is whether your business becomes a name that buyers encounter, remember, verify, and trust across multiple environments. AI tools may introduce the options. Google may validate them. Third-party sites may reinforce them. Your own website must then close the confidence gap.
That changes the job of marketing. It is no longer only about winning the click. It is about shaping the shortlist.
My theory in one sentence
AI search is not killing Google Ads in B2B; it is moving generic discovery upstream and making branded validation more important downstream.
That is why the smartest small businesses will not choose between AI visibility and Google search. They will build a strategy that uses both.
