For the better part of two decades, online search was synonymous with Google. Businesses fine-tuned their digital presence for keywords, meta tags and backlink strategies, all with one goal: Land on page one of the search results. But the landscape has changed. We’re entering a new era, one where the question is no longer who ranks first but who gets cited by the AI.
The arrival of large language models (LLMs) like ChatGPT, Gemini and Claude has introduced a fundamentally different way to retrieve information. These tools do not point users to a list of links. Instead, they deliver direct, synthesized responses, drawing from vast corpora of public content. And they are beginning to reshape the expectations of how people search altogether.
From Search Results To Synthesized Answers
The shift may feel subtle at first, but the implications are significant. Users no longer have to skim through a dozen articles to piece together an answer. Instead, AI models offer the summary upfront. This isn’t just more convenient; it’s structurally different. It bypasses the traditional web entirely.
We’re seeing this play out even within Google’s own ecosystem. With the rollout of its AI Overviews (formerly Search Generative Experience), Google has begun integrating AI-powered summaries at the top of many results pages. The outcome? A recent analysis found that when these AI summaries are present, traditional organic click-through rates can drop by as much as 70%. Even paid ads take a hit. What we’re witnessing is not a slight dip in traffic; it’s a reallocation of user attention away from web pages and toward machine-generated summaries.
At the same time, standalone AI assistants are gaining traction. ChatGPT now ranks among the most visited websites globally, with hundreds of millions of monthly users. It has also become a starting point for research, brainstorming and decision making tasks once firmly in Google’s territory. Even smaller players like Perplexity are gaining momentum, offering a hybrid search-chat experience that combines AI answers with cited sources—an early glimpse into what next-gen search may look like.
What This Means For Your Business
If your company’s discoverability strategy still relies heavily on traditional SEO techniques, it’s time to recalibrate. The notion of “ranking” is being replaced by something more ephemeral: being included, referenced or cited by an AI system that synthesizes answers in real time.
This new landscape rewards clarity, trust and technical readiness over clever keyword placement. It values the ability to be understood by machines just as much as being read by humans. And it places a premium on domain authority, not in the SEO sense, but in the broader sense of being seen as a reliable, high-quality source of truth.
Here is what digital marketing teams should be doing right now:
1. Write for answers, not just algorithms. Content must be structured in ways that make it easy to extract and reuse. That means addressing questions clearly, using plain language and front-loading the value. Think in terms of what an LLM might quote or paraphrase when constructing a response. Analyse how people phrase their interactions with LLMs and adjust your content to fit this design pattern.
2. Demonstrate authority through quality. AI models tend to draw from reputable, high-quality sources. This includes industry publications, well-maintained blogs, peer-reviewed research and sites with a history of accurate information. Superficial content created purely for traffic will struggle to earn citations. Instead, focus on depth, originality and trust signals like author bios, clear sourcing and consistent topical expertise.
3. Invest in structured data. Schema markup and structured metadata can help machines understand your content more effectively. It is not glamorous work, but it is essential if you want to be eligible for rich results, snippets or inclusion in AI-generated overviews. Especially for product, event or FAQ content, proper tagging increases the odds that your site is seen as “machine-readable.”
4. Go beyond Google. Traffic diversification is no longer a luxury but rather a necessity. Web crawlers that feed LLMs are increasingly pulling from non-traditional platforms to find fresh, credible content. Forums like Reddit, niche communities, technical Q&A sites and public newsletters are becoming valuable sources for both real-time conversations and training data. These platforms signal human engagement and topical relevance—two things that LLMs often prioritize when generating responses.
The Strategic Imperative
This is not just a shift in how people search. It’s a shift in who controls the gateway to information—and how your company earns a spot in that conversation. Google may still dominate the market by volume, but AI tools are reshaping the experience of search. And user habits are changing faster than most brands are reacting. Traditional SEO isn’t going away. But it is becoming only one piece of a much more complex discoverability puzzle. Being “AI-visible” is the next frontier.
Feature Image Credit: Getty
