Last year the question was whether generative tools were a toy. This year the question is which parts of the job they should touch. We ran a deliberate program across the agency: pick a task, measure the current cost and quality, use the tool for a month, then decide. Here is what stayed.

The nine that stuck

Research synthesis, turning twenty competitor pages into a structured comparison. First draft ad copy variants, where volume matters more than polish because the platform picks the winner anyway. Meta descriptions at scale. Transcription and call summaries. Translating campaign copy between English and Arabic as a first pass. Structured data markup. Turning a rough analytics export into a chart ready summary. Brainstorming hooks for short video. And reformatting one long asset into eight channel specific versions.

The common thread: tasks where the output is checkable in seconds and a mistake costs nothing. Our creative team stopped losing afternoons to reformatting and started spending them on ideas, which is the actual return.

The four we kept human

Strategy, because a model will confidently recommend the average answer and the average answer loses. Final published copy in a client voice, because fluent and forgettable is worse than rough and distinctive. Anything with a number attached to a claim, since a plausible fabricated statistic is the single most dangerous output these tools produce. And client conversations, obviously.

The rules we wrote down for AI in the marketing workflow

Never paste client data into a consumer tool. Every factual claim gets sourced by a human before it ships. Every published word gets edited by someone who could have written it themselves. And we tell clients where these tools are used, because finding out later is a trust problem nobody needs.

The productivity gain across the agency landed around 20 to 25 percent on production tasks and roughly zero on thinking tasks. That ratio is the whole lesson. Speed on the mechanical parts buys time for the part that actually differentiates the work, which is judgment about what to do and why. If you want to see what that judgment produces on real accounts, start with our success stories.