Every few months a new "AI marketing tool" launches, promising to replace some piece of the marketing function. Most of them don't replace anything. They produce competent, generic output that requires nearly as much editing as starting from scratch. The teams using them get frustrated, blame the tool, and try the next one. The cycle repeats.
The diagnosis is wrong. The tools aren't the problem. The brief is. AI marketing tools are wrappers around general-purpose models. They're as good as the brief you give them. Most marketing briefs are bad, so most AI marketing output is bad. The tool didn't fail. The input did.
WHY MARKETING BRIEFS ARE BAD
Most marketing briefs are bad in predictable ways. They describe the audience too broadly. They list every value the brand wants to communicate, instead of the one that matters. They include "tone" instructions that mean nothing ("conversational but professional"). They specify the ask without specifying the failure mode.
This was true before AI. Pre-AI, briefs that were too generic produced generic creative work, which then got revised three or four times until it was usable. The brief problem was hidden by the creative team's ability to compensate.
AI doesn't compensate. AI executes the brief literally. A bad brief produces bad output, faster and cheaper than a creative team would have produced it. The visibility of the brief problem went up because the cost of the brief problem went down. Nothing about the brief itself changed.
WHAT A GOOD BRIEF LOOKS LIKE
A good brief gives the model enough specificity that the most likely answer to the brief is also the right answer. This means: a specific audience defined narrowly enough that you could picture one of them; a specific tension or insight you're trying to land on; constraints that rule out the obvious wrong answers; reference material that establishes voice; an explicit failure mode.
If your brief is general enough that any brand in your category could submit it, the output you get back will sound like any brand in your category. The specificity of the brief determines the specificity of the output.
HOW TO TEST WHETHER YOUR BRIEFS ARE THE PROBLEM
Run a quick experiment. Take a piece of marketing work that didn't land and pull up the brief that produced it. Read the brief. Ask: could a competitor have written a brief that's nearly identical and gotten output from the same tool? If the answer is yes, the brief is the problem. The tool was producing the most likely answer to a generic prompt. The output couldn't have been better than the input allowed.
Now write the brief you wish you'd written. Specific audience. Specific insight. Specific constraints. Run it through the same tool. Compare the output. If the output is meaningfully better, you've diagnosed the problem. The tool was always capable of better work. You just weren't asking for it specifically enough.
THE LARGER POINT
AI marketing tools have raised the floor on what marketing teams can produce. They've done very little for the ceiling. The ceiling is set by the quality of thinking that goes into the brief, which is set by the quality of strategic clarity the team has, which is set by the team's willingness to commit to specific positions about their audience and category.
The teams that complain about AI marketing tools usually have a strategic clarity problem hiding inside what looks like a tool problem. The tools are exposing the lack of clarity, not creating it. The right response isn't a different tool. It's better thinking upstream of the tool. The brief is the work. The tool is just the production line.