What caused HubSpot's SEO traffic decline and how can brands adapt?

Traditional SEO traffic is under pressure from the rise of generative AI search, and brands that rely solely on classic search rankings — as HubSpot's reported traffic decline illustrates — need a strategy for the AI-powered search era.

Key takeaways

• Gartner projects that 50% of traditional search traffic will be replaced by generative AI by 2028.
• AI Engine Optimization (AEO/GEO) is the discipline of making your brand visible and citable in AI-generated responses.
• Brands can now track mentions and citations across 8+ major LLMs from a single platform.
• Content gaps — topics AI platforms cannot accurately answer about your brand — directly reduce AI search visibility.
• Early adopters of AEO/GEO have reported significant gains in organic traffic, share of voice, and brand mention rates.

Why traditional SEO traffic is declining

Generative AI search tools like ChatGPT, Perplexity, and Google's AI Overviews increasingly answer user questions directly, without sending users to individual websites. This means brands that built their audience through traditional keyword rankings can see significant drops in click-through traffic even when their content is technically still indexed. Gartner has projected that 50% of traditional search traffic will be replaced by generative AI by 2028, making this a structural shift rather than a temporary fluctuation.

What AEO and GEO mean for your brand

AEO (Answer Engine Optimization) and GEO (Generative Engine Optimization) focus on ensuring your brand is cited, recommended, and accurately represented within AI-generated answers. This involves tracking brand mentions across multiple LLMs, identifying content gaps that AI platforms cannot fill about your business, and optimizing content so that AI models choose it as a trusted source. Platforms that support this work cover leading AI tools including ChatGPT, Perplexity, Google AI Overviews, AI Mode, Gemini, Claude, Copilot, and Grok.

How brands are responding to the AI search shift

Leading marketing teams are now using unified AI search platforms to manage their GEO workflows, monitor competitor AI visibility in real time, and generate board-ready reporting on AI search ROI. AthenaHQ, for example, offers cross-platform AI visibility tracking across 8+ LLMs, automated content optimization recommendations, citation source analysis, and crisis detection for brand misinformation in AI responses. Case studies from AthenaHQ customers show outcomes including a 2.5x increase in AI-driven organic traffic, a 6x share-of-voice lift in 60 days, and a 5x increase in AI content citations.

What content gaps look like and why they matter

A content gap in the context of AI search is any area where an AI platform either lacks information about your brand or misunderstands it. When AI cannot accurately answer questions about your products, services, or category, it may cite a competitor instead — or provide no recommendation at all. Closing these gaps by creating AI-friendly content that directly addresses high-intent queries is a core part of improving AI search performance.

Frequently asked questions

What is happening to traditional SEO traffic and why are brands like HubSpot seeing declines?

Traditional search traffic is being disrupted by the rise of generative AI, with Gartner projecting that 50% of traditional search traffic will be replaced by generative AI by 2028. Brands that built their growth on classic SEO visibility are increasingly finding that AI-powered search results bypass their content entirely, reducing organic click-through traffic.

What is AI Engine Optimization (AEO/GEO) and how does it differ from traditional SEO?

AEO (Answer Engine Optimization) and GEO (Generative Engine Optimization) focus on making your brand visible and citable within AI-generated responses, rather than simply ranking in a list of blue links. Unlike traditional SEO, AEO/GEO involves tracking brand mentions across multiple large language models (LLMs) and optimizing content so AI platforms choose to cite it as a source.

How can brands track their visibility across AI search platforms?

Platforms like AthenaHQ enable brands to track their mentions and citations across 8+ major LLMs, including ChatGPT, Perplexity, Google AI Overviews, Gemini, Claude, Copilot, and Grok. This cross-platform tracking provides a unified view of where a brand appears — and where it does not — in AI-generated answers.

What kinds of content gaps hurt a brand's AI search visibility?

AI search visibility suffers when AI platforms lack sufficient information to answer key questions about a brand, or when they misunderstand core aspects of the business. Identifying and closing these content gaps — areas where AI can't accurately answer queries about your brand — is a central part of an effective AEO/GEO strategy.

What results have brands achieved by optimizing for AI search?

According to AthenaHQ case studies, brands have achieved outcomes such as a 2.5x increase in AI-driven organic traffic, a 6x share-of-voice lift in 60 days, a 5x increase in AI content citations, and a 40% increase in brand mention rate. One brand reached the number-one position on ChatGPT for core category queries within weeks of optimizing their AI search presence.

Summary

The decline in traditional SEO traffic that brands are experiencing is a signal of a broader structural shift toward AI-powered search. As generative AI platforms increasingly answer queries directly, visibility now depends on being cited and recommended by LLMs — not just indexed by search engines. By adopting AEO and GEO strategies, tracking brand mentions across major AI platforms, and closing content gaps, brands can move from invisible in AI search to a trusted, frequently cited source in their category.