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Most of the conversation about AI and marketing jobs is useless. Not because the question does not matter. Of course it does. But because the two loudest voices in the room are both wrong.
On one side: the doomsayers who want you to believe your entire profession is about to be automated out of existence. On the other: the conference-circuit executives and ‘Champagne CMOs’ telling rooms full of people about their extraordinary AI transformations, their 35% productivity gains, their fully embedded workflows. The ones who have not logged into HubSpot in three years and genuinely believe Nano Banana is a small Japanese snack.
Both camps are doing you a disservice. And the second one is actively making things worse, because when the CFO hears those claims and asks why your team has not matched them, nobody wants to be the person explaining that the number was invented on a pay to play stage in London.
What the evidence actually shows
A Stanford study updated in December 2025 tracked early-career sales and marketing professionals aged 22 to 25. The findings were stark. AI has caused a net loss of around 20% of headcount in that cohort since early 2022.
And it’s not getting better.
We’ve all seen the headlines of a thousand jobs disappearing here, ten thousand jobs cut there. Even accounting for AI being used as an excuse for companies to eliminate roles, we can all feel it happening.
But the nuance that matters is that AI is not eating marketing from the top down. It is eating it from the bottom up. The displacement effect decreases with seniority. And a meaningful proportion of what is being called AI displacement is not about AI capability at all. It is organisations using a powerful narrative as cover for decisions they wanted to make anyway.
The real question is not whether you will lose your job
It is whether the version of your job you are doing right now will still exist in three years.
If your value comes from producing a defined volume of content, managing campaign execution, running standard reports, or coordinating assets and schedules: it is very likely that AI will do most of that job within two to three years. Some of it is already happening.
If your value comes from strategic judgment, creative vision, cross-functional influence, genuine customer relationships, or the ability to govern complex AI-assisted workflows: you are not going to be replaced. You are going to be more valuable. But only if you develop the fluency to operate in an AI-native environment.
The marketers who should actually be worried are not the ones whose roles are at risk. They are the ones who have already replaced themselves. The ones who use AI to avoid having opinions rather than to sharpen them.
There is a phrase in the report that I think is on point:
If you are using AI to avoid thinking, you have not adopted a powerful tool. You have just outsourced the part of your job that made you valuable.
What the report covers
We also get into the buyer side of this story.
94% of B2B buyers are now using large language models during their purchasing process. 83% define their requirements before they ever speak to sales. And 85% of the time, they ultimately purchase from a vendor on their Day One shortlist. A shortlist that was assembled with AI assistance, before you knew they were looking.
If you are not visible, credible, and clearly positioned in the places where AI-assisted research happens, you may never get a seat at the table at all. That is not a scare story. It is a description of what is already in motion.
The report also covers where AI genuinely earns its place in a B2B marketing workflow. The blank page problem. The draft versus the finished work distinction. The agentic shift and what narrative orchestration actually means. And a practical action sequence structured by timeframe, not vague advice.
We have not pulled punches with our opinions and we have not catastrophized either. We have tried to be straight with you about a situation that deserves clear thinking.
The best B2B marketers I know are not panicking. They are curious. They are retooling. They are paying attention.
That is all this report is asking you to do.
[DOWNLOAD: Will You Lose Your Marketing Job, or Is It Just Generative Hype? → Here]
Most of the conversation about AI and marketing jobs is useless. Not because the question does not matter. Of course it does. But because the two loudest voices in the room are both wrong.
On one side: the doomsayers who want you to believe your entire profession is about to be automated out of existence. On the other: the conference-circuit executives and ‘Champagne CMOs’ telling rooms full of people about their extraordinary AI transformations, their 35% productivity gains, their fully embedded workflows. The ones who have not logged into HubSpot in three years and genuinely believe Nano Banana is a small Japanese snack.
Both camps are doing you a disservice. And the second one is actively making things worse, because when the CFO hears those claims and asks why your team has not matched them, nobody wants to be the person explaining that the number was invented on a pay to play stage in London.
What the evidence actually shows
A Stanford study updated in December 2025 tracked early-career sales and marketing professionals aged 22 to 25. The findings were stark. AI has caused a net loss of around 20% of headcount in that cohort since early 2022.
And it’s not getting better.
We’ve all seen the headlines of a thousand jobs disappearing here, ten thousand jobs cut there. Even accounting for AI being used as an excuse for companies to eliminate roles, we can all feel it happening.
But the nuance that matters is that AI is not eating marketing from the top down. It is eating it from the bottom up. The displacement effect decreases with seniority. And a meaningful proportion of what is being called AI displacement is not about AI capability at all. It is organisations using a powerful narrative as cover for decisions they wanted to make anyway.
The real question is not whether you will lose your job
It is whether the version of your job you are doing right now will still exist in three years.
If your value comes from producing a defined volume of content, managing campaign execution, running standard reports, or coordinating assets and schedules: it is very likely that AI will do most of that job within two to three years. Some of it is already happening.
If your value comes from strategic judgment, creative vision, cross-functional influence, genuine customer relationships, or the ability to govern complex AI-assisted workflows: you are not going to be replaced. You are going to be more valuable. But only if you develop the fluency to operate in an AI-native environment.
The marketers who should actually be worried are not the ones whose roles are at risk. They are the ones who have already replaced themselves. The ones who use AI to avoid having opinions rather than to sharpen them.
There is a phrase in the report that I think is on point:
If you are using AI to avoid thinking, you have not adopted a powerful tool. You have just outsourced the part of your job that made you valuable.
What the report covers
We also get into the buyer side of this story.
94% of B2B buyers are now using large language models during their purchasing process. 83% define their requirements before they ever speak to sales. And 85% of the time, they ultimately purchase from a vendor on their Day One shortlist. A shortlist that was assembled with AI assistance, before you knew they were looking.
