Straight answers about AI marketing for B2B

What is answer engine optimisation?

Answer engine optimisation, or AEO, is the practice of getting a brand named and cited inside AI-generated answers — ChatGPT, Perplexity, Google AI Overviews — rather than only ranking in a list of links. It matters because 51% of B2B software buyers now begin vendor research inside an AI chatbot.

Source · Omnibound, 2026

How is AEO different from SEO?

SEO competes for a position in a list of results. AEO competes to be the source an AI quotes when it answers a question. SEO rewards pages that rank; AEO rewards content structured for extraction — clear definitions, question-shaped headings, comparison tables and consistent citation across the web.

What is GEO, and is it the same as AEO?

Generative engine optimisation (GEO) and answer engine optimisation (AEO) describe the same practice: getting a brand cited inside AI-generated answers rather than only ranked in a list of links. The terms are used interchangeably. Some teams reserve GEO for generative results and AEO for direct-answer boxes.

How do I get my brand mentioned in ChatGPT?

Publish clear, extractable answers to the questions your buyers ask, get your brand named alongside your category on sites the models already trust, and keep the facts about you consistent everywhere. Models cite what they see repeated across independent sources, not what your homepage claims.

Why is my B2B brand invisible in AI answers?

Usually because your content is written to persuade rather than to be extracted, and because your brand is not mentioned consistently alongside your category elsewhere on the web. Language models form preferences from patterns across sources, so a brand that appears in one place rarely gets cited.

Is AI-generated marketing content bad for SEO?

Not inherently. Search engines penalise unhelpful content, not content produced with AI. The failure mode is publishing volume nobody checked — generic, unsourced and indistinguishable from competitors. Content that carries real expertise and evidence performs whether a person or a model drafted it.

What does an AI marketing department actually do?

The same disciplines as a traditional one — visibility, demand, creative, operations — with AI carrying the volume and senior marketers making the decisions. In practice that means more output per person, faster iteration, and measurement that would be impractical by hand.

Can AI replace a marketing team?

No, and treating it that way is how brands end up sounding identical. AI multiplies the reach of people who already know the market. It has no judgement about positioning, no relationship with your buyers, and no accountability. The work still needs marketers; it needs fewer of them doing repetitive tasks.

Can AI handle design, social media and paid media for B2B?

It can carry the volume in all three — variations on a design system, first drafts of social copy, bid and audience adjustments. It cannot decide what the brand should look like, what is worth saying, or when a campaign is quietly wasting budget. Those stay human.

What is the difference between an AI marketing department and an agency?

An agency advises and bills for time. An embedded AI marketing department operates the work and is measured on pipeline. The practical test: ask who will be running the system in ninety days, and whether anyone’s name is attached to its number.

How much does AI marketing cost for a B2B company?

It depends on how much of the department you need, so serious providers scope after a conversation rather than publishing a price list. A useful benchmark: compare any quote to one senior in-house marketing hire, fully loaded — that person takes about three months to recruit and covers a single discipline.

How long before AI marketing shows results?

First systems live within thirty days, real numbers to optimise against by sixty, and compounding visibility by ninety. Pipeline effects follow your sales cycle: a business with a six-month cycle should expect leading indicators first and closed revenue later.

How do you measure whether AI marketing is working?

Against pipeline, not impressions. The leading indicators are share of AI answers you appear in, branded search volume, and qualified meetings booked. The lagging one is revenue influenced. If a programme cannot be traced to one of those, it should not be running.

Should we outsource marketing or hire in-house?

Hire in-house for the things that compound with company knowledge — positioning, relationships, product marketing. Bring in outside help for capability you do not have yet and cannot recruit quickly. The best arrangements are temporary by design: outside help builds it, your team runs it.

Should we build marketing tools in-house or buy them?

Buy anything where your requirements match the market’s. Build where your advantage is specific — your buying cycle, your data model, the thing your company knows that competitors do not. Off-the-shelf software averages that advantage away, because it is sold to your competitors too.

What is marketing automation, and where should we start?

Marketing automation is having software perform repeatable marketing work without a person doing it each time. Start by writing down every repeating process with the hours it consumes, then automate the most expensive ones. Most teams find a day a week within their first process map.

How do we govern AI use in marketing?

Write down what is automated, who owns each system, what a human must approve before it ships, and where the audit trail lives. Forrester expects more than $10 billion of enterprise value to be lost in 2026 to ungoverned generative AI, and nearly all of it traces back to those four questions being unanswered.

Source · Forrester, 2026