There’s no shortage of information on how AI is influencing sales teams.

I’m having plenty of conversations about how small businesses can best power up their sales strategy with AI.

If salespeople are using AI — effectively or otherwise — is it much of a stretch to say buyers are doing the same?

Semrush’s 2026 research into B2B buying found that AI has helped 97% of buyers discover new vendors, shaped the vendor shortlist for 92%, and influenced the final decision for 83%. Separately, the same research found 69% of buyers use AI daily, and 95% at least weekly. (Source: Semrush — How AI tools shape the B2B buying process, July 2026)

This research will certainly ask questions of those businesses who view marketing as an expense, and those who use it mainly for lead generation.

It’s a live issue for the SMEs and enterprise sales teams I work with across Belfast and Northern Ireland — several are already asking whether their own content would survive an AI vendor search.

Several 2026 studies — including Muck Rack’s Generative Pulse report — have found that roughly 84% of what AI cites comes from outside a brand’s own website, not from Semrush’s research specifically, but from independent studies on where AI models actually source their answers. This suggests marketing’s job must shift from generating leads to generating content that AI finds for buyers before any contact with the seller is made.

AEO (Answer Engine Optimisation) has become an essential extension of SEO.

SEO helps your content get found and indexed, and AEO helps your expertise become part of the answer.

Good content should satisfy both parts of the optimization objective — continuing to help you get discovered, while also directly answering buyers’ questions, publishing original frameworks and evidence, demonstrating first-hand expertise, and making pages easy for AI systems to understand and cite.

Web content now needs to be structured so that AI tools can extract and cite it directly in their answers, in addition to still ranking well in traditional search.

This matters even more once you look at what happens after AI recommends a vendor. Semrush found that 75% of buyers trust AI vendor recommendations — but almost all of them verify before committing: 71% go on to visit the vendor’s website, 63% search for the company on Google, and 38% check reviews on G2 or similar platforms. Being mentioned by AI gets you noticed; what buyers find in the next few clicks decides whether that notice turns into anything.

There’s also a genuine opportunity here for smaller businesses without big marketing budgets: only 7% of buyers say brand recognition is why they notice a vendor in an AI response, while 53% say it’s because the vendor closely matches their specific use case. Precision beats familiarity.

PR agencies will earn their keep as earned, third-party coverage becomes more valuable than what you publish on your own site — and it might even be time to justify sponsoring industry awards and events, as independent media mentions gain value.

Your sales team needs marketing support more than ever

Practical steps for AEO (Answer Engine Optimisation)

Case studies
Get your case studies polished up and get them across LinkedIn, and where possible referenced by a third-party or trade publication. Earned, third-party coverage tends to get picked up and cited by AI more readily than content sitting only on your own website.

Transparent pricing
A challenge for many businesses where prices are available only on request. Pricing now needs to be visible, ideally using exact figures, or at least tiers/ranges, and where necessary showing security/compliance documentation, integration guides, and comparison pages.

FAQs
Use the exact, real language from your sales and discovery calls, and publish it as questions alongside direct answers — either as an FAQ page or as individual blog posts, depending on how often those questions come up.

Home-grown research
Data, surveys, or benchmarks your own company generates — not citing someone else’s study. Takes time and effort, but well worth it. (Marcus Sheridan was talking about a lot of this almost 10 years ago in They Ask, You Answer.)

Track AI citation visibility as a metric
Regularly check if your brand gets mentioned when someone asks ChatGPT, Perplexity, Gemini, or Copilot a relevant question. This can be done manually or with a dedicated monitoring tool. Otterly.AI tracks brand mentions and citations across AI platforms and reports a “share of AI voice” against competitors.

What next?
It’s clear there’s an AI-assisted shift happening for both sellers and buyers. It might be logical to double down on sales activity and look for competitive advantage at the front line — but it’s also worth evaluating your marketing strategy, making sure your content accurately reflects what you do while directly targeting what your buyer needs.

Your content might already be doing that for you — worth checking.

Having the confidence to talk openly about your most closely guarded secret (price) might be a bigger challenge, but if your “Price on Request” model is shutting you out of hundreds of live conversations, it’s worth a rethink.

Thanks for reading.

FAQs

Why do case studies matter for AEO?
Get your case studies polished and published across LinkedIn, and pursue third-party coverage rather than relying on your own site alone. AI engines are more likely to cite claims that appear in multiple independent places — a case study mentioned only on your own website carries less weight than the same result covered by a trade publication or shared by the client themselves. For example, a client testimonial sitting only on your site is one data point; the same story picked up by a trade publication, shared by the client on their own LinkedIn, and referenced in an industry roundup becomes three independent confirmations — and that’s the kind of corroboration AI models are trained to weight more heavily than a single self-published claim.

Why does pricing transparency help with AEO?
Publishing exact figures or ranges, rather than “contact us for pricing,” gives AI systems and buyers a concrete, quotable answer to one of the most common questions in any buying journey. A “Price on Request” model might protect a negotiating position, but it also means AI has nothing specific to cite when a buyer asks what something costs — so the answer goes to a competitor who did publish numbers. Even a range (“programmes typically start from X for a small team, scaling for enterprise engagements”) gives an AI system something concrete to work with, without committing to a fixed rate card.

How should FAQs be written for AEO?
Use the exact, real language from your own sales and discovery calls, and publish it as a question followed by a direct answer. Buyers and AI systems both respond better to the actual phrasing prospects use — not a polished marketing version of the question — because that’s what matches how the question gets typed into a search bar or asked of an AI assistant. If a prospect has asked “do you only do one-off training days or is there follow-up?” three times this month on discovery calls, that’s the FAQ to publish — word for word, not rephrased into “What does your engagement model look like?”

What is home-grown research and why does it matter for AEO?
Original data, surveys or benchmarks you generate yourself, rather than only citing other people’s studies, give AI engines something unique to cite back to you specifically. Citing someone else’s statistic makes you one of thousands of sources saying the same thing; publishing your own puts you in the sole position to be credited for it. Something as simple as “of the last 40 sales teams we’ve worked with in Northern Ireland, X% had no formal onboarding process” is a genuinely citable, ownable data point — and it doesn’t require an expensive research operation to produce, just a willingness to track and publish what you already see across your own client base.

How do you track whether AI platforms are citing your business?
Monitor brand mentions across ChatGPT, Perplexity, Gemini and Copilot, either manually by asking each platform relevant questions yourself, or with a dedicated tool like Otterly.AI, which reports a “share of AI voice” against named competitors over time. A simple manual check — asking each platform “who offers sales training and coaching in Belfast” once a month and noting whether you’re mentioned — costs nothing and still gives a useful early signal before investing in a paid monitoring tool.

Source: Semrush — How AI tools shape the B2B buying process (July 2026)