If you are not visible, credible, and clearly positioned in the places where AI-assisted research happens, you may never get a seat at the table at all. That is not a scare story. It is a description of what is already in motion.
The report also covers where AI genuinely earns its place in a B2B marketing workflow. The blank page problem. The draft versus the finished work distinction. The agentic shift and what narrative orchestration actually means. And a practical action sequence structured by timeframe, not vague advice.
We have not pulled punches with our opinions and we have not catastrophized either. We have tried to be straight with you about a situation that deserves clear thinking.
The best B2B marketers I know are not panicking. They are curious. They are retooling. They are paying attention.
That is all this report is asking you to do.
[DOWNLOAD: Will You Lose Your Marketing Job, or Is It Just Generative Hype? → Here]
Most of the conversation about AI and marketing jobs is useless. Not because the question does not matter. Of course it does. But because the two loudest voices in the room are both wrong.
On one side: the doomsayers who want you to believe your entire profession is about to be automated out of existence. On the other: the conference-circuit executives and ‘Champagne CMOs’ telling rooms full of people about their extraordinary AI transformations, their 35% productivity gains, their fully embedded workflows. The ones who have not logged into HubSpot in three years and genuinely believe Nano Banana is a small Japanese snack.
Both camps are doing you a disservice. And the second one is actively making things worse, because when the CFO hears those claims and asks why your team has not matched them, nobody wants to be the person explaining that the number was invented on a pay to play stage in London.
What the evidence actually shows
A Stanford study updated in December 2025 tracked early-career sales and marketing professionals aged 22 to 25. The findings were stark. AI has caused a net loss of around 20% of headcount in that cohort since early 2022.
And it’s not getting better.
We’ve all seen the headlines of a thousand jobs disappearing here, ten thousand jobs cut there. Even accounting for AI being used as an excuse for companies to eliminate roles, we can all feel it happening.
But the nuance that matters is that AI is not eating marketing from the top down. It is eating it from the bottom up. The displacement effect decreases with seniority. And a meaningful proportion of what is being called AI displacement is not about AI capability at all. It is organisations using a powerful narrative as cover for decisions they wanted to make anyway.
The real question is not whether you will lose your job
It is whether the version of your job you are doing right now will still exist in three years.
If your value comes from producing a defined volume of content, managing campaign execution, running standard reports, or coordinating assets and schedules: it is very likely that AI will do most of that job within two to three years. Some of it is already happening.
If your value comes from strategic judgment, creative vision, cross-functional influence, genuine customer relationships, or the ability to govern complex AI-assisted workflows: you are not going to be replaced. You are going to be more valuable. But only if you develop the fluency to operate in an AI-native environment.
The marketers who should actually be worried are not the ones whose roles are at risk. They are the ones who have already replaced themselves. The ones who use AI to avoid having opinions rather than to sharpen them.
There is a phrase in the report that I think is on point:
If you are using AI to avoid thinking, you have not adopted a powerful tool. You have just outsourced the part of your job that made you valuable.
What the report covers
We also get into the buyer side of this story.
94% of B2B buyers are now using large language models during their purchasing process. 83% define their requirements before they ever speak to sales. And 85% of the time, they ultimately purchase from a vendor on their Day One shortlist. A shortlist that was assembled with AI assistance, before you knew they were looking.
If you are not visible, credible, and clearly positioned in the places where AI-assisted research happens, you may never get a seat at the table at all. That is not a scare story. It is a description of what is already in motion.
The report also covers where AI genuinely earns its place in a B2B marketing workflow. The blank page problem. The draft versus the finished work distinction. The agentic shift and what narrative orchestration actually means. And a practical action sequence structured by timeframe, not vague advice.
We have not pulled punches with our opinions and we have not catastrophized either. We have tried to be straight with you about a situation that deserves clear thinking.
The best B2B marketers I know are not panicking. They are curious. They are retooling. They are paying attention.
That is all this report is asking you to do.
[DOWNLOAD: Will You Lose Your Marketing Job, or Is It Just Generative Hype? → Here]
London
Mar 25, 2026
Rich Fitzmaurice
Letters
Dear Rich,
I am under pressure from my CEO and CCO because they are increasingly obsessed with AI chatbots. Apparently the chatbots don't know much about our firm but can answer questions about our competitors. I am interim head of marketing and I'm feeling like I don't have long to address this before it harms my prospects for the gig full time.
I understand organic content is still valuable but how exactly do I get our firm and our products into ChatGPT or Claude?
Rebecca, Manchester
Dear Rebecca,
Your CEO and CCO have stumbled onto something increasingly real. To be fair to them, I think they are right, you need to treat this as a priority.
Prospective buyers are using AI tools to shortlist vendors before they ever land on your website. A CFO types "which platforms offer AI-powered forecasting" into Copilot. A procurement director asks ChatGPT "who are the main providers of X in the UK." None of them went to Google first (who would have said that just a year ago?!). And when the AI answered, it named specific brands. If yours wasn't one of them, you lost ground in a conversation you didn't know was happening.
The discipline you need is called AEO. Answer Engine Optimisation. It's what SEO was in 2008, which means the window to get ahead of your competitors is open right now, but it won't stay open forever. You can’t open LinkedIn or Instagram or any social media without someone talking about it or pitching a solution.
Here's what you actually do.
First, understand how AI decides what to say. Tools like ChatGPT were trained on web data up to a certain point. What they know about your company comes from that training: your content, your press mentions, your directory listings, third-party coverage. Retrieval-based tools like Perplexity pull live web data. Google's AI Overviews blend both. No single fix works across all of them. But the underlying principle is consistent. AI rewards clarity, consistency, and credibility.
Start with an audit. Open ChatGPT, Perplexity, and Claude. Ask the questions your buyers actually ask. "What are the best platforms for [your category]?" "Which providers work with [your target industry]?" "Tell me about [your brand name]." Note where you appear. Note where your competitors appear instead. Run fifteen to twenty prompts. The gaps become your priority list. This also gives you something concrete to take back to your CEO this week, which, given your situation, is not a small thing. It shows you are on it.
