EXPOSED
This is a residual bucket — outreach workers, program coordinators, benefits navigators, reentry and housing specialists — and the modal worker splits time between in-person client contact and a heavy documentation load: intake forms, case notes, eligibility screening, grant reporting, referral logs. The paperwork half is squarely in AI's wheelhouse, and eligibility triage and resource matching are already being handled by chatbots and benefit-screening tools. What holds is the part that requires showing up: home visits, community meetings, walking a distrustful client through a system that has failed them, and de-escalating in real time.
Dipped in 2020, then grew past where it started.
Median pay $43,790 → $56,730 +3.6% 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
+4.6% 119,200 → 124,700 on the projections basis
Growing, and only partly exposed
The BLS expects +4.6% more of these jobs by 2034, and at 49/100 the work is only partly exposed — some tasks are automatable, the core of the job is not. Nothing here is in tension.
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.
~13,100 openings a year on average, including replacing people who leave.
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The BLS uses Community and Social Service Specialists, 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: trust premium . Weakest point: liability shield .
Mixed — a routine tier and a judgment tier Screening a client for SNAP/Medicaid eligibility, generating a referral list, and writing the case note are already being done by benefits-screening software, but sitting with someone in a shelter intake room who won't produce documents, or convincing a landlord to hold a unit for a reentry client, has no digital substitute — roughly half the workweek is exposed, which is what puts this at 11 rather than 6 or 15.
Some physical or field component Home visits, ride-alongs to court dates and clinic appointments, street outreach to encampments, and staffing a table at a community health fair are recurring duties, but they're punctuated by long stretches at a desk in the CRM or HMIS — this is a job with a car and a caseload, not a job with tools and a jobsite, hence 11 and not 16.
No licence, no signature requirement Most of these positions post as bachelor's-preferred with no licence at all; a CHW certification or a state peer-support credential may be listed, and neither creates personal legal exposure — the agency's clinical supervisor or the LCSW signs off on anything with consequence, which is why this sits at 4 and not 8.
Meaningful discretion You decide whether a family goes on the priority list, whether today's disclosure crosses into a mandated-reporter call, and whether to keep a client in a program after a relapse — real calls, but made inside eligibility rules, funder-defined service tiers, and a supervisor's sign-off, which is why this is 9 and not the 15 a clinical decision-maker would carry.
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 (11/20 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 (4/20) is whether the law requires a licensed human to sign. Trust premium (14/20) is whether buyers specifically pay for a person. Judgment and accountability (9/20) 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 27 of this occupation's 49 points (55%).
Embodiment (11/20) 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 67/100 — SAFE.
If state credentialing spreads for the sub-roles now unlicensed — e.g. state certification for peer support and community health workers tied to Medicaid billing (already in place in Texas, Michigan, Indiana), plus mandated-reporter duties attaching personally to the named worker on a case — a human signature becomes billing-required. Also watch VA and SAMHSA grant terms requiring a named certified staffer of record for each enrolled client.
If AI absorbs intake forms, eligibility screening and grant-report drafting, the residual job becomes home visits, engagement of clients who have disengaged, and case conferencing — a genuine two-tier split where the surviving tier is judgment and presence. Watch for Medicaid 1115 waiver and CalAIM Enhanced Care Management contracts that pay per in-person contact rather than per case note.
If funders formalize lived-experience hiring preferences (returning-citizen reentry navigators, peer specialists with the same recovery or immigration history as clients), the buyer is explicitly paying for who the worker is, not the output.
If child-welfare and reentry agencies adopt rules that algorithmic risk scores are advisory only and a named specialist must document an override rationale — as followed the Allegheny County screening tool controversy and DOJ scrutiny — the override call sits with the human and is auditable.
If housing-first and street-medicine models continue expanding (e.g. HUD Continuum of Care outreach requirements, state-funded encampment response teams) the field-contact share of the day rises rather than the desk share.
The limit. Wages and funding structure cap this: the work is grant-funded and chronically underpaid, so agencies face strong pressure to substitute software or volunteers wherever a signature isn't legally required. Trust premium here is paid by funders, not clients, and funders respond to cost.
| New York-Newark-Jersey City, NY-NJ | 14,030 | $66,580 +17% |
| Los Angeles-Long Beach-Anaheim, CA | 5,480 | $56,960 +0% |
| Denver-Aurora-Centennial, CO | 3,620 | $57,830 +2% |
| Seattle-Tacoma-Bellevue, WA | 2,800 | $70,630 +25% |
| San Francisco-Oakland-Fremont, CA | 2,560 | $68,390 +21% |
| Minneapolis-St. Paul-Bloomington, MN-WI | 2,490 | $56,780 +0% |
| Chicago-Naperville-Elgin, IL-IN | 2,260 | $41,240 -27% |
| Atlanta-Sandy Springs-Roswell, GA | 2,090 | $47,160 -17% |
| Harrisburg-Carlisle, PA | 210 | $84,070 +48% |
| Richmond, VA | 1,160 | $77,210 +36% |
| Olympia-Lacey-Tumwater, WA | 250 | $76,690 +35% |
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 49. 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.