Insurance Policy Clerks
Overall Exposure
2025 vs 2023
Theoretical Exposure
86What AI could do
Observed Exposure
50What AI actually does
Automation Risk Score
72Displacement risk
3-Year Outlook (2025 โ 2028)
Projected changes in AI automation metrics over the next 3 years based on estimated data.
Overall Exposure
2025 โ 2028 (estimated)
Theoretical Exposure
2025 โ 2028 (estimated)
Observed Exposure
2025 โ 2028 (estimated)
Automation Risk
2025 โ 2028 (estimated)
Exposure Metrics (2023 - 2028)
Detailed Metrics Table
| Year | Overall | Theoretical | Observed | Risk | Data Type |
|---|---|---|---|---|---|
| 2023 | 55 | 75 | 32 | 60 | actual |
| 2024 | 63 | 81 | 42 | 66 | actual |
| 2025 | 70 | 86 | 50 | 72 | actual |
| 2026 | 76 | 90 | 57 | 77 | estimated |
| 2027 | 81 | 93 | 63 | 81 | estimated |
| 2028 | 85 | 95 | 68 | 85 | estimated |
Task Breakdown
About This Occupation
If you work as an Insurance Policy Clerk, AI is rapidly transforming your role. With an automation risk of 72/100 and overall exposure at 70%, this role faces very high transformation. The highest-impact area is calculating premiums and processing policy renewals at 90% automation. This is classified as an 'automate' role. BLS projects -6% decline through 2034. The most resilient task is corresponding with policyholders regarding coverage changes (65% automation), where human empathy and nuance remain valuable.
Frequently Asked Questions
With an automation risk score of 72%, Insurance Policy Clerks faces a significant risk of AI-driven displacement. Many core tasks in this role can be automated by current AI systems. However, full replacement is unlikely in the near term -- AI will more likely transform the role rather than eliminate it entirely.
The AI automation risk score for Insurance Policy Clerks is 72% (2025 data). Overall AI exposure is 70%, with 86% theoretical exposure and 50% observed exposure. The risk trend from 2023 to 2025 is +12 points.
The tasks with the highest automation potential for Insurance Policy Clerks are: Calculate premiums and process policy renewals (90%), Verify and enter policyholder data into systems (88%), Process new policy applications and endorsements (82%). These rates reflect how much of each task current AI systems can handle, based on research data from Anthropic and academic sources.
The BLS projects -6% employment change for Insurance Policy Clerks from 2024 to 2034. Combined with an overall AI exposure of 70%, this occupation is experiencing both traditional labor market shifts and AI-driven transformation. Workers should monitor both employment trends and AI capability growth.
Since AI primarily automates tasks in this role, professionals in Insurance Policy Clerks should focus on developing skills that complement AI rather than compete with it. Consider learning AI tool management, shifting toward supervisory and quality-control tasks, and building expertise in areas where human judgment remains essential.