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Will AI replace Insurance Underwriters?

Review individual applications for insurance to evaluate degree of risk involved and determine acceptance of applications. The percentage shown is a task-exposure model, not a prediction of certain job loss.

O*NET 30.3 · 13-2053.00 · modeled exposure, not guaranteed job loss
MODERATE TASK EXPOSURE
56%
Estimated share of representative tasks exposed to current AI capabilities.
Last updatedAugust 20, 2026
Evidence confidenceMedium
Browse this risk tierModerate exposure jobs →
Task automation shareⓘ
56%Automatable
Automatable56%
Augmentable22%
Hard to automate22%
Based on analysis of representative responsibilities and current AI capability maturity.
Category#
Finance & Legal
Back office / Ops
Modeled pay midpoint$
$61,700/yr
Directional estimate — verify locally
Time until impact⌁
2–4 years
Earliest 2027 · widespread 2029–2031
Task-level replaceability ⓘ
Representative tasks ranked from highest to lowest AI exposure.
◇Examine documents to determine degree of risk from factors such as applicant health, financial standing and value, and condition of property.66%
⚙Decline excessive risks.57%
▥Write to field representatives, medical personnel, or others to obtain further information, quote rates, or explain company underwriting policies.47%
✦Licensed accountability and complex judgment15%
✦Interpreting unusual, high-stakes cases11%
Impact timeline ⓘ
How AI assistance may move from early support to wider adoption.
2027Next2029–2031
Early impactAI begins supporting examine documents to determine degree of risk from factors such as applicant health, financial standing and value, and condition of property..
Role reshapingRepeatable tasks become faster and more automated.
Wider adoptionThe role centers more on licensed accountability and complex judgment.
2–4 yearsdirectional confidence window
HOW AI CHANGES THIS JOBtyping the logic in plain English
01>Start with the real work done by Insurance Underwriters.
02>AI can help with: Examine documents to determine degree of risk from factors such as applicant health, financial standing and value, and condition of property.
03>If a task is repetitive and easy to check, AI pressure goes up.
04>But a person is still needed for: Licensed accountability and complex judgment.
05>Likely result: AI is more likely to change this job than remove it.
06>Important: 56% is estimated task exposure—not a 56% chance of losing the job.
What AI can do
Examine documents to determine degree of risk from factors such as applicant health, financial standing and value, and condition of property.MEDIUM-HIGH
Decline excessive risks.MEDIUM
Write to field representatives, medical personnel, or others to obtain further information, quote rates, or explain company underwriting policies.MEDIUM
How estimates work →
Your human moat
◆

Licensed accountability and complex judgment

MEDIUM-HIGH

Combined with interpreting unusual, high-stakes cases, this keeps a human in the loop.

Strength7.0
Similar-role comparison
RoleRisk
Insurance Underwriters56%
Management Analysts55%
Accountants and Auditors57%
Financial Specialists, All Other57%
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Why this score?

✓The model evaluates 3 representative core tasks.
✓The role mixes repeatable work with human judgment.
✓Occupation and task language comes from O*NET 30.3.
✓The strongest human advantage is licensed accountability and complex judgment.
Research basis

O*NET 30.3 occupation tasks plus the ILO 2025 exposure framework. Scores are directional estimates.

Read ILO research →
Data: O*NET 30.3 · Model framework: ILO 2025O*NET 13-2053.00Share report
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Sources for this report

Official occupation tasks; timeline remains uncertain Scores are directional estimates and sources do not endorse this site’s exact percentage.

O*NET 13-2053.00 occupation profile ↗ILO Generative AI and Jobs 2025 ↗Scoring methodology →

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