(Important Note: We see the need, so B2B Marketing United have decided to build our own ‘AI Search Scout Report’ tool to conduct this audit for free and get you started. We’ll release it soon so sign up to the newsletter on our website for updates.)
Then look at your own website. AI systems parse content differently from humans. They break pages into individual passages and evaluate each one independently. Clear headings, direct answers at the top of each section, and specific factual statements all increase the chance of being cited. A page that says "our platform processes two million transactions per day with 99.9% uptime" is far more citable than one that says "we offer industry-leading reliability." Specific beats vague. Every time. Go through your most important pages and make them legible to a machine. This means leading each section with a direct answer, adding FAQ sections that mirror the actual questions buyers ask, and replacing any claim that a journalist couldn't quote with one that they could.
Build your authority footprint outside your own site. Here's the thing most marketers miss. What others say about you matters at least as much as what you say about yourself. Often more. AI models weight sources by perceived credibility. Coverage in respected industry publications, bylines on high-authority sites, mentions from recognised experts: these all increase the probability that AI treats your brand as worth citing. One well-placed article in a credible trade publication does more for your AI visibility than ten posts on your own blog. I said it in our AEO how-to and I'll say it again here: PR is making a comeback, and this is the big reason why.
Fix your entity consistency. This is the unglamorous work that nobody wants to do and that most companies haven't done. Audit every place your brand appears online. Your website, your LinkedIn page, your Google Business Profile, your directory listings, your press mentions. Make sure your brand name, description, category, and key facts are identical everywhere. If your founding year, product description, or company category varies between sources, AI loses confidence in citing any of them. Content and Comms teams must be loving that all their hard work insisting on ‘core scripts’ and ‘factbooks’ are now more than justified and back in vogue.
Use the language your buyers use. AI categorises content using semantic relationships. If your website speaks in internal jargon and your buyers are searching in plain English, the connection AI needs to make between your brand and their queries simply won't be there. Write for their vocabulary, not yours.
The pressure you're under is real. But the good news is that fixing this is visible work. You can show your CEO a before and after. The audit alone demonstrates that you understand the problem and are taking action. The content and authority work demonstrates that you're addressing it. Most of your competitors haven't even started. That's your advantage, and your argument for the full-time role.
Move fast. Document what you do. Show the change. Get that job permanently!
Onwards!
Rich
For a fast read on the full AEO playbook, our how-to is here: How to use AEO to get your B2B brand into AI answers. And if you want to know exactly where you stand right now, the B2BMU AI Scout Report will audit your AI visibility for free just get in touch with the team via the website at www.b2bmarketing.com
Dear Rich,
I am under pressure from my CEO and CCO because they are increasingly obsessed with AI chatbots. Apparently the chatbots don't know much about our firm but can answer questions about our competitors. I am interim head of marketing and I'm feeling like I don't have long to address this before it harms my prospects for the gig full time.
I understand organic content is still valuable but how exactly do I get our firm and our products into ChatGPT or Claude?
Rebecca, Manchester
Dear Rebecca,
Your CEO and CCO have stumbled onto something increasingly real. To be fair to them, I think they are right, you need to treat this as a priority.
Prospective buyers are using AI tools to shortlist vendors before they ever land on your website. A CFO types "which platforms offer AI-powered forecasting" into Copilot. A procurement director asks ChatGPT "who are the main providers of X in the UK." None of them went to Google first (who would have said that just a year ago?!). And when the AI answered, it named specific brands. If yours wasn't one of them, you lost ground in a conversation you didn't know was happening.
The discipline you need is called AEO. Answer Engine Optimisation. It's what SEO was in 2008, which means the window to get ahead of your competitors is open right now, but it won't stay open forever. You can’t open LinkedIn or Instagram or any social media without someone talking about it or pitching a solution.
Here's what you actually do.
First, understand how AI decides what to say. Tools like ChatGPT were trained on web data up to a certain point. What they know about your company comes from that training: your content, your press mentions, your directory listings, third-party coverage. Retrieval-based tools like Perplexity pull live web data. Google's AI Overviews blend both. No single fix works across all of them. But the underlying principle is consistent. AI rewards clarity, consistency, and credibility.
Start with an audit. Open ChatGPT, Perplexity, and Claude. Ask the questions your buyers actually ask. "What are the best platforms for [your category]?" "Which providers work with [your target industry]?" "Tell me about [your brand name]." Note where you appear. Note where your competitors appear instead. Run fifteen to twenty prompts. The gaps become your priority list. This also gives you something concrete to take back to your CEO this week, which, given your situation, is not a small thing. It shows you are on it.
(Important Note: We see the need, so B2B Marketing United have decided to build our own ‘AI Search Scout Report’ tool to conduct this audit for free and get you started. We’ll release it soon so sign up to the newsletter on our website for updates.)
Then look at your own website. AI systems parse content differently from humans. They break pages into individual passages and evaluate each one independently. Clear headings, direct answers at the top of each section, and specific factual statements all increase the chance of being cited. A page that says "our platform processes two million transactions per day with 99.9% uptime" is far more citable than one that says "we offer industry-leading reliability." Specific beats vague. Every time. Go through your most important pages and make them legible to a machine. This means leading each section with a direct answer, adding FAQ sections that mirror the actual questions buyers ask, and replacing any claim that a journalist couldn't quote with one that they could.
Build your authority footprint outside your own site. Here's the thing most marketers miss. What others say about you matters at least as much as what you say about yourself. Often more. AI models weight sources by perceived credibility. Coverage in respected industry publications, bylines on high-authority sites, mentions from recognised experts: these all increase the probability that AI treats your brand as worth citing. One well-placed article in a credible trade publication does more for your AI visibility than ten posts on your own blog. I said it in our AEO how-to and I'll say it again here: PR is making a comeback, and this is the big reason why.
