Compare roles · AI exposure side by side
Claims Adjusters and Examiners
Put up to three roles next to each other: the exposure figure, the inputs behind it, the window, what is driving change, and where the work moves. Every figure comes from the same method, so the gap between two scores means something.
Exposure
Window · adoption
until most of the change has landed
High adoption
In one line
Photo-based estimating, straight-through processing and AI triage are automating routine claims, leaving adjusters the complex, contested and human cases.
Inputs behind the score · scaled 0–100
Task applicability
41Observed usage
11Official exposure tier
100Labour-market trajectory
n/aPublished adoption rating
70Editorial adjustment +4
What is driving it
- Photo-based damage estimation
- Straight-through processing
- Predictive triage and fraud scoring
- Document extraction and file summarisation
- Claimant expectations for speed
- Expense-ratio pressure
Skills worth building
- Liability investigation
- Negotiation and settlement
- Model oversight and audit
- Medical and repair literacy
- Claimant communication
- Regulatory knowledge
Tools in the work now
Where the work moves
More exposed
Different skills, growing
Complementary, less exposed
Full report
Scores are the CareerGuard Exposure Index v2: the same five inputs and weights for every role, so a gap of ten points means the same thing wherever it appears. How scores are built.