Finance occupation

Will AI replace Insurance Underwriters?

See how this occupation’s day-to-day work compares with other jobs in exposure to AI and automation, why it received this result, and where human skills remain essential.

Insurance Underwriters

Higher AI & automation exposure than 84% of jobs we compare.

Exposure index: 84 / 100

This compares the type of work in this job with the work in hundreds of other jobs.

This is a comparison between jobs — not a 84% chance of job loss.

Why did this job get this result?

  • Reviewing insurance applications, credit reports, property inspections, and loss histories involves continuous digital screening.
  • Applying underwriting guidelines, policy terms, and rate tables follows established risk-selection protocols.
  • Underwriting is performed in office environments using policy management software without physical automation.
  • Underwriters must evaluate non-standard applications, assess moral hazards, and determine customized coverage conditions.
  • Negotiating terms with insurance brokers, explaining coverage declensions, and building agency relationships require strong interpersonal skills.

How technology may change this work

Technology and human strengths

What AI & automation may affect

  • Automated underwriting software can evaluate standardized policy applications and routine insurance risks quickly.
  • Data-aggregation tools can automatically pull property records, loss histories, and risk metrics into policy evaluation software.

Human strengths in this job

  • Evaluating unique, complex, or high-value commercial risks that do not fit automated underwriting parameters
  • Negotiating policy terms, pricing, and exclusions collaboratively with insurance brokers and commercial clients
  • Assessing intangible risk factors, management competence, and operational hazards during underwriting reviews
  • Balancing aggressive premium growth targets with disciplined long-term portfolio loss management

How this result breaks down

These are model components, not percentages of the job or of how necessary people are.

AI & digital work73

How much the job involves information, data, writing, analysis or other digital work that AI and software may help with.

Repeatable work51

How much of the work follows regular, predictable or repeated steps.

Physical automation51

How much of the physical work may be suitable for machines or robotics.

Human skills matter49

How much the job depends on judgment, creativity, communication and adapting to real situations.

How is the index calculated?

The Exposure Index is a percentile comparing this job's digital, routine, and physical tasks against all 897 occupations in the Model 2.1 dataset. A score of 84 means higher modeled exposure than approximately 84% of comparable jobs.

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What people in this job commonly do

  • Examine documents to determine degree of risk from factors such as applicant health, financial standing and value, and condition of property.
  • Decline excessive risks.
  • Write to field representatives, medical personnel, or others to obtain further information, quote rates, or explain company underwriting policies.
  • Evaluate possibility of losses due to catastrophe or excessive insurance.
  • Review company records to determine amount of insurance in force on single risk or group of closely related risks.
  • 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.

How we compare jobs

We look at what people do in hundreds of occupations — including digital work, repeatable activities, physical automation and human skills — then compare the job with other occupations.

View full methodology →

What this tool cannot predict

It cannot predict individual job loss, exact technology adoption timing or decisions by an individual employer.

Occupation and data details

O*NET-SOC: 13-2053.00
Career category: Finance
Typical education: Bachelor's degree

Data source: O*NET, U.S. Department of Labor.

This product includes information from the O*NET 31.0 Database by the U.S. Department of Labor, Employment and Training Administration (USDOL/ETA), used under the CC BY 4.0 license. Toolsyte has modified and scored some information; USDOL/ETA has not approved, endorsed, or tested these modifications. O*NET® is a trademark of USDOL/ETA.