Fix your entity consistency. This is the unglamorous work that nobody wants to do and that most companies haven't done. Audit every place your brand appears online. Your website, your LinkedIn page, your Google Business Profile, your directory listings, your press mentions. Make sure your brand name, description, category, and key facts are identical everywhere. If your founding year, product description, or company category varies between sources, AI loses confidence in citing any of them. Content and Comms teams must be loving that all their hard work insisting on ‘core scripts’ and ‘factbooks’ are now more than justified and back in vogue.
Use the language your buyers use. AI categorises content using semantic relationships. If your website speaks in internal jargon and your buyers are searching in plain English, the connection AI needs to make between your brand and their queries simply won't be there. Write for their vocabulary, not yours.
The pressure you're under is real. But the good news is that fixing this is visible work. You can show your CEO a before and after. The audit alone demonstrates that you understand the problem and are taking action. The content and authority work demonstrates that you're addressing it. Most of your competitors haven't even started. That's your advantage, and your argument for the full-time role.
Move fast. Document what you do. Show the change. Get that job permanently!
Onwards!
Rich
For a fast read on the full AEO playbook, our how-to is here: How to use AEO to get your B2B brand into AI answers. And if you want to know exactly where you stand right now, the B2BMU AI Scout Report will audit your AI visibility for free just get in touch with the team via the website at www.b2bmarketing.com
Dear Rich,
I am under pressure from my CEO and CCO because they are increasingly obsessed with AI chatbots. Apparently the chatbots don't know much about our firm but can answer questions about our competitors. I am interim head of marketing and I'm feeling like I don't have long to address this before it harms my prospects for the gig full time.
I understand organic content is still valuable but how exactly do I get our firm and our products into ChatGPT or Claude?
Rebecca, Manchester
Dear Rebecca,
Your CEO and CCO have stumbled onto something increasingly real. To be fair to them, I think they are right, you need to treat this as a priority.
Prospective buyers are using AI tools to shortlist vendors before they ever land on your website. A CFO types "which platforms offer AI-powered forecasting" into Copilot. A procurement director asks ChatGPT "who are the main providers of X in the UK." None of them went to Google first (who would have said that just a year ago?!). And when the AI answered, it named specific brands. If yours wasn't one of them, you lost ground in a conversation you didn't know was happening.
The discipline you need is called AEO. Answer Engine Optimisation. It's what SEO was in 2008, which means the window to get ahead of your competitors is open right now, but it won't stay open forever. You can’t open LinkedIn or Instagram or any social media without someone talking about it or pitching a solution.
Here's what you actually do.
First, understand how AI decides what to say. Tools like ChatGPT were trained on web data up to a certain point. What they know about your company comes from that training: your content, your press mentions, your directory listings, third-party coverage. Retrieval-based tools like Perplexity pull live web data. Google's AI Overviews blend both. No single fix works across all of them. But the underlying principle is consistent. AI rewards clarity, consistency, and credibility.
Start with an audit. Open ChatGPT, Perplexity, and Claude. Ask the questions your buyers actually ask. "What are the best platforms for [your category]?" "Which providers work with [your target industry]?" "Tell me about [your brand name]." Note where you appear. Note where your competitors appear instead. Run fifteen to twenty prompts. The gaps become your priority list. This also gives you something concrete to take back to your CEO this week, which, given your situation, is not a small thing. It shows you are on it.
(Important Note: We see the need, so B2B Marketing United have decided to build our own ‘AI Search Scout Report’ tool to conduct this audit for free and get you started. We’ll release it soon so sign up to the newsletter on our website for updates.)
Then look at your own website. AI systems parse content differently from humans. They break pages into individual passages and evaluate each one independently. Clear headings, direct answers at the top of each section, and specific factual statements all increase the chance of being cited. A page that says "our platform processes two million transactions per day with 99.9% uptime" is far more citable than one that says "we offer industry-leading reliability." Specific beats vague. Every time. Go through your most important pages and make them legible to a machine. This means leading each section with a direct answer, adding FAQ sections that mirror the actual questions buyers ask, and replacing any claim that a journalist couldn't quote with one that they could.
Build your authority footprint outside your own site. Here's the thing most marketers miss. What others say about you matters at least as much as what you say about yourself. Often more. AI models weight sources by perceived credibility. Coverage in respected industry publications, bylines on high-authority sites, mentions from recognised experts: these all increase the probability that AI treats your brand as worth citing. One well-placed article in a credible trade publication does more for your AI visibility than ten posts on your own blog. I said it in our AEO how-to and I'll say it again here: PR is making a comeback, and this is the big reason why.
Fix your entity consistency. This is the unglamorous work that nobody wants to do and that most companies haven't done. Audit every place your brand appears online. Your website, your LinkedIn page, your Google Business Profile, your directory listings, your press mentions. Make sure your brand name, description, category, and key facts are identical everywhere. If your founding year, product description, or company category varies between sources, AI loses confidence in citing any of them. Content and Comms teams must be loving that all their hard work insisting on ‘core scripts’ and ‘factbooks’ are now more than justified and back in vogue.
Use the language your buyers use. AI categorises content using semantic relationships. If your website speaks in internal jargon and your buyers are searching in plain English, the connection AI needs to make between your brand and their queries simply won't be there. Write for their vocabulary, not yours.
The pressure you're under is real. But the good news is that fixing this is visible work. You can show your CEO a before and after. The audit alone demonstrates that you understand the problem and are taking action. The content and authority work demonstrates that you're addressing it. Most of your competitors haven't even started. That's your advantage, and your argument for the full-time role.
Move fast. Document what you do. Show the change. Get that job permanently!
Onwards!
