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Insurance Underwriters

Review individual applications for insurance to evaluate degree of risk involved and determine acceptance of applications.

105,420 people do this job in the US. $81,370 a year.

now
85%

of the working time. Estimate.

Kinds of work
  • 100%
  • 0%
  • 0%
6%

Measured, from Anthropic's usage data (2025). Counts help on part of a task.

Half the desk work within reach
Already

On the chosen pace and reliability. Estimate.

Share of the working time within reach, now to 2030

0%25%50%75%100%2027202820292030Now
Chosen to
DateNow
NowEnd of 2030

What each choice means: , , , , . Every pace starts from .

At this date and pace, models finish tasks up to 4.4 h long four times in five.

How far this has come

With GPT-4, measured in March 2023, 0% of this job's working time was within reach at . With Claude 3.7 Sonnet, measured in February 2025, 1%. With Claude Mythos Preview (early), measured in April 2026, 74%. Today's estimate: 85%.

0%25%50%75%100%2023202420252026GPT-4, March 2023: 0% within reachGPT-4 Turbo (Nov 2023), November 2023: 0% within reachGPT-4o, May 2024: 0% within reachClaude 3.5 Sonnet (June 2024), June 2024: 0% within reacho1-preview, September 2024: 0% within reachClaude 3.5 Sonnet (Oct 2024), October 2024: 0% within reacho1, December 2024: 0% within reachClaude 3.7 Sonnet, February 2025: 1% within reacho3, April 2025: 10% within reachGPT-5, August 2025: 15% within reachGemini 3 Pro, November 2025: 24% within reachClaude Opus 4.5, November 2025: 24% within reachGPT-5.2, December 2025: 31% within reachClaude Opus 4.6, February 2026: 34% within reachClaude Mythos Preview (early), April 2026: 74% within reachToday (estimate), September 2026: 85% within reach
Each step is a new best model measured by METR, four in five; the dashed end is today's estimate. Point at a dot for the model.

A backcast: today's task data with the best model METR had measured by each date. It shows how fast the models have moved, not what anyone forecast at the time.

The tasks

Sorted by . 7 tasks from .

TaskKind
Examine documents to determine degree of risk from factors such as applicant health, financial standing and value, and condition of property.Done hourly or more by most who do it. 41%1.3 h25 min to 3.3 h77%Half by now
Evaluate possibility of losses due to catastrophe or excessive insurance.Done daily by most who do it. 19%1.3 h25 min to 3.3 h77%Half by now
Decrease value of policy when risk is substandard and specify applicable endorsements or apply rating to ensure safe, profitable distribution of risks, using reference materials.Done several times a day by most who do it. 15%1.1 h25 min to 2.1 h95%Half by now
Write to field representatives, medical personnel, or others to obtain further information, quote rates, or explain company underwriting policies.Done several times a day by most who do it. 9%21 min8 min to 50 min100%Half by now
Review company records to determine amount of insurance in force on single risk or group of closely related risks.Done several times a day by most who do it. 8%29 min13 min to 1.3 h99%Half by now
Authorize reinsurance of policy when risk is high.Done more than yearly by most who do it. 4%50 min17 min to 2.5 h87%Half by now
Decline excessive risks.Done more than weekly by most who do it. AI observed on this task.4%21 min8 min to 50 min100%Half by now

Within reach, per task: the share of the task's time whose instances are short enough for a model to finish at the chosen date, pace and reliability. Half by: the date half of that time comes within reach.

Jobs that share skills with this one

From O*NET's related occupations. Within reach now and by the end of 2028, long-run pace, four in five.

Where this job works

The industry groups that employ the most of it (BLS, May 2025).

Where the most of these jobs are

The metro areas with the most people in it (BLS, May 2025).