SEO is not dead: 5 ways to win more citations from AI search

Semrush analysis cited in the article shows AI traffic to websites rose 66% in 2025, but AI still accounts for less than 0.15% of total visits—implying growing visibility pressure on traditional SEO. The article argues AI platforms (ChatGPT, Perplexity, Gemini) can both start and end the user journey without clicks to websites, potentially reducing organic referral traffic even when rankings don’t change. It outlines tactics to improve AI citations (e.g., avoid blocking AI crawlers, lead with clear passages, add sources, and consider an llms.txt file), noting study-reported visibility gains of up to 40%.

Analysis

This reads as a budget reallocation story, not a sudden demand shock. The highest-quality beneficiaries are the measurement/optimization layer, because AI citations create a new paid problem for marketers: they need tooling to see where they appear, why they appear, and whether that visibility converts. That favors SEMR first, and secondarily HUBS-style workflow vendors that can bundle content ops, CRM, and reporting into one stack.

The losers are the traffic-arbitrage businesses: affiliate-heavy publishers and SEO-dependent media assets where small changes in click-through rate can hit revenue harder than headline traffic trends suggest. ZD is exposed because the economic model depends on users leaving the platform; if AI answers satisfy the query upstream, the monetization gap widens even when brand awareness rises. For GOOGL, the effect is mixed: tighter query retention supports time spent inside its ecosystem, but it also accelerates open-web decoupling, which is a medium-term negative for content supply and a potential antitrust accelerant.

Time horizon matters. Over the next 1-3 months, this is mostly a narrative and procurement-cycle story, so expect limited P&L translation. Over 6-18 months, if AI answer surfaces keep improving, the open-web traffic tax becomes structural, and the market will likely reward platforms that sell visibility or own the workflow while compressing multiples on publishers with weak direct audiences. The key falsifier is conversion: if AI referrals begin to represent meaningful, recurring lead flow rather than vanity exposure, the bearish publisher call is too early.

Key Decisions for Investors

• Long SEMR on weakness over the next 1-3 months; thesis is that AEO/AI-search measurement becomes a new line item in marketing budgets. Use a tight stop if management does not show pipeline conversion or if customer adoption looks like free-tool usage only.
• Short ZD into any rally over the next 1-3 months as a hedge against AI-mediated traffic erosion in affiliate/content models. Falsify the trade if Q2/Q3 referral traffic from AI surfaces becomes a material share of total visits or if revenue deceleration does not show up.
• Pair trade: long SEMR / short ZD for 3-6 months. Best risk/reward if the market starts pricing AI visibility as a category while discounting publisher traffic leakage; size modestly because the revenue impact is still early and noisy.
• Use GOOGL as a monitor, not a conviction trade, until there is evidence that AI search improves monetization without accelerating open-web cannibalization. Add only if AI Mode/query retention lifts engagement metrics and ad load remains intact; otherwise keep neutral.
• Watch HUBS as a secondary beneficiary only if management starts talking about AI-search optimization as part of inbound marketing spend. If no budget reallocation appears by next earnings cycle, do not force the trade.