AI in Marketing
Last updated · 1 min read
Where marketing teams actually use AI
Production drafts. First drafts of emails, ads, landing pages and social posts are the workhorse use case — a prompt recipe plus brand guidelines gets to version one in minutes instead of days. The winning teams edit hard; the losing teams publish raw output and all start to sound identical.
Ad optimization. Platforms like Google and Meta have used machine learning for bidding and audience targeting for years. You do not opt in — it is the default plumbing of performance marketing.
Research synthesis. Summarizing hundreds of reviews, survey responses and support tickets into themes is a genuinely strong use of an LLM — pattern-finding over messy text is exactly what it is built for.
SEO. Question clusters, briefs and internal-link ideas come from models; the ranking systems still reward genuinely useful, sourced, first-hand content — the kind that survives AI-generated filler.
The honest limits
Customers can smell generic. Brand voice, cultural judgment and accountability for claims remain human work — a model will happily invent a customer statistic (a hallucination) that looks perfectly at home in a slide deck.