Will AI replace insurance claims and policy processing clerks?
Partly.
This job scores 58 out of 100 onStill needs a humanOur headline score for each job, from 0 to 100. Higher is safer: AI can do less of the work, or does it less well.It combines how much of the job AI can do with how well AI does it compared with a qualified person, and it is always shown beside those answers.How the score works · More in the glossary (higher is safer). Today AI could do about 17% of the work by itself, and people do 83% with AI’s help.
No two jobs leave the same print
Every job gets its own fingerprint, drawn from its code. The amber ridges are the share of task time that still needs a person. Below them, the same ridges are written out in ones and zeros: slate for the work AI helps with, white for the work AI can do.
What AI can and cannot do
The tasks that make up the job, from O*NET, and where AI stands on each today. 0% of the task time still needs a human.
Is it better than a person? The evidence
No direct test against people in this job yet. Every study is graded A to D, and vendor studies are labelled as such.
Could be largely automated 2035–2045
80% of scenarios between 2035 and 2045. A range from our scenario model of capability, adoption and friction, not a forecast that the job ends.
How this job could shift, year by year
We run this job as ten scenarios spread across its replacement range. In each, the score moves towards the bottom band (Largely: AI could largely do the job) by the year that scenario reaches it, slowly at first and faster later, as adoption usually goes. Each bar splits the ten by the band they put the job in. The model stops at 2060. How the timeline works
Show the data
| Year | Largely | Mostly | Partly | A little | Nah |
|---|---|---|---|---|---|
| Today (2026) | 0.0% | 0.0% | 100.0% | 0.0% | 0.0% |
| 2030 | 0.0% | 10.0% | 90.0% | 0.0% | 0.0% |
| 2035 | 40.0% | 50.0% | 10.0% | 0.0% | 0.0% |
| 2040 | 80.0% | 20.0% | 0.0% | 0.0% | 0.0% |
| 2045 | 100.0% | 0.0% | 0.0% | 0.0% | 0.0% |
| 2050 | 100.0% | 0.0% | 0.0% | 0.0% | 0.0% |
| 2055 | 100.0% | 0.0% | 0.0% | 0.0% | 0.0% |
| 2060 | 100.0% | 0.0% | 0.0% | 0.0% | 0.0% |
What’s stopping AI taking over?
The things that keep this work with people, strongest first. Each is scored 0 to 100 from O*NET work context, licensing and the evidence we have.
What would it cost to hand the work to AI?
The share of the year AI could handle (1,050 of 2,080 hours a year), priced two ways. Both are ranges, not quotes.
Robots and humanoids
AI software can only take the work at a screen. The rest needs a robot that can do it.
Source: Anthropic Economic Index, 'What work can robots do?' (30 September 2026); O*NET 31.0 task weights.
Which AI skills does this job lean on?
The job’s task time split by what an AI model would need to be good at, and where models stand today.
Still needs a human: 58/100↑ safer
The amber matter on the outside holds its orbit: that is the task time that still needs a person. The slate matter circling the inner disc is the work AI helps with. The white matter is the share AI can do; it spirals in and is gone over the edge.
People are asking
How often people ask whether AI will replace this job: on Google, and by estimate, in AI assistants.
In the US
Source: DataForSEO, US and UK, fetched October 3, 2026. Google figures are Google Ads’ rounded monthly averages. The AI figure is DataForSEO’s estimate from Google’s “People also ask” data, not a count from any AI assistant. UK workers are ONS employment figures matched to this job, so the UK rate per 1,000 is an estimate. Search figures are not part of our open dataset.
What the AIs say
We asked four AI assistants the same question: will AI replace this job in the next 10 years? One word (Yes, Partly or No), then one sentence. Our own answer, from the data: Still needs a human: 58/100 ↑ safer. Will AI replace them? Partly.
AI will automate many routine claims tasks like intake, assessment, fraud detection, and simple settlements, but complex, disputed, or sensitive claims will still need human judgment.
gpt-5.5-2026-04-23 · asked 2026-10-03AI will automate and streamline much of the claims process—especially routine claims assessment, fraud detection, and initial processing—but complex, disputed, or high-value claims will likely still require human judgment and oversight within the next decade.
claude-sonnet-5 · asked 2026-10-03While AI will automate routine, data-driven claims processing and fraud detection, complex, high-value, and disputed claims will still require human judgment, empathy, and oversight.
gemini-3.8-flash · asked 2026-10-03AI will likely automate many routine claims, while humans remain necessary for complex, disputed, and high-value cases.
sonar · asked 2026-10-03Cite this page
NeedsAHuman.com (2026). Will AI replace Insurance Claims and Policy Processing Clerks? Partly. Still needs a human: 58/100, higher is safer; release 2026-Q4. https://needsahuman.com/jobs/insurance-claims-and-policy-processing-clerks/ (accessed 3 October 2026).
Scores change with each ReleaseA dated edition of all our scores, such as 2026-Q4. Scores can change from one release to the next, so cite the release.What changed in each release · More in the glossary, so cite the release. The data is open under CC BY 4.0A free license: anyone may reuse and republish the data, even commercially, as long as they credit the source with a link.Our scores are open under it; so is O*NET.Download the open data · More in the glossary: credit NeedsAHuman.com with a link. Open data · Press
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Sources
- Tasks and work context: O*NETThe US government’s free database of about 1,000 jobs, listing each job’s tasks and how much each one matters.Run for the US Department of Labor. Every score here starts from its task lists (version 31.0).onetcenter.org · More in the glossary 31.0, US Department of Labor (USDOL/ETA)The US government department for work and workers. Its Employment and Training Administration (ETA) pays for O*NET.dol.gov · More in the glossary (CC BY 4.0A free license: anyone may reuse and republish the data, even commercially, as long as they credit the source with a link.Our scores are open under it; so is O*NET.Download the open data · More in the glossary).
- Jobs, pay and projections: US BLSThe Bureau of Labor Statistics: the US government’s official source for how many people do each job, what they earn, and job outlook.bls.gov · More in the glossary, OEWSOccupational Employment and Wage Statistics: the government survey that counts how many people do each job, and their pay, by state.Run by the Bureau of Labor Statistics.More in the glossary and Employment ProjectionsThe Bureau of Labor Statistics’ official ten-year outlook for each job, now 2025 to 2035: expected growth or decline, and openings each year.More in the glossary 2025–35.
- How AI is used today: Anthropic Economic IndexData published by Anthropic, the company that makes the Claude AI assistant, on which work tasks people actually use Claude for.It shows where AI is used today, not only where it could be. Its robot data also caps hands-on tasks.anthropic.com · More in the glossary; Microsoft Research, Microsoft “Working with AI”A Microsoft Research study of real conversations with its Copilot assistant, showing which kinds of work people use AI for.More in the glossary.
- What AI can do: our task ratings (RubricOur published checklist for rating what AI can do on each task, from “no meaningful part” to “the whole task, at a qualified worker’s standard.”An AI model applies it to every task; the levels are T0 to T3.Read the rubric · More in the glossary r1) and the quality evidence register.
- UK names and employment: ONSThe Office for National Statistics, the UK government’s official statistics body. Our UK job and pay figures come from it.ons.gov.uk · More in the glossary UK SOC 2020The UK’s official job codes, such as 2421 for chartered and certified accountants. We match each job to its closest UK codes.More in the glossary coding index and Annual Population SurveyA large UK household survey by the ONS, used to estimate how many people in the UK do each job.More in the glossary.
How each score is built: methodology. Every figure on this page: open data. Release 2026-Q4.