EXPOSED
The production layer of this job — drafting campaign concepts, writing briefs and copy variants, building media plans, assembling performance decks, and A/B analysis — is exactly what generative and media-buying AI now does at usable quality and enormous volume. What holds is the accountability layer: owning a seven-figure budget, negotiating with agencies and media vendors, deciding brand positioning when the data is ambiguous, and standing in front of a CMO or client when a campaign flops. There is no license and no physical work, so the moat is purely relationship and P&L ownership, which means smaller teams of more senior managers rather than the same headcount doing less typing.
This fall is concentrated in 2020 and has not recovered since.
Median pay $125,510 → $133,660 -14.8% in real terms
This line is counted by the Bureau of Labor Statistics — the one figure on this page that isn't a judgement of ours. Headcount moves on demand, offshoring, demographics and the business cycle, and automation is one term among several, often not the loudest.
So a falling line is not evidence that AI did it, and a rising one is not evidence that it won't. Both happen in this register: some occupations resist automation and shrink anyway, others are highly automatable and keep growing. The marked year is 2020.
BLS projection, 2024–2034
-2.2%
Percentage only. The projection counts a different population from the 21,470 above — it includes self-employed workers, which for this occupation is most of them, so the two headcounts are not comparable.
Exposed, and shrinking
Both signals point the same way: the tasks are largely automatable and the BLS projects -2.2% by 2034. This is the case where the score and the forecast agree, and it is the one worth taking seriously.
Different clocks. The score is what current AI could do to this work today. The projection is how many of these jobs will exist in 2034. Everything between the two — how fast employers actually adopt, whether demand grows in the meantime — is why they can point opposite ways without either being wrong.
~2,100 openings a year on average, including replacing people who leave.
Brand ManagerLeague ManagerMedia DirectorMedia PromoterAccount ManagerAccount DirectorCampaign ManagerAccount ExecutiveCampaign DirectorMarketing ManagerAccount SpecialistMarketing DirectorPromotions ManagerCirculation ManagerPromotions DirectorStreet Team ManagerMarketing CoordinatorPrint Traffic ManagerPromotions SupervisorCommunications ManagerCommunications DirectorSales Promotion ManagerCampaign Program ManagerClient Services Director
Holding it up: judgment & accountability . Weakest point: liability shield .
Mixed — a routine tier and a judgment tier An 8 reflects that concept generation, copy variants, media-mix modeling, audience segment builds, and weekly performance reporting — the bulk of hours logged — are now handled by generative tools and programmatic buying platforms, while agency negotiation, budget reallocation mid-flight, and internal stakeholder alignment still need a person in the room, which is why this sits above the 6 line rather than below it.
Fully desk- and screen-based A 3 acknowledges the occasional shoot supervision, trade show booth walkthrough, or press event, but the job is run from a laptop with campaign dashboards, spreadsheets, and video calls to agencies — nothing about the work fails if you never leave the desk.
No licence, no signature requirement A 1 rather than 0 because FTC truth-in-advertising rules, Lanham Act false-advertising exposure, and industry-specific claims review (pharma, financial services) do create real legal risk — but that risk lands on the company and its counsel, not on a credential you personally hold, since no license or registration gates the title.
Meaningful discretion A 13 is earned by the calls that have no right answer in the data: pulling a live campaign during a brand-safety incident, shifting spend from a channel that looks good on last-click to one that doesn't, approving a positioning that could alienate an existing segment — you own the outcome to the P&L, but you own it inside a budget someone above you set.
The verdict above describes this occupation as a whole. Almost nobody does the typical version of a job — tick what's actually in your week and see how your own mix sits.
Your task mix speaks to task resistance (8/20 here) — how much of the day's work current AI already does. That is the dimension the boxes above are about.
It cannot move the other three. Liability shield (1/20) is whether the law requires a licensed human to sign. Trust premium (11/20) is whether buyers specifically pay for a person. Judgment and accountability (13/20) is whether the role exists to own consequential calls. Those are facts about the occupation's standing, not about which tasks are in your week — a paralegal who does only trial exhibits still holds no licence. Together they are 25 of this occupation's 36 points (69%).