Rich
For a fast read on the full AEO playbook, our how-to is here: How to use AEO to get your B2B brand into AI answers. And if you want to know exactly where you stand right now, the B2BMU AI Scout Report will audit your AI visibility for free just get in touch with the team via the website at www.b2bmarketing.com
Content
Mar 23, 2026
Content
How to's
We can all sense that something has changed in how buyers conduct their research. But most B2B marketers have not caught up with it yet.
A CFO opens Copilot and types: "Which accounting platforms offer AI-powered forecasting?" A marketing director asks ChatGPT: "What are the best agencies for B2B lead generation?" A Head of IT asks Claude: "What project management software works best for a team of fifty?"
None of them went to Google first. And when the AI answered, it named specific brands. Yours may not have been one of them.
This is the problem that Answer Engine Optimisation (AEO) exists to solve.
What AEO actually is
Answer Engine Optimisation is the practice of structuring your content, your brand presence, and your technical foundations so that AI-powered platforms cite and recommend you when buyers ask questions relevant to your business.
Just as SEO emerged to help brands get found in search engines, AEO has emerged to help brands get found in AI systems. It does not replace SEO. It extends it for an era where the answer, not the link, is the product.
When ChatGPT or Perplexity generates a response to a buyer question, it is not serving a list of links. It is synthesising an answer from sources it considers credible and relevant. Our job, as B2B marketers, is to be one of those sources.
Why this matters right now
Gartner projected that traditional search volume would drop 25% in 2026 as users shift to AI assistants. ChatGPT alone has over 800 million weekly active users. Around 60% of Google searches now end without a single click to a website.
The discovery layer is moving. Buyers are increasingly getting their answers inside the AI response itself, without ever visiting a vendor’s site.
That matters for two reasons beyond the obvious traffic one.
First, the intent behind AI queries is really high. When someone asks an AI for a recommendation, they are past the browsing phase. They want an answer they can act on. AI-referred traffic converts at higher rates than organic search precisely because the AI has already filtered and, implicitly, endorsed.
Second, buyers trust what AI tells them. Probably too much if you've ever had n argument with an LLM (I certainly have!). Research from Capgemini found that 73% of consumers globally trust content created by generative AI. When an AI says “I’d recommend Brand X for this use case”, that carries weight. It lands like expert advice, not an advert.
The brands that build AEO presence now will be the defaults AI recommends for years. Think of SEO in 2008. The companies that invested early still dominate today. The same compounding effect is available in AEO, but only for those who move while most of their competitors are not paying attention.
How AI answer engines decide what to cite
Before you can optimise for AI, you need to understand how it works. It is meaningfully different from traditional search.
Large language models like ChatGPT are trained on vast amounts of web data. What they know about your brand comes from that training: your content, mentions in publications, reviews, directory listings, third-party coverage. When a user asks a question, the model synthesises from everything it has absorbed, weighting sources it considers authoritative.
Retrieval-based systems like Perplexity work differently. They pull real-time information from the web when generating answers, making current content and domain authority more directly relevant.
Google’s AI Overviews blend both approaches, drawing on traditional search signals alongside AI synthesis.
The practical implication is that no single fix works across all platforms (oh, if only it was that easy). A robust AEO strategy has to account for all three models. But the underlying principles are consistent: AI rewards clarity, consistency, and credibility.
The five things AEO actually optimises
Content structure. AI systems parse content differently from humans. They break pages into individual passages and evaluate each one independently. Clear headings, direct answers at the top of each section, factual statements with specific numbers, and Q&A formatting all increase the likelihood of being cited. A page that states “our platform processes two million transactions per day with 99.9% uptime” is far more citable than one that says “we offer industry-leading reliability.” Specific beats vague, always.
Entity recognition. AI needs to understand what your brand is, which category it sits in, and how it relates to other things in its world. This means consistent naming across every platform you appear on, proper schema markup on your website, and presence on the platforms that define entities in AI systems: your Google Knowledge Graph entry, industry directories, authoritative databases. If AI cannot confidently place your brand in a category, it will not confidently recommend you.
Source authority. LLMs weight sources by perceived credibility. Coverage in respected industry publications, thought leadership on high-authority sites, mentions from recognised experts: these all increase the probability that AI treats your content as worth citing. What others say about you matters at least as much as what you say about yourself. Often more. This is why I think PR will make a comeback.
Factual consistency. AI cross-references information across sources. If your founding date, revenue figure, or product description varies between your website, your LinkedIn, your press mentions, and your directory listings, AI loses confidence in citing any of them. Inconsistency reads as unreliability. Fixing it is unglamorous work. It matters enormously. For us B2B marketers, those 'fact books' and 'core scripts' will be coming back in vogue.
Semantic alignment. AI categorises content using semantic relationships. Using the terminology, frameworks, and concepts your industry actually uses, and doing so naturally within authoritative content, strengthens the connection between your brand and the queries you want to own. Write for the buyer’s language, not your internal vocabulary.
How to get started
Step one: audit what AI currently says about you.
Open ChatGPT, Perplexity, and Claude. Ask the questions your buyers actually ask. "What are the best platforms for [your category]?" "Which [your service type] providers work with [your target industry]?" "Tell me about [your brand name]."
Note where you appear. Note how accurately you are described. Note which competitors appear instead of you. This is your baseline. Do it across at least fifteen to twenty prompts that represent your real buyer questions. The gaps you find become your content and authority priorities.
Step two: map your target queries.
Build a list of twenty to thirty questions your ideal customers are likely to ask an AI assistant. Include category queries ("best X software for Y"), comparison queries ("X versus Y versus Z"), and recommendation queries ("which X should I use for this use case"). This is your AEO query universe: the questions you need to own.
Step three: restructure your existing content.
You do not necessarily need to create new content. You need to make what you have more legible to AI systems. Start with your most important pages. Lead each section with a direct answer. Add FAQ sections that use the exact language from your target query list. Replace vague claims with specific, citable statements. Use clear heading hierarchies. Make every section able to stand alone as a passage.
