← Risk register SOC 29-2061 · reviewed 2026-08-11

Licensed Practical and Licensed Vocational Nurses

648,410 US workers · median $64,400/yr · Healthcare

SAFE

The core of this job — administering injections and oral meds, changing dressings, inserting catheters, taking vitals, repositioning and bathing residents, feeding, monitoring for skin breakdown — happens with hands on a human body in nursing homes and clinics, where robotics is nowhere close. AI will absorb the charting, care-plan documentation, shift-report summaries, and insurance paperwork that eat a real share of the shift, which changes the day but not the headcount. State licensure and personal accountability for medication administration keep a credentialed human in the loop; note that this is a regulatory shield, and scope-of-practice rules can be rewritten.

10-year outlook: Demand keeps climbing with an aging population in nursing homes and home health; expect documentation load to shrink and bedside hours per shift to rise.

US employment, 2019–2025-7.0%
697,510648,410 workers

This fall is concentrated in 2020 and has not recovered since.

Median pay $47,480 → $64,400 +8.5% in real terms (nominal +35.6%, less ~25% US inflation over the period)

The job count is not the verdict

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

+2.6% 651,400 → 668,500 on the projections basis

Hard to automate, and growing

The work resists current AI and the BLS projects +2.6% more of these jobs by 2034. Note that safe does not mean well paid — several of the fastest-growing resistant occupations are among the lowest paid on the register.

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.

~54,400 openings a year on average, including replacing people who leave.

One email if this score changes. Watch as many occupations as you like from the same address — no account, and nothing is sent on a schedule, only when a verdict actually moves.

Also known as — 16 job titles this covers

Titles reported by people doing this work, from the US Department of Labor's O*NET survey. If your job title is here, this page is about your work even though the name doesn't match.

Charge NurseClinic NurseOffice NursePrivate Duty NurseRadiation Oncology NurseLicensed Practical Nurse (LPN)Licensed Care Coordinator (LCC)Licensed Vocational Nurse (LVN)Clinic Licensed Practical Nurse (Clinic LPN)Triage LPN (Triage Licensed Practical Nurse)Medical LPN (Medical Licensed Practical Nurse)Pediatric LPN (Pediatric Licensed Practical Nurse)Home Health Licensed Practical Nurse (Home Health LPN)Nursing Home LPN (Nursing Home Licensed Practical Nurse)Private Duty Licensed Practical Nurse (Private Duty LPN)Long Term Care LPN (Long Term Care Licensed Practical Nurse)

Score — 73/100 resistance

Holding it up: embodiment (18/20). Weakest point: judgment & accountability (10/20).

Five dimensions, 0–20 each, summed. Higher means more protected. The arithmetic is shown so you can check it: 15 + 18 + 15 + 15 + 10 = 73. · Scored 2026-08-11, and re-examined when evidence accumulates rather than on a schedule.

Task resistance 15/20

Tasks largely resist digitisation At 15, the shift is dominated by tasks no software can perform — wound irrigation and packing, IM and subcutaneous injections, Foley insertion, ostomy care, glucose checks, two-person transfers — but it isn't 18 because MAR reconciliation, MDS-adjacent documentation, prior-auth forms, and shift-change reporting are genuine hours of the day and are exactly what language models eat first.

Embodiment 18/20

Hands-on in uncontrolled environments An 18 reflects a body that must be within arm's reach of another body in an uncontrolled setting: turning a 240-lb resident on a fall-risk mattress, catching a combative dementia patient mid-slide, palpating for a vein, smelling a wound before you see it — the 2 points held back only because a slice of LPN work is now telehealth triage and clinic phone follow-up.

Liability shield 15/20

Licensed human required and personally liable 15 is right because your NCLEX-PN license and state board number are attached to every med you push and every entry you sign, and a diversion or wrong-dose error goes to your license, not just your employer's — but it sits below the 18-20 band because your scope is defined and supervised by the RN or physician who writes the orders, so you carry accountability without independent authority.

Trust premium 15/20

The human relationship is the product In long-term care you are the person a resident sees three shifts a week for two years, and families call asking for you by name because you noticed the appetite change first; 15 rather than 19 because agency staffing, high turnover, and rotating floor assignments mean the institution, not the individual, is often what the patient is stuck with.

Judgment & accountability 10/20

Meaningful discretion 10 fits the reality that you decide when a change in mentation, output, or skin color warrants escalating to the RN or calling the family — real triage discretion under time pressure — but the definitive calls on diagnosis, med changes, and code status belong to others, and much of your day runs on standing orders, care plans, and protocol.

Confidence: high · reviewed 2026-08-11 · how scoring works

What this job involves — and which parts are yours

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.

