Lists of AI use cases for marketing are easy to find and hard to act on. Most of them describe what a tool can do in general. This one is organised around work a marketing team already does, with a note on what each task needs before AI can help with it.
The examples are illustrative. Which of them fit your team depends on your process, the tools you have approved and who reviews the result.
Content and drafting
- A first draft from an approved brief. Needs the current brief, brand guidance and a person who edits before anything is published.
- Adapting one approved piece for several channels. Needs the source text and clear rules for each format, such as length and tone.
- Answering writers’ questions about the product. Needs approved product material and references in every answer so a writer can check the source.
Research and company knowledge
- Finding the current answer in internal documents. Needs a maintained set of sources and agreed access rules. Old versions cause more trouble than missing ones.
- Summarising supplied research. Needs the material itself, not a general question, and a format the team already uses for notes.
- Competitor and market notes from named sources. Needs a list of sources you trust and a reviewer who knows the market well enough to spot a wrong claim.
Reporting
- A plain-language summary of a report the team has already checked. Needs agreed metric definitions and the reporting period in the prompt.
- Flagging unusual changes for a person to investigate. Needs a defined baseline. The assistant points, a person explains.
- Drafting client commentary for an agency report. Needs the checked figures, the campaign context and an account manager who signs it off.
Leads and enquiries
- Summarising a free-text enquiry before handoff. Needs the original message kept alongside the summary so nothing is lost in translation.
- Checking a submission for missing information. Needs a clear list of required fields. This is usually a rule, not AI.
- Drafting a follow-up for review. Needs the enquiry, the summary and a person who decides whether to send it.
What every use case has in common
Each one needs three things: a source the team trusts, a named owner and a review step. Where one of them is missing, the task tends to produce confident output nobody wants to rely on.
Several items on the list are not really AI tasks at all. Routing a lead by country or checking required fields follows fixed rules. This guide explains how to tell the two apart before commissioning any work.
How to choose the first one
Pick the task that happens most often, that one person can describe end to end and whose result that person can judge in a few minutes. Frequency gives you enough attempts to compare. A clear owner gives you someone to ask what changed. A quick review keeps the pilot honest.
If you want to work through that choice with someone, see how we approach AI for marketing teams or read where a marketing team should start with AI.
