What Content Looks Like Before and After AI Search
A Canva image showing search results on Chat GPT vs traditional Google search
The BBC reported, based on a study by Cambridge University Press, that AI-generated stories are preferred over human-written ones. A key reason for their high ratings is that AI writing tends to be clearer and easier to understand. This matches advice from many writing conferences and webinars focused on AI, which emphasise that LLMs favour clear and digestible content. As both humans and LLMs seek straightforward information, writers must reconsider their previous strategies for search engine optimisation.
The traditional approach involved carefully selecting keywords, search volumes, page titles, metadata, and common search phrases. The goal was to craft a high-ranking page that effectively answered a query and provided readers with a compelling reason to click. When someone asks ChatGPT, Gemini, Perplexity or Claude a question today, they are not necessarily presented with ten blue links and left to decide which looks most useful. They are given an answer that has already been assembled from information gathered from multiple sources. That means the role of content is changing, too, to creating information that an AI system can understand, trust, extract and use when constructing an answer.
But our previous lessons on SEO remain useful. Websites still need to be technically sound, and content still needs to be discoverable and to reflect what your audience is looking for. The difference is that the definition of “good content” is becoming broader. Content needs to work for the person reading it and make sense within a much wider information ecosystem.
An easy way to grasp this change is to compare traditional content with what it needs to be today. Here are tactics that SUSO Digital proposes to help your content show up:
When answering what people ask beats matching keywords
Imagine you run a hotel and want to create a welcoming page for people searching for business hotels in London. Traditional SEO starts with keyword research, finding phrases like “business hotels London” and “London hotels for business travellers,” then including them in titles, headings, and metadata. This isn't wrong; knowing what people are searching for is important, and a page that doesn’t match their needs won't do well. But the issue comes when the keyword becomes the main focus instead of understanding the visitors. A page that focuses too much on keywords might just mention being a “leading business hotel in London,” list facilities, location, and generic reasons to stay, without really answering travellers' questions. An AI-first approach changes the focus to understanding what users want to know, like which areas are convenient, proximity to business districts, availability of meeting rooms, early breakfast, flexible check-in, reliable Wi-Fi, and options for longer stays. Creating content around these key questions makes the page more helpful and prioritises understanding over keyword stuffing.
Giving each section a purpose that readers care about
The same principle applies to how content is structured. A traditional article might use headings such as “Business Travel in London”, “Our Facilities”, “Why Choose Us” and “Our Location”. These headings are perfectly serviceable, but they do not necessarily tell a reader or an AI system exactly which question each section answers.
Compare that with headings such as “What is the best area of London to stay in for business?”, “Which London hotels have meeting rooms?”, or “How close are these hotels to the City and Canary Wharf?” The second approach is much closer to the way people think and search. More importantly, it gives the content a clear purpose. If a reader asks, “Which London hotels have meeting rooms?” and your article contains a clearly labelled section answering that question, there is very little ambiguity about what the section is about or what information it contains.
This does not mean every heading needs to be phrased as a question. That would quickly feel unnatural. The point is to consider the questions underlying the topic. A good piece of content should make it easy for a reader to find the answer they came for, rather than making them work their way through several paragraphs of marketing copy before getting there.
From burying the answer to giving it upfront
Another big difference is where the useful information is placed. Traditional web writing often favours longer introductions. It’s easy to feel drawn into spending several paragraphs setting the scene before reaching the main point, especially when creating polished marketing content. However, this can be frustrating for readers and isn't very helpful for AI systems trying to find the most relevant details on a page.
For example, if someone asks, “What are the best London hotels for business travellers?”, the answer shouldn’t be buried halfway through a lengthy 2,000-word article. It’s better to share the key information early on and then explain the reasons behind it.
This is where the classic journalistic idea of the inverted pyramid stays so useful. Start with the most important details first, then add the evidence, background, and additional info underneath. This simple shift makes content easier to navigate and gives AI systems clearer pieces of information to work with. It also helps when content is taken out of its original context. An AI might not reproduce an entire article when answering a question, but instead, select a specific statistic or explanation to use alongside other sources. The clearer each piece of information is, the more helpful it becomes.
