How AI Overviews Are Changing Marketing Strategy in 2026: A Founder's Perspective

AI Overviews are fundamentally changing how marketing works because they have shifted visibility from the traditional ten blue links to a completely new channel where appearance is determined by LLM training and live search integration. Companies that optimized only for traditional Google search will find their visibility declining dramatically as users increasingly ask questions directly to ChatGPT and Perplexity rather than conducting traditional searches. The winners in 2026 are companies that simultaneously optimize for Google search and for AI search visibility.

I built Loamly because I saw this shift happening in real-time. My "direct" traffic was growing 126% year-over-year without any corresponding brand awareness changes. After investigating, I discovered that ChatGPT, Claude, and Perplexity were sending traffic that traditional analytics couldn't detect. This isn't a future problem—it's happening now.

The Data: How AI Overviews Have Evolved in 2025

The numbers tell a clear story. According to Semrush's research, AI Overviews appeared in 6.5% of search results in May 2024, peaked at 25% in June 2024, then stabilized around 16% by the end of 2025.

What this means: One in six Google searches now shows an AI-generated answer at the top. That's not a small change—it's a fundamental shift in how people discover information.

But here's what most marketers miss: the impact isn't just on Google. ChatGPT, Perplexity, and Claude are separate channels with their own discovery patterns. When you combine all AI search platforms, the percentage of searches that go through AI systems is much higher than 16%.

The real number: Based on Adobe Analytics data, AI-sourced traffic grew 1,200% in 2025. That's not a typo. Twelve hundred percent growth in a single year.

This isn't a trend. It's a new reality.

Why Traditional SEO Strategy Is No Longer Sufficient

Traditional SEO works on a simple principle: rank higher in Google's ten blue links, get more clicks. The entire industry is built around this model.

The problem: AI Overviews don't work like ten blue links. They work like conversations.

When someone searches "best CRM for startups," Google's AI Overview might cite three specific tools with explanations. It doesn't show ten links—it shows a direct answer. Either you're in that answer, or you're not. There's no page 2.

The clickthrough rate reality:

Traditional SEO assumes you need to rank #1 to get clicks. But with AI Overviews, if you're cited in the answer, you get the click—regardless of whether you rank #1 in traditional search.

According to ROI Amplified's case study, a commercial lending firm that got ChatGPT recommending them saw 15% of all inbound sales calls come directly from ChatGPT leads. These leads had significantly higher close rates because prospects already trusted the recommendation.

The strategic shift: You can't optimize for AI search the same way you optimize for traditional search. You need different tactics:

• Semantic structure instead of keyword density
• Answer-first content instead of long-form articles
• Entity relationships instead of backlink profiles
• Citation quality instead of ranking positions

I learned this the hard way. I spent months optimizing Loamly's content for traditional SEO. It worked—I ranked well in Google. But I wasn't appearing in ChatGPT or Perplexity. That's when I realized I was optimizing for the wrong channel.

The Clickthrough Rate Surprise

Here's what surprised me: AI Overviews actually increased clickthrough rates for companies that appeared in them.

The data: According to Search Engine Journal's analysis, websites cited in AI Overviews saw 15-20% higher clickthrough rates compared to traditional #1 rankings.

Why this happens: When AI systems cite you, they're endorsing you. Users trust that endorsement. They click because they believe the AI has vetted you. It's not just a link—it's a recommendation.

The catch: You can't game this. AI systems evaluate sources using E-E-A-T (Experience, Expertise, Authoritativeness, Trustworthiness). If your content lacks these signals, you won't appear in AI Overviews—no matter how well you rank in traditional search.

This creates a new competitive dynamic: companies with strong E-E-A-T signals get cited in AI Overviews and see higher clickthrough rates. Companies without these signals get left behind, even if they rank well in traditional search.

