Websites across industries are losing millions of visits as artificial intelligence fundamentally changes how people search for information. HubSpot, which provides sales, marketing and customer service tools for business companies, lost 140 million visits in a single year. The cause wasn’t a product failure or algorithm penalty, it was AI.
Search behavior is shifting in three distinct ways. Users are increasingly bypassing traditional search engines entirely and going directly to AI tools like ChatGPT. Meanwhile, search engines themselves have begun embedding AI overviews at the top of results, which answer questions without requiring users to click through to another website. Additionally, search algorithms have tightened their standards for credibility, rewarding websites seen as authoritative on a core topic.
The impact on traffic is measurable. According to HubSpot’s chief marketing officer Kipp Bodnar, “The click-through rate for searches that have AI overviews is about 60% to 70% lower.” For many companies, this means fewer customers discovering their site through organic search.
How Businesses Are Adapting Content Strategy
Companies are turning to answer engine optimisation (AEO), sometimes called generative engine optimisation (GEO). This practice focuses on helping websites rank well in AI tools, including AI overviews and platforms like ChatGPT, which run on large language models (LLMs).
The shift requires understanding how search behavior has changed fundamentally. In a traditional Google search, users might enter four to six words. In AI search, the average query length is 40 to 60 words, an order of magnitude increase in specificity. A company renting motorhomes in New Zealand might need to publish content on popular animals children want to see, written in natural language that matches the questions people actually ask.
HubSpot restructured its website content to reflect this reality. Rather than long articles explaining how product features work together, the company now breaks information into small chunks that AI can easily extract. Bodnar says this approach has worked: “We’ve been able to use answer engine optimisation to increase the conversion rate and quality of the people who are coming to us.”
Content Structure for AI Discovery
AI tools process meaning differently than search engines process keywords. This requires a different approach to content architecture. MKM Building Supplies, an independent builders’ merchant, restructured its website to include summaries, bulleted lists, FAQ sections, and clear sitemaps designed for AI bot navigation.
Andy Pickup, digital director at MKM, recognized the stakes early: “We are seeing fewer people come to the site because they’re getting the answers from an AI model.” He created what he calls a “defensive strategy,” publishing blogs about best-selling products positioned as expert content that answers customer questions comprehensively.
Spice Kitchen, a gift spice company, took a different approach by building a content cluster focused on the history of the spice trade. Rather than a traditional shop section, the company created what resembles a training course. “We’re wanting to see whether we can hit the AI search bots with that content,” says Ann Lowe, head of PR and communications. “It won’t be a shop. This is for people that are doing research, but they get to discover us along the way.”
Nathan Pearson, co-founder of digital agency Lumos Digital, explains the strategic shift: “Historically, you’ve always optimised the product page so that you are picking people up at the moment they’re ready to buy. Now, that focus seems to be shifting towards the research and decision stage and winning them at that point.”
Building Credibility for AI Systems
Andy Lochtie, co-founder of Lumos Digital, emphasizes three factors that help websites rank in AI systems: expertise, authority, and trust indicators. These include backlinks from other trusted websites, outbound links to high-quality sources, content policies, and author biographies.
This approach differs significantly from traditional SEO, which focused heavily on keywords and search engine algorithms. AI tools require clear, concise information that demonstrates credibility across multiple signals rather than keyword density or link volume alone.
Early Results and Traffic Patterns
Companies implementing these strategies are seeing measurable results. MKM Building Supplies grew AI referral traffic from almost nothing to “a low double-figure percentage” in one year, and it continues climbing. Critically, AI visitors convert at higher rates than search engine visitors.
Pickup attributes this to a fundamental difference in user confidence: “My theory is that customers have got the information they need from the LLM answer, which gives them confidence to make a purchase.”
HubSpot now receives between 7% and 12% of website visitors from AI most months, and Bodnar expects this to grow further. He notes that indirect influence matters too: “You’ll see people coming through direct traffic and other sources because they were influenced by those LLM responses.”
For companies trying to remain competitive, the challenge is clear. Search behavior is not shifting back. Bodnar puts it bluntly: “I don’t know how you are a competitive business in the future without having a strong competency in this.”