Step four: build your authority footprint.
Identify where AI systems go to assess credibility in your category. Industry publications. Analyst reports. Review platforms. Expert directories. Community platforms that AI crawls: LinkedIn, Reddit, relevant industry forums. Pursue presence on those consistently. Not volume. Consistency and quality. One well-placed byline in a credible industry publication does more for AEO than ten posts on your own blog.
Step five: fix your entity consistency.
Audit every place your brand appears online. Your website, your Google Business Profile, your LinkedIn company page, your directory listings, your press mentions. Make sure your brand name, description, category, and key facts are identical everywhere. This is the kind of work that nobody wants to do but everybody benefits from.
Step six: measure and iterate.
Start tracking how your AI citation rate changes over time. Run your target query list monthly across the main platforms and record where you appear. Track whether AI referral traffic is showing up in your analytics. This will not be perfect attribution. It does not need to be. You are looking for directional signals: more citations, more accurate descriptions, more queries where you feature.
What good AEO looks like in practice
A page that states "our platform processes two million transactions per day with 99.9% uptime" is far more citable than one that says "we offer industry-leading reliability."
A FAQ section that asks "which B2B marketing platforms are best for companies with under fifty employees?" and answers it directly is far more useful to an AI system than a generic features page.
A founder with a consistent, expert-level presence in trade publications is far more likely to have their brand cited than one who only publishes on their own site.
These are not complicated ideas. But most B2B brands are not doing them systematically, yet! Which is the opportunity!
The honest caveat
AEO is not a one-time project. AI models update continuously. What works today may need adjusting in six months. The platforms themselves are evolving. Perplexity’s citation logic is not identical to ChatGPT’s, which is not identical to Google’s AI Overviews.
As marketers, we must build the habit. The brands that treat AEO as an ongoing discipline rather than a box to tick are the ones that will compound advantage over time.
Most companies have not even started yet. That window will not stay open indefinitely.
Want help assessing your current AI visibility? It's something we actually specialize in. Get in touch via our contact us.
We can all sense that something has changed in how buyers conduct their research. But most B2B marketers have not caught up with it yet.
A CFO opens Copilot and types: "Which accounting platforms offer AI-powered forecasting?" A marketing director asks ChatGPT: "What are the best agencies for B2B lead generation?" A Head of IT asks Claude: "What project management software works best for a team of fifty?"
None of them went to Google first. And when the AI answered, it named specific brands. Yours may not have been one of them.
This is the problem that Answer Engine Optimisation (AEO) exists to solve.
What AEO actually is
Answer Engine Optimisation is the practice of structuring your content, your brand presence, and your technical foundations so that AI-powered platforms cite and recommend you when buyers ask questions relevant to your business.
Just as SEO emerged to help brands get found in search engines, AEO has emerged to help brands get found in AI systems. It does not replace SEO. It extends it for an era where the answer, not the link, is the product.
When ChatGPT or Perplexity generates a response to a buyer question, it is not serving a list of links. It is synthesising an answer from sources it considers credible and relevant. Our job, as B2B marketers, is to be one of those sources.
Why this matters right now
Gartner projected that traditional search volume would drop 25% in 2026 as users shift to AI assistants. ChatGPT alone has over 800 million weekly active users. Around 60% of Google searches now end without a single click to a website.
The discovery layer is moving. Buyers are increasingly getting their answers inside the AI response itself, without ever visiting a vendor’s site.
That matters for two reasons beyond the obvious traffic one.
First, the intent behind AI queries is really high. When someone asks an AI for a recommendation, they are past the browsing phase. They want an answer they can act on. AI-referred traffic converts at higher rates than organic search precisely because the AI has already filtered and, implicitly, endorsed.
Second, buyers trust what AI tells them. Probably too much if you've ever had n argument with an LLM (I certainly have!). Research from Capgemini found that 73% of consumers globally trust content created by generative AI. When an AI says “I’d recommend Brand X for this use case”, that carries weight. It lands like expert advice, not an advert.
The brands that build AEO presence now will be the defaults AI recommends for years. Think of SEO in 2008. The companies that invested early still dominate today. The same compounding effect is available in AEO, but only for those who move while most of their competitors are not paying attention.
How AI answer engines decide what to cite
Before you can optimise for AI, you need to understand how it works. It is meaningfully different from traditional search.
Large language models like ChatGPT are trained on vast amounts of web data. What they know about your brand comes from that training: your content, mentions in publications, reviews, directory listings, third-party coverage. When a user asks a question, the model synthesises from everything it has absorbed, weighting sources it considers authoritative.
Retrieval-based systems like Perplexity work differently. They pull real-time information from the web when generating answers, making current content and domain authority more directly relevant.
Google’s AI Overviews blend both approaches, drawing on traditional search signals alongside AI synthesis.
The practical implication is that no single fix works across all platforms (oh, if only it was that easy). A robust AEO strategy has to account for all three models. But the underlying principles are consistent: AI rewards clarity, consistency, and credibility.
The five things AEO actually optimises
Content structure. AI systems parse content differently from humans. They break pages into individual passages and evaluate each one independently. Clear headings, direct answers at the top of each section, factual statements with specific numbers, and Q&A formatting all increase the likelihood of being cited. A page that states “our platform processes two million transactions per day with 99.9% uptime” is far more citable than one that says “we offer industry-leading reliability.” Specific beats vague, always.
Entity recognition. AI needs to understand what your brand is, which category it sits in, and how it relates to other things in its world. This means consistent naming across every platform you appear on, proper schema markup on your website, and presence on the platforms that define entities in AI systems: your Google Knowledge Graph entry, industry directories, authoritative databases. If AI cannot confidently place your brand in a category, it will not confidently recommend you.