Letting your work (not your slogans) do the talking
A key part of content strategy for AI-driven search is understanding the difference between claiming authority and demonstrating it. Your website might say you're “a leading expert,” “the UK's number one provider,” or “a trusted authority.” While these statements can be true, they tend to be self-promotional. It’s more impactful to show proof of these claims, like publishing original research, sharing insights from your work with clients, providing thoughtful commentary on industry trends, including team credentials, or linking to reputable external sources. Building visibility through interviews, media appearances, industry articles, conference talks, and active engagement in discussions can also help.
As AI search draws on information from across the internet, not just your website, credibility from third-party sources is especially important. Research from Muck Rack shows that 84% of links cited by AI platforms come from earned media, highlighting the importance of trustworthy external sources. Your focus should be on creating a trusted information environment around your brand, rather than only claiming authority on your website.
Building a whole body of knowledge instead of only a landing page
Another adjustment is how we should view individual pieces of content. In traditional search, focusing on a single page targeting one keyword was often enough; for example, creating an article about “business hotels in London” and considering the task complete once it ranked. However, AI search emphasises the importance of the broader context. If that article is your main resource on business travel, what happens when someone asks a follow-up question? They might want information about hotels near Heathrow, the best hotels for meetings, places with flexible check-in, or accommodations suitable for visits to both the City and Canary Wharf.
This highlights the value of topical depth. Instead of viewing content as isolated pages aimed at specific searches, consider it as a comprehensive body of knowledge that helps users understand a topic from multiple angles. For example, a financial services firm may produce content about mortgages, guides for first-time buyers, deposit requirements, affordability, fixed versus variable rates, and often-overlooked costs. A tech company might discuss not only its products but also the broader issues it addresses, industry trends, common challenges, implementation concerns, and comparisons with alternatives.
The aim isn’t to generate countless articles just for volume but to make your organisation helpful when someone seeks to understand a subject.
Why the ‘set and forget’ content approach is outdated
There is a subtle shift in how we should approach updating content. In the past, articles often stayed on a website for years with little oversight, particularly if they kept drawing traffic, which lessened the need for frequent updates. If your article includes 2021 statistics or mentions outdated legislation at present, it loses usefulness regardless of its previous search rankings.
AI search amplifies the need for accuracy, as outdated information can be extracted from the original article and presented in a new context. Regularly reviewing key content should now be part of your content strategy. This doesn't mean updating every few weeks for appearances, but taking responsibility for your published information and ensuring it remains accurate. When you make significant changes, noting when the content was last reviewed or updated provides helpful context for readers.
From writing for clicks to creating content worth citing
Perhaps the biggest change is how we think about the purpose of content. Traditional SEO has often been built around the click. AI search introduces the possibility that someone might never visit your website at all. That might sound like a problem, but it also changes the value of being a source.
If your research is quoted, your expertise is referenced for an AI answer, your content has still influenced the conversation. This is particularly interesting for brands whose value depends on expertise and reputation. A consultancy, law firm, financial services business, technology company, or specialist agency may not need everyone who encounters its expertise to click through immediately. Being consistently associated with useful answers can help build familiarity and credibility over time.
Aim to create content that helps
It is tempting to look at AI search and immediately ask what technical changes a website needs. There are certainly technical considerations that should not be ignored, but the bigger opportunity is to produce useful content.
The ideal article today isn't about keyword repetition. It should focus on understanding the reader's intent, providing a clear and credible answer, and offering sufficient detail to address subsequent questions. This sets a higher and more human standard. The main goal of moving to AI search is to create information that everyone can easily understand and trust, as well as reference to make decisions. Consistently doing so helps to build a lasting body of knowledge that supports your audience, brand, and the evolving AI systems that bridge the two.