Why AI Search Visibility Requires Different Optimization

Traditional SEO focuses on:

• Keyword research and density
• Backlink building
• Technical optimization (page speed, mobile-friendly)
• Content length and freshness

AI search optimization focuses on:

• Semantic structure and entity relationships
• Answer-first content format
• E-E-A-T signals (author credentials, domain authority)
• Conversational query alignment

The fundamental difference: Traditional SEO optimizes for algorithms. AI search optimization optimizes for understanding.

When ChatGPT evaluates whether to cite your content, it's not looking for keyword matches. It's looking for:

• Does this content answer the question clearly?
• Is this source trustworthy?
• Does this content provide specific, useful information?

If your content is optimized for traditional SEO but not for AI understanding, you'll rank well in Google but won't appear in AI Overviews.

My experience: I built Loamly's content to rank for "AI visibility" and "GEO" keywords. It worked—I rank #1-3 for those terms. But when I asked ChatGPT "What tools track AI visibility?", it didn't mention Loamly. It mentioned established analytics platforms that had better E-E-A-T signals, even though they didn't rank as well in traditional search.

That's when I realized I needed to optimize for both channels simultaneously.

The Timing Advantage: Why 2026 Is When Companies Must Act

Here's why 2026 is the inflection point:

1. LLM training compounds over time

AI systems learn from citations. If ChatGPT cites you in 2026, it's more likely to cite you in 2027. The companies that establish visibility now will maintain it because AI systems build trust networks that compound.

2. The market is still early

Most companies haven't optimized for AI search yet. The ones that start now have a first-mover advantage. By 2027, everyone will be doing it, and the advantage will be gone.

3. Budget reallocation is happening

Marketing teams are starting to allocate budget specifically for AI visibility. According to Gartner's 2026 marketing trends, 40% of marketing leaders plan to increase investment in AI search optimization in 2026.

4. The data is clear

We're past the speculation phase. The data shows AI search is growing, AI Overviews are increasing, and companies that appear in AI responses see higher conversion rates. The question isn't "should we do this?"—it's "how fast can we start?"

My recommendation: Start optimizing for AI search visibility now, even if you're still optimizing for traditional search. The two aren't mutually exclusive—you can do both. But if you wait until 2027, you'll be competing against companies that have been building AI visibility for a year.

What This Means for Your Marketing Budget and Organization

The shift to AI search requires budget reallocation, not just new tactics.

Traditional search budget (2025):

• 80% Google organic search
• 15% Google Ads
• 5% other channels

AI search budget (2026-2027):

• 50% Google organic search
• 20% Google AI Overviews optimization
• 15% ChatGPT/Claude/Perplexity visibility
• 10% Google Ads
• 5% other channels

The organizational changes:

Content teams need to learn answer-first writing, semantic structure, and E-E-A-T optimization. This isn't just SEO—it's a new content format.

Analytics teams need tools that track AI visibility, not just traditional search rankings. Most analytics tools are blind to AI traffic.

Marketing leadership needs to understand that AI search is a separate channel with separate metrics. You can't measure AI visibility success using traditional SEO KPIs.

The budget reality: You can't just add AI search optimization on top of existing SEO budgets. You need to reallocate. That means making hard choices about what to cut or what to reduce.

My approach: I'm spending 50% of my marketing time on AI visibility optimization and 50% on traditional SEO. That's the split that makes sense for 2026. By 2027, I expect it to be 70/30 in favor of AI search.

The Strategic Imperative

The companies that win in 2026 will be the ones that:

• Optimize for both traditional search and AI search simultaneously
• Build E-E-A-T signals into their content from day one
• Track AI visibility as a separate channel with separate metrics
• Allocate budget specifically for AI search optimization
• Start now, not in 2027

The companies that lose will be the ones that:

• Optimize only for traditional search
• Ignore AI search until it's too late
• Measure success using outdated SEO KPIs
• Wait for "proof" that AI search matters (it's already proven)

The bottom line: AI Overviews aren't replacing traditional search. They're creating a new channel alongside it. The winners will be companies that master both channels. The losers will be companies that only master one.

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