Source authority. LLMs weight sources by perceived credibility. Coverage in respected industry publications, thought leadership on high-authority sites, mentions from recognised experts: these all increase the probability that AI treats your content as worth citing. What others say about you matters at least as much as what you say about yourself. Often more. This is why I think PR will make a comeback.
Factual consistency. AI cross-references information across sources. If your founding date, revenue figure, or product description varies between your website, your LinkedIn, your press mentions, and your directory listings, AI loses confidence in citing any of them. Inconsistency reads as unreliability. Fixing it is unglamorous work. It matters enormously. For us B2B marketers, those 'fact books' and 'core scripts' will be coming back in vogue.
Semantic alignment. AI categorises content using semantic relationships. Using the terminology, frameworks, and concepts your industry actually uses, and doing so naturally within authoritative content, strengthens the connection between your brand and the queries you want to own. Write for the buyer’s language, not your internal vocabulary.
How to get started
Step one: audit what AI currently says about you.
Open ChatGPT, Perplexity, and Claude. Ask the questions your buyers actually ask. "What are the best platforms for [your category]?" "Which [your service type] providers work with [your target industry]?" "Tell me about [your brand name]."
Note where you appear. Note how accurately you are described. Note which competitors appear instead of you. This is your baseline. Do it across at least fifteen to twenty prompts that represent your real buyer questions. The gaps you find become your content and authority priorities.
Step two: map your target queries.
Build a list of twenty to thirty questions your ideal customers are likely to ask an AI assistant. Include category queries ("best X software for Y"), comparison queries ("X versus Y versus Z"), and recommendation queries ("which X should I use for this use case"). This is your AEO query universe: the questions you need to own.
Step three: restructure your existing content.
You do not necessarily need to create new content. You need to make what you have more legible to AI systems. Start with your most important pages. Lead each section with a direct answer. Add FAQ sections that use the exact language from your target query list. Replace vague claims with specific, citable statements. Use clear heading hierarchies. Make every section able to stand alone as a passage.
Step four: build your authority footprint.
Identify where AI systems go to assess credibility in your category. Industry publications. Analyst reports. Review platforms. Expert directories. Community platforms that AI crawls: LinkedIn, Reddit, relevant industry forums. Pursue presence on those consistently. Not volume. Consistency and quality. One well-placed byline in a credible industry publication does more for AEO than ten posts on your own blog.
Step five: fix your entity consistency.
Audit every place your brand appears online. Your website, your Google Business Profile, your LinkedIn company page, your directory listings, your press mentions. Make sure your brand name, description, category, and key facts are identical everywhere. This is the kind of work that nobody wants to do but everybody benefits from.
Step six: measure and iterate.
Start tracking how your AI citation rate changes over time. Run your target query list monthly across the main platforms and record where you appear. Track whether AI referral traffic is showing up in your analytics. This will not be perfect attribution. It does not need to be. You are looking for directional signals: more citations, more accurate descriptions, more queries where you feature.
What good AEO looks like in practice
A page that states "our platform processes two million transactions per day with 99.9% uptime" is far more citable than one that says "we offer industry-leading reliability."
A FAQ section that asks "which B2B marketing platforms are best for companies with under fifty employees?" and answers it directly is far more useful to an AI system than a generic features page.
A founder with a consistent, expert-level presence in trade publications is far more likely to have their brand cited than one who only publishes on their own site.
These are not complicated ideas. But most B2B brands are not doing them systematically, yet! Which is the opportunity!
The honest caveat
AEO is not a one-time project. AI models update continuously. What works today may need adjusting in six months. The platforms themselves are evolving. Perplexity’s citation logic is not identical to ChatGPT’s, which is not identical to Google’s AI Overviews.
As marketers, we must build the habit. The brands that treat AEO as an ongoing discipline rather than a box to tick are the ones that will compound advantage over time.
Most companies have not even started yet. That window will not stay open indefinitely.
Want help assessing your current AI visibility? It's something we actually specialize in. Get in touch via our contact us.
We can all sense that something has changed in how buyers conduct their research. But most B2B marketers have not caught up with it yet.
A CFO opens Copilot and types: "Which accounting platforms offer AI-powered forecasting?" A marketing director asks ChatGPT: "What are the best agencies for B2B lead generation?" A Head of IT asks Claude: "What project management software works best for a team of fifty?"
None of them went to Google first. And when the AI answered, it named specific brands. Yours may not have been one of them.
This is the problem that Answer Engine Optimisation (AEO) exists to solve.
What AEO actually is
Answer Engine Optimisation is the practice of structuring your content, your brand presence, and your technical foundations so that AI-powered platforms cite and recommend you when buyers ask questions relevant to your business.
Just as SEO emerged to help brands get found in search engines, AEO has emerged to help brands get found in AI systems. It does not replace SEO. It extends it for an era where the answer, not the link, is the product.
When ChatGPT or Perplexity generates a response to a buyer question, it is not serving a list of links. It is synthesising an answer from sources it considers credible and relevant. Our job, as B2B marketers, is to be one of those sources.
Why this matters right now
Gartner projected that traditional search volume would drop 25% in 2026 as users shift to AI assistants. ChatGPT alone has over 800 million weekly active users. Around 60% of Google searches now end without a single click to a website.
The discovery layer is moving. Buyers are increasingly getting their answers inside the AI response itself, without ever visiting a vendor’s site.
That matters for two reasons beyond the obvious traffic one.
First, the intent behind AI queries is really high. When someone asks an AI for a recommendation, they are past the browsing phase. They want an answer they can act on. AI-referred traffic converts at higher rates than organic search precisely because the AI has already filtered and, implicitly, endorsed.
Second, buyers trust what AI tells them. Probably too much if you've ever had n argument with an LLM (I certainly have!). Research from Capgemini found that 73% of consumers globally trust content created by generative AI. When an AI says “I’d recommend Brand X for this use case”, that carries weight. It lands like expert advice, not an advert.