AI already does these at usable quality

These still need a person

Active moats on the surviving side: embodiment, licensure, trust

How to future-proof this job

Where to go deeper on what this job runs on: Coursera — customer service and client-facing skill courses free to audit · Coursera — communication and interpersonal skills free to audit · Coursera — project coordination and cross-team delivery free to audit · Coursera — active listening and communication skills free to audit · Toastmasters — public speaking practice at local clubs worldwide low · edX — performance measurement and evaluation free to audit

All 35 skills ranked by how many jobs they open →

What would move this back up — beyond any one person

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 83/100, still SAFE.

4 specific changes that would raise this score
  • already happening judgment accountability +4

    Task-mix shift: once charting, MDS/care-plan documentation and prior-auth paperwork are absorbed by AI, the residual shift is assessment, deterioration recognition and escalation calls. This rises further if facilities formalize LPN 'charge nurse' roles in SNFs with documented authority to escalate to the on-call provider, and if AI early-warning systems (sepsis, fall, skin-breakdown alerts) are deployed with a licensed nurse required to adjudicate each alert — the pattern already emerging with Epic Deterioration Index workflows.

  • plausible liability shield +3

    Federal enforcement of the CMS minimum staffing rule for long-term care (2024 final rule, 42 CFR 483.35 — 3.48 total nursing HPRD with specific RN/aide floors) plus state-level licensed-nurse ratio laws that count LPN hours specifically; also state board rules that bar unlicensed or AI-directed medication administration in assisted living. Watch state nurse practice act revisions that explicitly name the licensed nurse as accountable for verifying AI-generated med reconciliation or fall-risk flags.

  • plausible task resistance +2

    Acuity shift in nursing homes: as lower-acuity residents move to home-based and remote-monitoring care, the on-site caseload concentrates into complex wound care, trach/vent, IV therapy, and behavioral dementia care — tasks with no automation path. Watch state expansions of LPN scope to IV push and central line care (already permitted in several states).

  • plausible trust premium +1

    Narrow route only: private-duty and hospice home-care markets where families pay out of pocket and explicitly contract for a named human at the bedside. This does not extend to institutional LTC, where the payer is Medicaid and buyers do not choose the nurse.

The limit. Already 73 and near the practical ceiling on embodiment. The realistic risk direction is downward, not upward: scope-of-practice deregulation letting medication aides or AI-supervised unlicensed staff administer meds would cut liability_shield fast, and institutional payers give this occupation almost no trust premium to build on.

These are conditions, not forecasts — what would have to happen, not what will. Specific rules, cases and bills are named so you can go and check whether they exist and where they stand; verify before relying on any of them. Nothing here is legal or financial advice.

Where this work is, and what it pays there

BLS metro figures for 391 areas. The verdict above does not change by city — the rubric judges what the work involves, not where it happens — but pay and headcount do, and the national median hides a very wide range.

Most of these jobs

Los Angeles-Long Beach-Anaheim, CA 33,590 $79,310 +23%
New York-Newark-Jersey City, NY-NJ 32,410 $75,910 +18%
Philadelphia-Camden-Wilmington, PA-NJ-DE-MD 15,920 $70,710 +10%
Dallas-Fort Worth-Arlington, TX 12,590 $64,370 +0%
Chicago-Naperville-Elgin, IL-IN 11,420 $78,070 +21%
Houston-Pasadena-The Woodlands, TX 10,730 $63,670 -1%
Atlanta-Sandy Springs-Roswell, GA 9,710 $65,060 +1%
Miami-Fort Lauderdale-West Palm Beach, FL 8,900 $62,610 -3%

Best paid

San Jose-Sunnyvale-Santa Clara, CA 3,290 $95,320 +48%
San Francisco-Oakland-Fremont, CA 8,800 $94,310 +46%
Santa Rosa-Petaluma, CA 870 $92,580 +44%

Percentages are against this occupation's national median of $64,400. Counts are jobs in that metro, not vacancies. Metros where the BLS suppressed the cell are absent rather than shown as zero.

Who is actually doing this — nobody, on the record

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 73. 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.

Read that as a gap in the reporting we can see, not proof of absence — the dispatch runs on English-language feeds and misses plenty. If you know of a case, tell us, or add a field report from inside the job.

Quick take — do you do this job?

Has AI actually changed your work? One tap, anonymous, and the running tally is public. Nothing else is asked of you.

Self-reported and unverified — a sentiment signal, not a survey. One response per person per occupation; you can change your answer.

Field reports — what people say has changed

No field reports yet. A written account takes a paragraph rather than a tap, goes to an editor before it appears, and is the one thing on this page the rubric cannot produce on its own.

File a field report

Concrete beats general: a tool that arrived, a task that moved, a headcount decision you watched happen. Don't include anything that identifies you or your employer if that would put you at risk.

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