I don’t think ‘SEO is dead’ rhetoric is a useful place to start, because it’s not really what’s happening. Search isn’t disappearing, but the word might not stretch far enough any more for what’s actually going on: it’s spreading out across more platforms as AI tools, answer engines, and discovery surfaces join the mix.
A lot of the sessions at Brighton SEO 2026 were framed as ‘search’ talks, but the conversation kept moving into brand, content, PR, paid media, reporting, community, AI workflows, and trust. It feels like search is becoming harder to separate from the rest of marketing, and it’s easy to jump from ‘search is changing’ into another tactical checklist. But the bigger shift is that search is becoming more dependent on the whole system around the brand: how clearly it explains itself, how consistently it shows up, how much proof sits around it, and whether buyers and machines understand why it should be trusted.
For B2B, that matters because the buying journey was never particularly tidy. People aren’t searching for one neat answer; they’re trying to reduce risk and work out whether they’d feel comfortable taking a recommendation back to other stakeholders. Being found still matters, but the harder bit is making sure that once someone finds the brand, they can quickly understand who you are, what you do, why you’re credible, and whether you’re worth taking seriously.
The SEO talks kept drifting into other things (which felt pretty telling)
One of the more interesting things about the event was how often the ‘SEO’ talks didn’t stay inside SEO for long. They’d start with visibility, rankings, or structured data, but quickly move into content quality, brand credibility, expert voices, PR mentions, and how AI systems decide what to cite.
That doesn’t mean the technical side matters less; crawlability, site structure, schema, and SERP visibility still count. But SEO is harder to get right if it’s disconnected from how the business explains itself across the places buyers form an opinion. The questions get broader: are there credible people attached to the brand? Do third-party sources describe it the way we want to be known? Can a buyer, search engine, or AI system understand what it actually does? Does the content add anything useful, or is it the same article everyone else could publish with a different logo?
Trust feels like the one consistent thread across everything
The more I think about it, trust was probably the thread that connected most of the sessions, even where it wasn’t mentioned directly. Erin Simmons’ talk on trust-centred SEO framed search less as an information retrieval exercise and more as a confidence-building process: people search because they’re uncertain, looking for something that makes them feel more confident about what to believe or do next.
That confidence might come from the brand’s own website, or from a named expert, a customer story, or a recommendation from someone the buyer already trusts. In B2B that feels familiar, because buying comes with real risk: budget, implementation, stakeholder, and the awkward risk of something that looked great in the sales process but wobbles the second someone asks how it actually works.
So trust isn’t a soft brand extra sitting separate from performance; it affects whether someone believes the landing page and feels confident enough to speak to sales. The practical version isn’t just ‘build trust’; it’s making the people behind the brand visible, connecting claims to evidence, and answering what buyers are actually worried about.
The machine-readable side is really about being clearer
The AI search side can sound very technical, once people start talking about structured data, entities, schema, and knowledge graphs. The more useful point is practical: if AI systems are trying to understand what a business does, who it serves, what it offers, which people and proof points are connected to it, and why it should be treated as credible, vague or inconsistent information becomes a real issue.
That’s where Alex McKenna’s session on next-generation search was useful, though I’d be careful with any platform-led claim that makes the future sound too solved. If discovery is shaped by systems that interpret and recommend based on what they understand, ambiguity becomes expensive: scattered or contradictory facts mean the system works harder to describe the brand confidently, leaving more room for it to be flattened or missed.
Structured data can help, but it’s not a magic fix; it won’t make a weak proposition strong. What it can do is reduce confusion, which matters when systems are deciding whether a brand should be included in an answer. For B2B brands, that means looking at the connected picture, services, sectors, people, case studies, PR, rather than individual pages.
Average content has less room to hide
The content conversations kept coming back to a point worth sitting with: if AI can produce average content quickly, average content becomes less useful. That doesn’t mean AI-assisted content is automatically bad; the helpful distinction is original versus derivative, and whether the content has any reason to exist beyond a keyword having search volume.
A lot of SEO content has followed a familiar pattern for years: find the keyword, cover the expected subtopics, add headings, publish something broadly helpful. That’s less convincing as the whole strategy when every competitor can produce a passable version of the same page. The stronger opportunity is in things harder to copy: proprietary data, original research, expert judgement, first-hand experience, a clear point of view.
A useful test is whether the same page could sit on a competitor’s website with the logo changed. If it could, it isn’t making the brand more memorable or easier to recommend, awkward given the three weeks and six stakeholders it took to get live, but the internet doesn’t award points for effort.
AI workflows probably need more discipline than most teams have given them
Another thing that stood out was how normal AI use has become inside marketing teams, so the interesting question isn’t whether people are using it. They are. The more useful question is whether they’re using it consistently and well, or just creating more drafts for someone else to review.
One simple prompt structure discussed was role and context, task, source material, output format, constraints, and examples. It sounds obvious, which is probably why it gets skipped; people jump straight to the output, then spend the next few prompts fixing what should’ve been in the brief. For B2B teams, prompting is looking less like a personal productivity trick and more like an operational skill, one that only works as a shared asset. Prompts can make weak thinking repeatable, so judgement still has to sit upstream of the tool.
Paid media is changing, but it still needs people asking better questions
The paid media sessions reinforced something we’re already seeing: automation is getting stronger and helps with scale, bidding, and efficiency. But automation isn’t strategy, and platforms optimise towards the signals they can see, so if those signals are incomplete, the system can look like it’s improving while the outcome drifts the wrong way. So the paid media role changes but doesn’t disappear: less lever-pulling, more need to define what success means and how performance connects back to pipeline, margin, or customer quality.
Reporting needs to be more honest, not just more detailed
The measurement sessions were useful because they didn’t throw out the old metrics, but made clear those metrics can’t carry the whole story anymore. Clicks, rankings, and last-click attribution aren’t useless, but they’re increasingly incomplete when AI Overviews, zero-click search, and long buying cycles shape how people discover and validate brands.
Reporting often tries to create certainty where the journey doesn’t allow for it. A dashboard can show what happened, but not always why, or which earlier touchpoint gave someone the confidence to convert. That doesn’t mean giving up on measurement, but being clearer about confidence and what decision the data is meant to support.
For B2B, the journey’s usually long and messy: a LinkedIn post, a third-party article, a peer’s opinion, a branded search, conversion weeks later. No single platform report explains that cleanly, so marketers need a more honest picture, clearer about the job of each activity, since some content captures demand, some builds trust, and some converts.
Is ‘optimising for AI’ the next core focus?
The main thing I took from BrightonSEO wasn’t that every B2B brand now needs an ‘AI search strategy’; that feels too narrow and a bit too convenient. The bigger point is that discoverability is becoming more connected, and search is increasingly shaped by the full system around the brand: what it does, who it serves, what it can prove, where that proof appears, and whether all of that is consistent enough for people and machines to make sense of it.
So the question I’d take back into B2B planning is simple, even if the work behind it isn’t: if a buyer, a search engine, or an AI system is trying to work out whether we’re credible enough to recommend, have we given them enough clear, connected, trustworthy evidence to do that?
So is search even the right word for what’s happening now? Probably not on its own. It isn’t going away, but it’s becoming shorthand for something much bigger: how clearly a brand explains itself, how much proof sits around it, and whether people and machines find it easy to trust. The brands that get that right are probably the ones that become easier to find, easier to trust, and easier to choose.