Embodiment (3/20) is also a property of the work rather than the worker, but we don't tag individual tasks as physical or not, so the picker can't tell you anything about it. That's a limit of this tool, not a claim.
Did we get the list right? Tell us what's missing — the tasks are written from the outside, and you're reading this from the inside.
Fundraising Managers EXPOSED
Sales Managers EXPOSED
The moves above are yours to make. This is the other half: what would have to change in the world for the occupation itself to score higher. None of it is in any one person's gift, but it is where the floor actually comes from. Scores here are not a one-way ratchet. Only two of the five dimensions — task resistance and embodiment — track what machines can do. The other three track law, what buyers will pay for, and who is answerable, and those move in both directions, often in response to the same pressure AI creates. If every lever below landed, this occupation would score around 47/100, still EXPOSED.
Pure task-mix shift, no law needed: once brief-writing, copy variants, media-plan drafts and performance decks are fully machine-produced, what remains billable as a manager's day is agency/vendor negotiation, budget reallocation under ambiguous attribution data, and crisis calls on creative that has offended someone. The job genuinely has two tiers; the residual tier is thin but hard. Watch for job postings that drop 'copywriting/deck-building' from the requirements and add 'P&L ownership' and 'agency roster management'.
Named-human-accountability rules for synthetic ad content: state synthetic-media disclosure laws for political and issue ads (California AB 2839/AB 2355, Texas SB 751, Michigan, Washington) plus EU AI Act Art. 50 transparency and the EU Political Advertising Regulation, which require a identified responsible sponsor/advertiser for AI-generated creative. If US platform or FTC guidance extends synthetic-disclosure attestation to commercial advertising, the marketing lead becomes the person who personally signs that a campaign's claims and imagery were substantiated.
Not a license, but a functional equivalent: FTC Section 5 substantiation enforcement naming individual marketing executives in consent orders (as it has done in ROSCA and endorsement-guide cases), or D&O/media-liability insurers requiring a named marketing officer to attest that AI-generated claims and testimonials were reviewed before binding coverage. This is a real underwriting trend in media E&O post-2023 generative-AI exclusions. It creates personal exposure without creating a credential, so the lift is capped.
Contractual human-authorship guarantees: SAG-AFTRA's 2023 commercials and interactive agreements and WGA-style AI clauses spreading into brand-agency master service agreements, where a client pays for and warrants human-conceived creative. Also visible in some consumer brands advertising 'no AI' credentials. This protects the creative supply chain more than the manager role, so expect only a small lift.
The limit. Even with all four levers, this tops out in the low-to-mid 50s. There is no licensure route, no embodiment, and no route to headcount protection: accountability moats concentrate work into fewer, more senior seats rather than preserving the 21,470. A rising score here can coexist with a shrinking occupation.
| New York-Newark-Jersey City, NY-NJ | 3,630 | $174,390 +30% |
| Dallas-Fort Worth-Arlington, TX | 1,370 | $108,690 -19% |
| Los Angeles-Long Beach-Anaheim, CA | 1,350 | $167,930 +26% |
| Houston-Pasadena-The Woodlands, TX | 800 | $91,900 -31% |
| Philadelphia-Camden-Wilmington, PA-NJ-DE-MD | 660 | $146,510 +10% |
| Austin-Round Rock-San Marcos, TX | 570 | $123,360 -8% |
| San Francisco-Oakland-Fremont, CA | 440 | $181,250 +36% |
| Atlanta-Sandy Springs-Roswell, GA | 370 | $146,560 +10% |
| San Francisco-Oakland-Fremont, CA | 440 | $181,250 +36% |
| San Jose-Sunnyvale-Santa Clara, CA | 240 | $180,500 +35% |
| New York-Newark-Jersey City, NY-NJ | 3,630 | $174,390 +30% |
We have no reported case of a named organisation automating this occupation. Not one deployment, not one announcement.
That is worth saying out loud next to a score of 36. The verdict above is about what the work exposes — what current AI could do to these tasks. It is not a claim that anyone has done it. For this occupation those two things have come apart completely: the capability argument is on this page, and the evidence column is empty.
Has AI actually changed your work? One tap, anonymous, and the running tally is public. Nothing else is asked of you.
Rather than check back: get the digest and we'll tell you what changed — or watch a single occupation from its own page.