Businesses Scramble to Stay Visible in the Age of AI Search

AI-powered search is reshaping how users discover information online, forcing businesses to rethink visibility, content strategy, and digital growth.

A fundamental shift is underway in how people search for information online—and businesses are feeling the impact in real time. The rise of AI-driven search tools and generative interfaces is disrupting traditional web traffic patterns, forcing companies to rethink not just search engine optimization (SEO), but the very structure and purpose of their digital presence.

For companies like HubSpot, the consequences are already measurable. The firm reportedly lost 140 million website visits in a single year, a decline closely tied to changes in how users interact with search engines and AI platforms. As AI-generated answers increasingly replace traditional search results, fewer users are clicking through to websites—undermining a core pillar of digital marketing.

From search engines to answer engines: a structural shift in user behavior

Historically, search engines acted as gateways, directing users to external websites through lists of ranked links. Today, that model is being replaced by “answer engines”—AI systems that generate direct responses to user queries without requiring additional clicks.

Tools powered by large language models (LLMs), such as ChatGPT and Google’s AI-enhanced search features, are redefining expectations. Instead of scanning multiple sources, users now receive synthesized, conversational answers instantly. According to HubSpot’s chief marketing officer Kipp Bodnar, this shift dramatically reduces click-through rates—by as much as 60% to 70% when AI summaries appear at the top of search results.

This behavioral transformation is not just incremental—it represents a redefinition of search itself. Queries are becoming longer, more complex, and more intent-driven. While traditional searches might consist of a few keywords, AI queries often span 40 to 60 words, reflecting highly specific user needs.

The emergence of AEO and GEO: optimizing for AI visibility

In response, businesses are adopting new strategies collectively known as Answer Engine Optimization (AEO) or Generative Engine Optimization (GEO). These approaches aim to ensure that a company’s content is not just discoverable by search engines, but also extractable and usable by AI systems.

Unlike traditional SEO—which prioritizes keywords, backlinks, and ranking positions—AEO focuses on clarity, structure, and contextual relevance. Content must be easily interpreted by AI models, often requiring concise summaries, structured data, FAQs, and modular content blocks that can be seamlessly integrated into AI-generated answers.

HubSpot itself has begun restructuring its content strategy accordingly. Instead of long, monolithic product pages, the company is breaking information into smaller, targeted segments that AI systems can extract more efficiently. This modular approach reflects a broader trend toward “machine-readable” content design.

Content strategy evolves: from product pages to knowledge ecosystems

The implications extend beyond formatting. Entire content strategies are being reimagined to align with AI-driven discovery. For example, UK-based spice retailer Spice Kitchen is building a comprehensive content cluster the history of the spice trade—not to directly sell products, but to establish topical authority and increase the likelihood of being cited by AI systems.

This reflects a critical shift: businesses are moving upstream in the customer journey. Instead of targeting users at the point of purchase, companies are now focusing on the research and decision-making stages, where AI tools play a dominant role.

According to digital marketing agency Lumos Digital, content such as buying guides, comparative analyses, and authoritative explainers performs particularly well in AI contexts. These formats provide structured, high-confidence answers that LLMs can easily incorporate into their responses.

Trust, authority, and the new rules of digital credibility

As AI systems increasingly act as intermediaries between users and information, the importance of trust signals has intensified. Concepts like expertise, authority, and trustworthiness—long emphasized in SEO—are becoming even more critical in the age of AI.

To improve their chances of being cited, companies are investing in high-quality backlinks, transparent authorship, editorial policies, and credible sourcing. Linking to authoritative external resources—such as Google’s content guidelines—also helps reinforce legitimacy in the eyes of both search engines and AI models.

This shift effectively raises the bar for digital content. Low-quality, keyword-stuffed pages are increasingly filtered out, while well-structured, authoritative content gains prominence—not just in rankings, but in AI-generated answers themselves.

Traffic decline, conversion rise: a paradox emerges

While overall website traffic may be declining, the quality of incoming visitors is improving. Both HubSpot and building supplier MKM Building Supplies report that users arriving via AI tools are more likely to convert into customers.

This phenomenon reflects the role of AI as a pre-qualification layer. By the time users click through to a website, they have already received detailed information, compared options, and formed purchase intent. In effect, AI is compressing the traditional marketing funnel, reducing the need for extensive on-site education.

However, this also introduces new risks. If AI systems provide sufficiently comprehensive answers, users may never visit the source website at all. For some businesses, this could lead to a near-total erosion of organic traffic—a scenario already being contemplated by industry leaders.

Platform dynamics: ChatGPT vs. Google in the AI discovery race

Another notable development is the shifting balance of power between platforms. While Google remains the dominant search engine, AI-native tools are gaining traction as discovery channels.

Some businesses report that ChatGPT is now driving more referral traffic than Google’s own AI features. This suggests a broader change in user preference, with consumers increasingly choosing dedicated AI interfaces over traditional search engines—even when those engines incorporate AI capabilities.

This fragmentation of discovery channels complicates digital strategy. Companies must now optimize for multiple AI ecosystems, each with its own data sources, ranking mechanisms, and response styles.

The future of search: adaptation as a survival strategy

The transition from search engines to AI-driven answer systems represents one of the most significant shifts in the history of the internet. For businesses, the implications are profound: visibility is no longer determined solely by search rankings, but by inclusion in AI-generated narratives.

Success in this new environment requires a combination of technical adaptation, content innovation, and strategic foresight. Companies must understand how AI models interpret information, anticipate evolving user behavior, and continuously refine their digital presence.

As HubSpot’s experience illustrates, the cost of inaction can be substantial. But for those willing to adapt, the AI era also presents new opportunities—higher-quality leads, more targeted engagement, and a chance to redefine how brands connect with their audiences in an increasingly automated world.