COOKED
This is a residual BLS bucket — communications coordinators, media specialists, program assistants, captioners, content and outreach staff who don't fit the writer, editor, PR, or broadcast codes. The modal worker's day is drafting copy and newsletters, formatting and posting content, tracking coverage, transcribing and captioning, and coordinating logistics over email — nearly all of which current models do at usable quality. What persists is the in-person, relationship-carrying slice: running an event, managing a stakeholder or community group, and owning what goes out under an organization's name.
Nearly all of this fall was the 2020 shock. It has been climbing back since.
Median pay $47,580 → $73,620 +23.8% 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
+2.7%
Percentage only. The projection counts a different population from the 19,590 above — it includes self-employed workers, which for this occupation is most of them, so the two headcounts are not comparable.
Exposed, but growing
AI can already do a lot of these tasks, and the BLS still expects +2.7% more of these jobs by 2034. Demand for the output is growing faster than the work is being automated away — the mechanism BLS gives for software developers, and the combination people most often misread as an error.
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.
~3,000 openings a year on average, including replacing people who leave.
ReaderGraphologistTrain CallerScript ManagerTrain AnnouncerStage TechnicianContinuity ManagerAudience CoordinatorAudio-Visual SpecialistPA Announcer (Public Address Announcer)
The BLS uses Media and Communication Workers, All Other for work that doesn't fit any named occupation, so it covers roles that have little in common with each other. Two consequences worth knowing before you read anything below:
Holding it up: task resistance . Weakest point: liability shield .
Mixed — a routine tier and a judgment tier Drafting the weekly newsletter, cutting captions to reading speed, pulling a clip report, and re-sizing the same post for four platforms are all things a model does at first-draft quality today — the 8 rather than a 3 comes from the residual slice this code hides: standing at the check-in table at a community forum, chasing an interpreter who no-showed, and coaxing a quote out of a program director who won't answer email.
Some physical or field component There is a real body in this job on event days — hauling banners and A/V, staffing a booth, shooting phone video at a site visit, sitting in a booth doing live CART or realtime captioning — but it's episodic and in controlled rooms your employer booked, which is why it lands at 6 and not at the 13+ of someone whose worksite is a roof or a roadside.
No licence, no signature requirement Nothing here is licensed: there is no statute a communications coordinator can be struck off under, CPACC or a CRC captioning credential is a hiring preference at best, and when a post goes wrong the exposure sits with the agency, the executive director, or general counsel — not with the person who queued it.
Meaningful discretion Most calls run against a style guide, a brand kit, an approved messaging document, and a posting calendar, but you regularly decide alone and fast whether to post during a local tragedy, how to phrase a correction, and what gets escalated to the director before it goes live — discretion with reputational stakes, exercised inside a chain of approval, which is a 7 rather than a 14.
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 (8/20) is whether buyers specifically pay for a person. Judgment and accountability (7/20) 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 16 of this occupation's 30 points (53%).
Embodiment (6/20) 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.
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 48/100 — EXPOSED.
Task-mix shift: this bucket genuinely has two tiers. If the drafting/formatting/posting/monitoring tier is fully absorbed, the surviving role is event execution, stakeholder and community management, and crisis judgment about what the organization says — work that is not text generation. This raises the score of the remaining job while shrinking headcount, so it is not good news for the count.
Disclosure/attestation regimes for organizational communications: state political-ad AI disclosure laws (e.g. California AB 2839, Texas SB 751) and FTC endorsement/testimonial rules increasingly require a named human to attest that published content is not deceptive synthetic media. If employers formalize a 'human sign-off of record' on outbound comms to preserve insurance or FTC defensibility, the coordinator who presses publish becomes the attesting party.
Accessibility law enforcement that makes a named human responsible for caption/description accuracy: DOJ's 2024 ADA Title II web/mobile rule (28 CFR Part 35, WCAG 2.1 AA compliance by 2026-27) plus FCC caption quality rules already push public entities and broadcasters toward certified human review of machine captions. A CART/CDI-style credential requirement (like court reporter or ADA-mandated qualified interpreter rules) attaching personal certification to live captioning would create a real signature requirement for the captioner slice of this bucket.
Formal escalation ownership: organizations adopting AI content governance policies (e.g. the growing pattern of newsroom and agency AI-use policies requiring a designated human approver before publication, and NIST AI RMF-aligned internal controls) that name a communications staffer as the accountable reviewer for reputational risk decisions.
Concentration of the role into physical event and field work — venue logistics, on-site A/V, community meetings, in-person outreach in unpredictable settings — as remote-composable tasks disappear.
The limit. Realistic ceiling is modest. Trust premium has no plausible route: buyers of newsletters, social posts, and coverage reports do not pay for human authorship and rarely know who wrote it. The liability and accountability levers attach to narrow slices (captioning, political ads, publish authority) that cover a minority of this residual bucket, and every lever above is compatible with the occupation shrinking sharply while the survivors' scores rise.
| Los Angeles-Long Beach-Anaheim, CA | 7,490 | $103,050 +40% |
| San Francisco-Oakland-Fremont, CA | 1,130 | $89,050 +21% |
| New York-Newark-Jersey City, NY-NJ | 1,010 | $80,770 +10% |
| Miami-Fort Lauderdale-West Palm Beach, FL | 870 | $78,730 +7% |
| New Orleans-Metairie, LA | 580 | — |
| Atlanta-Sandy Springs-Roswell, GA | 490 | $75,740 +3% |
| San Diego-Chula Vista-Carlsbad, CA | 270 | $85,180 +16% |
| Washington-Arlington-Alexandria, DC-VA-MD-WV | 270 | $59,070 -20% |
| Los Angeles-Long Beach-Anaheim, CA | 7,490 | $103,050 +40% |
| San Francisco-Oakland-Fremont, CA | 1,130 | $89,050 +21% |
| Sacramento-Roseville-Folsom, CA | 170 | $85,950 +17% |
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 30. 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.