I believe we are witnessing the most significant disruption to paid advertising since the introduction of the auction model. While most marketing managers are focused on optimizing their current campaigns, a fundamental shift is occurring beneath the surface that will determine which small marketing teams thrive and which become obsolete.

The shift is this: Generative Engine Optimization (GEO) is replacing SEO as the dominant force in search visibility—and it's already destroying paid ad performance.

Let me explain why this matters to your team, and more importantly, what you must do about it.

Google made a decision in 2025 that should alarm anyone running paid campaigns. The company began placing AI Overviews—generative AI-powered answer boxes—above paid advertisements in search results. This is not a minor tweak. This is Google willingly sacrificing one of its most critical revenue sources to compete with ChatGPT and other large language models.

If Google is willing to cannibalize its own ad revenue, the threat must be existential. And the data confirms it.

According to Adthena's analysis of 21 million search engine results pages, paid search click-through rates have declined by 8-12 percentage points (a 20-40% relative drop) as AI-generated answers consume more real estate on the page. This is not a top-of-funnel problem. AI Overviews are now appearing on commercial queries—the exact keywords where your ad spend and ROI are concentrated.

In just four months, AI Overviews expanded across every vertical. The fastest growth is happening in the spaces where users research, compare, and plan purchases. These are the same high-intent queries that have historically delivered the best performance for paid ads.

Your ads are being pushed down. Your visibility is being compressed. And this is only the beginning.

Generative Engine Optimization is the practice of optimizing content to influence how large language models like ChatGPT, Gemini, and Perplexity surface information. While the concept sounds similar to traditional SEO, the mechanics are fundamentally different—and those differences have profound implications for marketing teams.

Traditional SEO relies on backlinks, domain authority, and keyword optimization to rank in search engines. Google's algorithm evaluates which pages are most authoritative based on how many credible websites link to them.

GEO operates on an entirely different principle. Large language models are language prediction engines, not authority evaluators. They scan the internet looking for patterns of text that are most likely to answer a user's query. The more frequently a certain phrase or concept appears in the LLM's dataset, the more likely it is to be included in the AI-generated response.

This means:

For marketing teams, this is both a threat and an opportunity. The brands that understand GEO early will capture visibility in AI-generated answers. The brands that ignore it will become invisible.

I have studied the most effective marketing teams navigating this transition, and they share a common approach. They are not abandoning SEO or paid ads—they are building a three-layer optimization stack that addresses traditional search, generative search, and paid visibility simultaneously.

Here is the framework:

Layer 1: Traditional SEO (Foundation)
Continue optimizing for Google's traditional algorithm. This remains essential for organic traffic and brand authority. Focus on backlinks, technical SEO, and keyword rankings.

Layer 2: GEO (Emerging Dominance)
Optimize content to influence AI-generated answers. This means:

Layer 3: Paid Ads (Adapted Strategy)
Adjust paid campaigns to account for AI Overviews compressing ad visibility. This means:

The teams that build all three layers will maintain visibility across the entire search landscape. The teams that focus only on one layer will lose market share.

The competitive advantage in this shift does not belong to the teams with the largest budgets. It belongs to the teams that move fastest.

Large enterprises are slow to adapt. They have entrenched SEO strategies, complex approval processes, and risk-averse leadership. Small marketing teams—especially those managing $10-50K monthly budgets—can pivot faster, test new approaches, and capture GEO visibility before the market catches up.

But this window is closing. In 12 months, generative engine optimization will be a standard practice. The teams that wait will be competing against established players who have already secured their position in AI-generated answers.

The question is not whether GEO will matter. The question is whether your team will be early or late.

This is not a tactical checklist. This is a strategic mindset shift that requires leadership buy-in and cross-functional coordination.

Step 1: Audit your current content through a GEO lens.
Go to ChatGPT or Perplexity and search for the queries your target customers use. Which brands are being cited? What content formats are being surfaced? Are you visible in these results? If not, why not?

Step 2: Identify your GEO content gaps.
Based on your audit, determine which content types you need to create to influence AI-generated answers. This likely includes comparison articles, "best of" lists, and how-to guides structured with clear, quotable language.

Step 3: Build a mention strategy.
GEO is not just about your owned content. It's about where your brand is mentioned across the web. Invest in earned media, partnerships, guest posts, and PR to increase the frequency of your brand mentions in contexts that LLMs crawl.

Step 4: Adjust your paid strategy.
Work with your paid media team to analyze which queries are being dominated by AI Overviews. Shift budget away from these queries toward longer-tail keywords or alternative platforms. Test creative formats that stand out in a compressed SERP.

Step 5: Monitor and iterate.
GEO is evolving rapidly. The websites that LLMs cite today may not be the same ones they cite in six months. Set up a monthly review process to track your visibility in AI-generated answers and adjust your strategy accordingly.

In 24 months, I predict that AI-generated answers will handle the majority of informational and comparison queries. Traditional search results will still exist, but they will be reserved for transactional queries and niche topics that AI cannot confidently answer.

For marketing teams, this means the battle for visibility is shifting from search engines to generative engines. The teams that prepare now will own the top position in AI-generated answers. The teams that wait will be fighting for scraps in a compressed, ad-heavy SERP.

The future of search is not Google versus ChatGPT. It is a hybrid landscape where both coexist, and marketing teams must optimize for both simultaneously.

The question is: Will your team lead this transition, or will you be left behind?

by SP
for the AdAI Ed. Team