Amaliia Isagulova 1/15/26
Over the past two years, Google has been rebuilding Search around generative AI. AI Overviews scaled across markets, and in May 2025, Google began rolling out AI Mode in the U.S. as a more conversational Search experience that supports follow-up questions. Google also started expanding ads into AI Overviews (including desktop) and bringing them into AI Mode, signaling that monetization will follow users into these new interfaces rather than forcing them back into “10 blue links.”
That said, the useful question for advertisers is no longer “how AI changes search marketing”. That part is obvious. The more actionable question is: what patterns are already visible inside ad accounts, and what do they imply about performance when an AI-driven setup becomes the default? The short answer: Google Ads is being redesigned around an AI-driven setup. Your advantage will come less from hand-tuned mechanics like bids and keyword sculpting. It will come more from the quality of your inputs: measurement, creative, audience signals, and landing-page content.
What’s changing inside Google Ads
Historically, PPC specialists “moved the levers”: segmenting tightly, controlling match types, tuning bids, and iterating through search terms to find a profitable balance. Google is steadily de-emphasizing that operating model in favor of AI-assisted campaign management and cross-surface delivery. In its own 2025 recap, Google frames Performance Max as its most automated approach to reaching users across behaviors and surfaces.
A clear signal is AI Max for Search campaigns: a one-click suite intended to expand reach into new queries and adapt creative using Google AI, explicitly positioned as preparation for “ever-evolving Search experiences.”
This is not unique to Google. Microsoft has also been rolling out advertising experiences built for Copilot-led interactions, including ad formats “designed with Copilot in mind.” The market direction is consistent: search interfaces become more conversational, and ad platforms become more automated to match that behavior.
AI becomes the default layer
Many advertisers still talk about “turning on AI features,” as if AI sits on top of the platform. Google’s documentation and product releases suggest the opposite: AI increasingly sits inside the auction and the delivery logic.
Consider how Google describes auction mechanics. Ad Rank is recalculated for each search and incorporates not only the bid, but also “auction-time quality” signals, such as expected CTR (Click-Through Rate), ad relevance, and landing page experience. With Smart Bidding, Google emphasizes “true auction-time bid optimization,” adjusting bids for each auction based on context. In practical terms, the “engine” is no longer something you operate from the outside. Your job shifts toward supplying the system with consistent goals, clean measurements, and credible signals.
Why You Cannot Ignore the Shift (Even If You Don’t Like It)
The reason this matters now is speed. When platforms redesign the auction and UI around automation, legacy approaches don’t fail dramatically on day one. Contrarywise, they fail gradually, then suddenly. Two forces accelerate at that moment:
- New Search surfaces change click behavior. Multiple independent datasets show AI Overviews taking meaningful SERP (Search Engine Results Page, the page displayed by search engines, like Google or Bing) real estate and correlating with CTR declines. Conductor’s large-scale tracking found AI Overviews appearing on a meaningful share of keywords (with variation over time). Seer Interactive’s CTR research also shows notable click-through shifts where AI Overviews appear.
- Automation changes what winning looks like in the auction. If your conversion tracking is weak, your landing pages are thin, or your creative inputs are generic, the machine has less to learn from. So you pay for exploration without earning the compounding benefits.
This is why keeping the old setup, because it used to wor,k becomes financially risky: spending can continue, while efficiency erodes.
Landing Pages Are No Longer Secondary
A major account-level trend is the renewed importance of landing page quality. Google explicitly includes landing page experience in auction-time quality and Ad Rank components.
More importantly, automated campaign types increasingly route traffic to the most relevant page, not the page you personally selected. In Performance Max, Final URL expansion can replace your chosen final URL with another page on your domain based on user intent.
This has a direct implication for the “one-page funnel” era. Many one-page landing sites were built to convert, not to communicate depth, topical authority, or breadth. As AI-driven matching relies more on understanding intent and relevance, thin landing environments become a constraint. Businesses will either invest in content-rich, crawlable, well-structured websites, or the market will produce new single-page approaches that are still indexable and structured—delivering depth without sacrificing conversion focus.
In 2025–2026, landing pages stop being where the click lands and become part of what the system uses to decide whether your ad deserves to win.
Bids Are Becoming a Smaller Part of the Story, Though the Auction Still Exists
Bidding doesn’t disappear; it shifts from a human skill to a model outcome. Google’s own materials increasingly position Smart Bidding as the default companion to broader reach. For broad match, Google explicitly says it is “critical” to use Smart Bidding because every query is different and bids should reflect auction-time signals.
So the practical trend is:
- Manual bid control matters less than measurement quality and goal-setting.
- Advertisers experience the auction as “less predictable” because the system optimizes at the user/query/context levels, not the keyword level they can see and manipulate.
This is one of the core psychological shifts: advertisers move from controlling price per click to controlling what the system learns.
Search Advertising Is Moving Toward Intent and Audiences
As Search becomes more conversational (AI Mode explicitly supports follow-up questions and deeper exploration), the input that matters is less the literal phrase and more the underlying intent.
That aligns with changes inside Google Ads:
- Broad match + Smart Bidding is positioned as a best practice because targeting and bidding decisions happen at auction time using multiple signals.
- Audience constructs are being operationalized more aggressively. Google Ads guidance describes audience segments as a way to reach people based on who they are, what they’re researching, and how they’ve interacted with you.
- In Performance Max, audience signals are explicitly framed as suggestions that guide machine learning, while the system can still go beyond them if it predicts conversion likelihood.
In other words, keywords increasingly function as hints and constraints, while the platform’s main optimization loop shifts toward user intent classification, audience modeling, and predicted value.
Where This Is Heading: Less Transparency, More Dependence on Strategy
The direction is clear. Google will continue reducing manual controls while expanding AI-led delivery across Search experiences (including AI Mode and AI Overviews).
As automation expands, transparency becomes a governance issue. Performance Max has already attracted regulatory scrutiny in at least one jurisdiction, reflecting broader concerns around how power and data concentrate inside automated ad products.
For advertisers, this means performance becomes more dependent on strategic discipline:
- strong conversion hygiene and value measurement,
- first-party data readiness,
- differentiated creative assets,
- a site that communicates relevance and credibility,
- and experimentation frameworks (incrementality tests, geo tests, controlled holdouts) to validate what the “black box” claims.
You cannot responsibly promise a single outcome for everyone, because AI-driven systems amplify both good inputs and bad inputs. What can be said with confidence is as follows. If you remain stuck in legacy setup habits, performance pressure tends to increase: costs rise, lead quality becomes inconsistent, and reporting feels less actionable, especially as SERP real estate shifts and CTR patterns change under AI Overviews and new interfaces. If you adapt early, the upside is real: better stability at scale, faster learning cycles, and the ability to compete in a new query space that manual keyword approaches often miss.
The dividing line is not “AI vs. non-AI.” It is account maturity: measurement, site quality, creative depth, and clarity of business strategy.
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Amaliia Isagulova is a Search Engine Marketing Specialist at WGG Advertising Agency, working with Google Ads and Yandex Direct. Operating between Moscow and Yerevan, she focuses on search-driven performance advertising, meaning campaigns built to generate measurable actions (such as leads or purchases) rather than simply visibility. Her recent work spans different types of customer journeys, from beauty services in Dubai to legal services across the UAE, requiring adaptation to distinct user intent, compliance constraints, and cost dynamics. Beyond campaign management, she has developed a custom automation script to resolve recurring conversion-tracking issues, improving data reliability for optimization. Alongside campaign execution, she publishes and researches how artificial intelligence is being embedded into paid-search platforms, translating platform changes into concrete priorities for advertisers.