How AI Is Changing What A Media Plan Actually Looks Like
A media plan used to be a document: fixed allocations across channels, signed off once, executed against for the length of a campaign. AI is turning it into something that keeps adjusting itself while the campaign runs, and that changes what a planner is actually being paid to do.
The traditional planning cycle assumed that decisions made in advance, based on the best available data at the time, would hold reasonably well for the length of a flight. AI-driven optimisation tools break that assumption deliberately, reallocating spend across channels and formats in near real time based on live performance signals, not the quarterly assumptions a plan was built on. The plan stops being a static artefact and starts being closer to a starting configuration for a system that keeps rewriting itself.
What this removes from a planner's job
The manual, spreadsheet-heavy work of building initial channel splits and adjusting them week to week based on reporting is exactly the kind of task these systems now do faster and more consistently than a human running the same numbers by hand. That part of planning was never where the real strategic value sat, and its disappearance from a planner's day-to-day is closer to relief than loss for most people doing the job.
What it adds instead
What's left, and what's growing in importance, is deciding what the optimisation system should actually be optimising for in the first place. An algorithm can chase the metric it's given extremely well; it cannot decide on its own whether that metric is the right one for a brand's actual objective this quarter. Planners are increasingly spending their time setting the constraints and goals a system operates within, checking its outputs against business context it doesn't have, and stepping in when a live reallocation is technically correct but strategically wrong.
The plan used to be the deliverable. Increasingly, the deliverable is deciding what the machine that builds the plan should be trying to achieve.
Why this raises the skill floor, not lowers it
This shift makes the job harder to do badly, not easier. A planner who doesn't understand what an optimisation algorithm is actually doing under the hood can no longer catch it making a strategically wrong call, because they're no longer building the plan by hand and noticing the same mistakes along the way. The planners who do well in this environment are the ones who understand both the media landscape and enough of how the underlying systems work to know when to override them.