AI Search: An Investor's Briefing on the Biggest Shift in Digital Visibility Since Google

If you are a PE operating partner or a VC board member, you have likely heard your portfolio companies mention AI search. You may have nodded and moved to the next agenda item. This briefing is designed to explain why that was a mistake, and what you should be asking instead.

The Shift in 90 Seconds

For two decades, businesses acquired customers through two primary digital channels: paid advertising and organic search (SEO). A predictable share of revenue flowed through Google. Marketing teams optimised for it. Financial models depended on it.

AI search engines, ChatGPT, Perplexity, Google AI Overviews, Microsoft Copilot, and Claude, are disrupting this model. Instead of showing users a list of websites, they provide direct answers with specific brand recommendations. Users increasingly skip the traditional search results page entirely.

This matters for investors because it directly affects customer acquisition costs, organic traffic volumes, brand visibility, and ultimately, revenue.

The Financial Impact: What We Are Already Seeing

Three measurable effects are emerging across the portfolios we advise:

1. Organic traffic erosion. Companies that depend heavily on informational organic traffic are seeing declines of 10 to 25% year-over-year in categories where AI Overviews are prevalent. Google's own AI Overviews answer the query directly, reducing the need to click through to the source site. For companies where organic traffic drives a significant share of pipeline, this is a revenue risk.

2. Shifting customer acquisition economics. As organic traffic declines, companies compensate with paid spend. This increases customer acquisition cost (CAC) and compresses margins. We have observed CAC increases of 15 to 30% in portfolio companies that have not adapted their organic strategy to account for AI search.

3. New citation-driven discovery. Simultaneously, companies that are being cited by AI engines are seeing a new source of qualified traffic. AI-referred visitors convert at rates comparable to branded search traffic, roughly 2 to 4 times higher than non-branded organic. For companies positioned correctly, AI search is net positive.

The divergence between companies adapting and companies ignoring this shift is already visible in their numbers. Within 18 months, it will be visible in their valuations.

What to Look for in Due Diligence

Most due diligence processes assess SEO as a line item in the marketing review. That is insufficient. Here is what a thorough assessment of AI search readiness should include:

AI Citation Audit

Query the major AI engines (ChatGPT, Perplexity, Claude, Gemini) with the 20 to 30 most commercially important questions in the target company's category. Document which brands are cited, in what position, and with what framing. If the target company is absent from AI recommendations in its core category, that is a risk factor.

Organic Traffic Trajectory

Look at organic traffic trends over the past 18 months, segmented by query type. Informational traffic declining while transactional traffic holds steady is a signature pattern of AI search disruption. The informational queries are being answered by AI engines before users reach the website.

Authority Infrastructure Assessment

Evaluate the target's domain authority, backlink profile quality, content depth, and structured data implementation. These are the inputs that determine AI citation eligibility. A company with thin content, a weak backlink profile, and no structured data markup is poorly positioned for AI search regardless of its current SEO performance.

Competitive Citation Position

Map the target's AI citation position relative to direct competitors. A company that is the third-most-cited brand in its category has a credible path to improvement. A company that is entirely absent from AI citations has a significant gap to close.

The Valuation Implications

We see three categories of valuation impact:

Positive premium: Companies with strong AI citation presence, high-authority organic infrastructure, and diversified traffic sources. These companies are building a moat that will become more defensible over time. Expect this to be increasingly reflected in growth multiples.

Neutral: Companies with adequate organic foundations but no specific AI search strategy. These represent an opportunity, the infrastructure can be built, but the investment required should be factored into the deal model.

Discount factor: Companies with weak organic infrastructure, high dependence on a single traffic channel (paid or organic), and no AI search presence. These companies face increasing CAC, declining discovery, and competitive displacement. The risk should be priced in.

What Portfolio Companies Should Be Doing Now

For existing portfolio companies, our recommendation is straightforward:

• Audit AI citation presence. Every portfolio company should know where it stands in AI recommendations for its core commercial queries. This takes 2 to 3 weeks to do properly.
• Assess organic infrastructure. Evaluate whether the company's SEO foundation is strong enough to support AI citation authority. Companies that treat SEO as bolt-on marketing rather than infrastructure are at higher risk.
• Build an AEO programme. For companies in categories where the competitive window is still open, this is a high-ROI investment. The cost of establishing authority now is a fraction of what it will be in 18 to 24 months.
• Integrate AI metrics into reporting. Add AI citation tracking to the standard marketing dashboard. If the board is reviewing SEO metrics without AI search metrics, the picture is incomplete.

How We Support Investors

We work with PE and VC firms at two levels. Pre-deal, we conduct organic due diligence assessments that include AI search readiness as a standard component. Post-deal, we build and execute AEO and organic growth programmes for portfolio companies.

If you are evaluating a target or reviewing portfolio performance, our organic due diligence service provides the data you need to make informed decisions about AI search risk and opportunity.