The brands that build AEO presence now will be the defaults AI recommends for years. Think of SEO in 2008. The companies that invested early still dominate today. The same compounding effect is available in AEO, but only for those who move while most of their competitors are not paying attention.
How AI answer engines decide what to cite
Before you can optimise for AI, you need to understand how it works. It is meaningfully different from traditional search.
Large language models like ChatGPT are trained on vast amounts of web data. What they know about your brand comes from that training: your content, mentions in publications, reviews, directory listings, third-party coverage. When a user asks a question, the model synthesises from everything it has absorbed, weighting sources it considers authoritative.
Retrieval-based systems like Perplexity work differently. They pull real-time information from the web when generating answers, making current content and domain authority more directly relevant.
Google’s AI Overviews blend both approaches, drawing on traditional search signals alongside AI synthesis.
The practical implication is that no single fix works across all platforms (oh, if only it was that easy). A robust AEO strategy has to account for all three models. But the underlying principles are consistent: AI rewards clarity, consistency, and credibility.
The five things AEO actually optimises
Content structure. AI systems parse content differently from humans. They break pages into individual passages and evaluate each one independently. Clear headings, direct answers at the top of each section, factual statements with specific numbers, and Q&A formatting all increase the likelihood of being cited. A page that states “our platform processes two million transactions per day with 99.9% uptime” is far more citable than one that says “we offer industry-leading reliability.” Specific beats vague, always.
Entity recognition. AI needs to understand what your brand is, which category it sits in, and how it relates to other things in its world. This means consistent naming across every platform you appear on, proper schema markup on your website, and presence on the platforms that define entities in AI systems: your Google Knowledge Graph entry, industry directories, authoritative databases. If AI cannot confidently place your brand in a category, it will not confidently recommend you.
Source authority. LLMs weight sources by perceived credibility. Coverage in respected industry publications, thought leadership on high-authority sites, mentions from recognised experts: these all increase the probability that AI treats your content as worth citing. What others say about you matters at least as much as what you say about yourself. Often more. This is why I think PR will make a comeback.
Factual consistency. AI cross-references information across sources. If your founding date, revenue figure, or product description varies between your website, your LinkedIn, your press mentions, and your directory listings, AI loses confidence in citing any of them. Inconsistency reads as unreliability. Fixing it is unglamorous work. It matters enormously. For us B2B marketers, those 'fact books' and 'core scripts' will be coming back in vogue.
Semantic alignment. AI categorises content using semantic relationships. Using the terminology, frameworks, and concepts your industry actually uses, and doing so naturally within authoritative content, strengthens the connection between your brand and the queries you want to own. Write for the buyer’s language, not your internal vocabulary.
How to get started
Step one: audit what AI currently says about you.
Open ChatGPT, Perplexity, and Claude. Ask the questions your buyers actually ask. "What are the best platforms for [your category]?" "Which [your service type] providers work with [your target industry]?" "Tell me about [your brand name]."
Note where you appear. Note how accurately you are described. Note which competitors appear instead of you. This is your baseline. Do it across at least fifteen to twenty prompts that represent your real buyer questions. The gaps you find become your content and authority priorities.
Step two: map your target queries.
Build a list of twenty to thirty questions your ideal customers are likely to ask an AI assistant. Include category queries ("best X software for Y"), comparison queries ("X versus Y versus Z"), and recommendation queries ("which X should I use for this use case"). This is your AEO query universe: the questions you need to own.
Step three: restructure your existing content.
You do not necessarily need to create new content. You need to make what you have more legible to AI systems. Start with your most important pages. Lead each section with a direct answer. Add FAQ sections that use the exact language from your target query list. Replace vague claims with specific, citable statements. Use clear heading hierarchies. Make every section able to stand alone as a passage.
Step four: build your authority footprint.
Identify where AI systems go to assess credibility in your category. Industry publications. Analyst reports. Review platforms. Expert directories. Community platforms that AI crawls: LinkedIn, Reddit, relevant industry forums. Pursue presence on those consistently. Not volume. Consistency and quality. One well-placed byline in a credible industry publication does more for AEO than ten posts on your own blog.
Step five: fix your entity consistency.
Audit every place your brand appears online. Your website, your Google Business Profile, your LinkedIn company page, your directory listings, your press mentions. Make sure your brand name, description, category, and key facts are identical everywhere. This is the kind of work that nobody wants to do but everybody benefits from.
Step six: measure and iterate.
Start tracking how your AI citation rate changes over time. Run your target query list monthly across the main platforms and record where you appear. Track whether AI referral traffic is showing up in your analytics. This will not be perfect attribution. It does not need to be. You are looking for directional signals: more citations, more accurate descriptions, more queries where you feature.
What good AEO looks like in practice
A page that states "our platform processes two million transactions per day with 99.9% uptime" is far more citable than one that says "we offer industry-leading reliability."
A FAQ section that asks "which B2B marketing platforms are best for companies with under fifty employees?" and answers it directly is far more useful to an AI system than a generic features page.
A founder with a consistent, expert-level presence in trade publications is far more likely to have their brand cited than one who only publishes on their own site.
These are not complicated ideas. But most B2B brands are not doing them systematically, yet! Which is the opportunity!
The honest caveat
AEO is not a one-time project. AI models update continuously. What works today may need adjusting in six months. The platforms themselves are evolving. Perplexity’s citation logic is not identical to ChatGPT’s, which is not identical to Google’s AI Overviews.
As marketers, we must build the habit. The brands that treat AEO as an ongoing discipline rather than a box to tick are the ones that will compound advantage over time.
Most companies have not even started yet. That window will not stay open indefinitely.
Want help assessing your current AI visibility? It's something we actually specialize in. Get in touch via our contact us.
Content
Mar 13, 2026
Content
