AI Overviews and LLM Distortion: What It Means for Your Investments

The Shift Nobody Saw Coming

In early 2024, organic traffic felt invincible. High rankings meant predictable visitors, and visitors meant revenue. Then Google launched AI Overviews, and the rules changed overnight.

For investors evaluating digital assets, this isn't just a marketing problem. It's a valuation problem. The traffic you're buying today may not exist in the same form tomorrow.

What Are AI Overviews?

AI Overviews (previously called Search Generative Experience or SGE) are Google's AI-generated summaries that appear at the top of search results. Instead of clicking through to websites, users get synthesised answers directly in the SERP.

The implications are profound:

Zero-click searches are accelerating: Users get answers without visiting your site

Source attribution is inconsistent: Even when cited, traffic is reduced

Informational queries hit hardest: The "top of funnel" content is most vulnerable

LLMs compress your content: Your 2,000-word guide becomes a 50-word summary

The LLM Distortion Effect

Beyond Google, ChatGPT, Perplexity, Claude, and other LLMs are changing how information is consumed. We call this "LLM Distortion" — the phenomenon where:

Your content trains models but you receive no traffic

AI cites competitors even when your content is superior

Brand differentiation collapses when responses homogenise sources

Freshness matters less because models have training cutoffs

The Traffic Value Problem

Traditional traffic valuation uses Ahrefs' methodology: the cost to acquire the same traffic via Google Ads. But this assumes traffic continues at current levels.

With AI Overviews, we're seeing:

| Query Type | Traffic Impact | Valuation Adjustment | |------------|----------------|---------------------| | Navigational | Minimal (-5%) | None required | | Transactional | Moderate (-15%) | -10% to -20% | | Informational | Severe (-40%+) | -30% to -50% |

If 60% of a site's traffic is informational, you need to discount the traffic value accordingly.

How to Assess AI Visibility Risk

At ParadoxSEO, we've added 16 AI Visibility (AEO) aspects to our 301-aspect framework. Here's what we evaluate:

1. Citation Frequency in LLMs

Using tools like Eigemy and Verity AI, we track how often a domain is cited in AI responses across ChatGPT, Perplexity, and Claude.

2. Content Structure for AI

LLMs favour:

Clear definitions and explanations

Structured data and tables

Authoritative sourcing

Unambiguous statements

3. Brand Recognition

Does the LLM know your brand? Try asking: "What is [brand name]?" If the response is thin or wrong, you have a brand visibility problem.

4. First-Party Data Advantage

Content based on proprietary data, original research, or unique expertise is harder for AI to synthesise from elsewhere.

Adapting Your Strategy

For business owners and investors, here's the playbook:

Short-Term (0-6 months)

Audit your traffic by query type: How much is informational vs transactional?

Track AI citations: Are you being cited in AI Overviews and LLM responses?

Identify defensible traffic: What queries are resistant to AI disruption?

Medium-Term (6-18 months)

Shift content strategy: Less generic information, more first-party insight

Build brand queries: Users searching your brand name can't be AI-disrupted

Invest in conversion: Extract more value from reduced traffic

Long-Term (18+ months)

Become the source: Original research, data, and tools that LLMs must cite

Multi-channel distribution: Email, community, and owned audiences

AI-first content design: Structure content for AI consumption and citation

The Due Diligence Imperative

If you're evaluating an acquisition where organic traffic is material, you must now ask:

What percentage of traffic is at risk from AI Overviews?

Is the brand recognised by major LLMs?

Is the content differentiated or commodity?

What's the company's strategy for AI visibility?

Ignoring these questions is like ignoring mobile in 2015. The shift is happening whether you acknowledge it or not.

Tools for AI Visibility Assessment

We recommend:

Eigemy: AI visibility monitoring and optimisation

Verity AI: LLM citation tracking and analysis

Ahrefs Brand Radar: AI response monitoring

Manual LLM queries: Test how AI describes your brand and products

The Bottom Line

AI Overviews and LLM distortion represent the biggest shift in organic search since mobile. For investors, this means:

Traffic values need adjustment: Apply AI disruption discounts

Due diligence must evolve: Add AI visibility to your assessment

Growth projections must account for AI: Don't extrapolate historical trends

The winners will be those who adapt fastest. The losers will be those who pretend the old rules still apply.

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*Need an AI-adjusted traffic valuation for your next deal? Contact us for a ParadoxSEO due diligence assessment.*