Editorial note: Examples on this page are illustrative unless a company, study or source is specifically named. The aim is to show realistic workflows without presenting invented scenarios as case studies.
Where AI is genuinely useful right now
- Content drafting at volume. First-pass social captions, ad variants, and email copy, produced far faster than manual writing.
- Ad targeting and bidding. Optimising audience segments and bid strategies using patterns a person couldn't track manually.
- Campaign analysis. Summarising performance data across channels into a readable report.
- SEO research. Identifying keyword gaps and content opportunities faster than manual research.
Illustrative scenario: brands increasingly use AI to generate dozens of ad copy variants for A/B testing, letting real audience data — not guesswork — decide which message performs best.
Where to be careful
- Generic AI copy is easy to spot — and increasingly penalised. Search engines are getting better at identifying low-effort, mass-produced AI content; it can hurt rankings rather than help them.
- Brand voice erosion. Unedited AI drafts tend to converge on the same tone — a human editorial pass keeps your brand distinct.
- Advertising disclosure rules. AI-generated testimonials, reviews, or influencer content still need to comply with FTC (US) and ASA (UK) disclosure requirements.
A useful test: if you'd be embarrassed to tell a customer a specific piece of content was written entirely by AI with no edits, it needs another pass before it goes out.
Getting started: Use AI for the first draft and the tedious variants, like A/B test copy or format adaptation, but keep a human editorial pass before anything ships — that's the difference between AI-assisted and AI-generic content.
A simple workflow marketing teams actually use
- Brief the AI tightly. Feed it your brand voice guide, target audience, and 2-3 examples of copy you like — vague prompts produce generic output.
- Generate 5-10 variants, not one. AI is cheap to iterate with; pick the best elements from several drafts rather than accepting the first result.
- Edit for specificity. Replace generic claims ("industry-leading", "cutting-edge") with real numbers, names, or details only your brand would know.
- Fact-check before publishing. AI can invent statistics or misattribute quotes — verify anything presented as fact.
Make AI earn its place through better experiments
Marketing teams can generate endless copy with AI; volume is not the same as value. I would use it to create genuinely different hypotheses, angles and first drafts, then judge them with real audience results rather than choosing whichever version sounds most polished.
A practical test: Pick one campaign and use AI to produce three distinct approaches based on the same brief. Human-edit them, run the normal test, and compare performance with the team’s baseline.
A prompt template to adapt
This is a template, not a tested result. Replace the brackets with your own details:
"Write three subject lines and one 80-word email for [audience] about [offer]. Use these verified facts only: [facts]. Keep the tone [tone], avoid exaggerated claims, and do not invent testimonials or statistics."
What to check before you rely on it
- Check every claim, statistic and testimonial. Advertising rules in many places require claims to be truthful and supportable.
- Disclose AI-generated images or endorsements where rules or platforms require it.
- Read the draft aloud. Generic AI phrasing is easy for audiences to spot.
- Avoid using real customers’ data in prompts unless your privacy notice and tool settings allow it.
For the habits behind these checks, see Fact-Checking AI Output and Privacy & Data When Using AI.
Frequently asked questions
Does using AI to write marketing copy hurt SEO?
Not inherently — search engines penalise low-quality, unedited mass content, not AI use itself. Reviewed, genuinely useful AI-assisted content performs fine.
Do I need to disclose AI-generated ad content?
For certain content, like AI-generated testimonials or influencer posts, yes, under FTC (US) and ASA (UK) rules. Check the specific disclosure requirements for your content type and region.
Which marketing tasks should stay human-only?
Brand strategy, tone-of-voice decisions, and anything involving real customer relationships or sensitive judgment calls — AI can support these but shouldn't lead them.