I have spent 25 years running marketing campaigns and have managed and audited hundreds of advertising accounts. Recently, I have been seeing a concerning combination: higher search costs, less precise targeting and more complexity between what an advertiser selects and what Google actually delivers.

For an experienced operator, that means more investigation and tighter oversight. For a solopreneur or small marketing team, it can mean spending thousands of dollars before understanding what went wrong.

Google Ads can still produce valuable customers. I continue to use it because it works when targeting, measurement, landing pages and the sales process align. But the supervision required is increasing just as more businesses are trusting AI to manage it.

Google’s growth does not guarantee advertiser profitability

Alphabet’s October 28, 2026 earnings release reported quarterly revenue of $127.6 billion, up 25%. Google Search and other revenue increased 12%, and the company said year-over-year Search query growth was its highest in five years. Those figures challenge the argument that overall Google Search volume is collapsing. publicnow.com

They do not tell an advertiser whether the next dollar spent will produce a profitable customer.

Google can grow advertising revenue while an individual business pays more to acquire a client. Search volume, platform revenue and advertiser profitability are separate measures.

Before increasing a budget, I want to know whether we are buying the right traffic, whether it converts and whether those conversions become paying customers.

What I am seeing inside accounts

In a recent campaign audit, I found Google serving one ad approximately twice as often as another, even though its reported cost per conversion was roughly twice as high.

More exposure was going toward the more expensive outcome.

I do not remember encountering this pattern as frequently in earlier years. That is my observation from working inside accounts, rather than evidence that every campaign behaves this way.

There can be explanations. Google uses auction-level predictions to determine which ads to serve. Conversion delays, differences in traffic and lead quality can also make historical averages misleading. Google documents that its system favors ads it expects to perform better in a particular auction. Google Ads Help

But a description of how automation works does not establish that its decisions benefit the advertiser.

Someone still needs to examine the ads, search terms, landing pages and actual customer outcomes. Accepting the allocation because the campaign is “optimized” is not sufficient.

Settings determine what you actually buy

When I audit an account, I compare what the marketer intended to buy with what the account actually delivered.

The keyword is only one part of that relationship. Location settings, networks, bidding, conversion goals, schedules, landing pages and automated features all influence the result.

Exact match, for example, now works through meaning and intent rather than strictly matching the advertiser’s wording. Google’s close-variant definitions include synonyms, paraphrases and other variations. Advertisers need to examine actual search terms instead of assuming their keyword list fully defines the traffic they purchase. support.google.com

This is where many small businesses struggle. Each setting may appear reasonable on its own. Combined, those settings can produce a campaign that spends reliably while generating weak commercial results.

The business owner sees leads in a dashboard. The sales team sees people outside the service area, prospects who cannot buy or inquiries for services the business does not provide.

Unless those outcomes reach the reporting system, the account can appear healthier than it is.

AI is changing how campaigns are managed

More advertisers are using AI to write ads, select keywords, audit accounts and recommend changes.

That can save time. It can also make a weak strategy look organized and convincing.

An AI audit might recommend expanding reach without understanding the business’s margins or capacity. It might suggest changing bidding before checking whether conversions are accurate. It might judge performance using form submissions when the business needs qualified appointments and paying customers.

Once implemented, those recommendations change the instructions and signals Google receives. Different keywords, budgets, conversion goals and landing pages can change campaign delivery.

That does not prove Google recognizes AI-managed accounts and treats them differently. The practical concern is that AI-generated changes can alter performance in ways the person approving them does not understand.

I use AI to accelerate analysis. I still verify the evidence, understand the business and take responsibility for the decision.

AI search is becoming an advertising market

Customers now have more places to research purchases.

Someone can ask an AI assistant to compare services, explain costs and narrow a shortlist before visiting a traditional search results page.

Advertising is following that activity. OpenAI reported in August 2026 that ChatGPT Ads had reached a $1 billion annualized revenue run rate. That is a company-reported run rate rather than a full year of recognized revenue, but it demonstrates that conversational AI is becoming a commercial advertising channel. OpenAI

It does not establish how much spending shifted directly from Google. It does show that advertisers have another place to compete for attention.

Google must remain relevant where customers research and make decisions while adapting its own search experience to AI. Advertisers need to understand that change and test where qualified demand is moving.

The traditional search campaign can remain valuable without being the entire acquisition strategy.

Good SEO matters in AI search

I am also seeing why strong SEO remains important as AI changes discovery.

Clear service pages, useful explanations, original expertise and credible evidence help people and search systems understand a business.

Google explicitly states that established SEO practices remain relevant to AI Overviews and AI Mode. Pages must be indexed and eligible for search snippets to qualify as supporting links. There is no special AI markup that guarantees inclusion. developers.google.com

A business should clearly explain what it does, who it serves, how its service works, what supports its claims and what a prospective customer should do next.

Publishing more generic content is unlikely to solve a positioning problem. Specific experience, useful answers and documented results give customers something meaningful to evaluate.

Good SEO does not guarantee an AI recommendation. Organic visibility in an AI answer is also different from a paid placement. Both deserve attention because both can influence how customers discover and choose a provider.

What advertisers should do now

Start by examining the existing account before adding more spend.

Review the ads receiving the most exposure. Examine the searches consuming the budget. Verify conversion tracking and compare landing-page performance. Connect inquiries to qualified conversations, appointments, sales and collected revenue.

Use AI to support the analysis, with an experienced person checking its recommendations before implementation.

At the same time, improve website performance, clarify service content and publish useful evidence of expertise. Track AI referrals where identifiable and ask customers how they discovered the business. Test emerging advertising channels with defined budgets and acquisition targets.

After 25 years, my standard remains the same: advertising must produce business outcomes that justify its cost.

The difference today is how much judgment it takes to decide where to spend, what to measure and which automated decisions need closer scrutiny.

Chris Fisher CMO/CRO z2llc.co