AI-based calculators can be tempting because they look fast and “objective.” But they can’t reliably account for the kinds of evidence that typically decide outcomes in Oregon workers’ compensation disputes.
In Keizer, common factors that an AI estimate may underweight include:
- Timeline gaps: Delays between injury, symptom reporting, and first medical documentation can create questions about causation.
- Work restriction accuracy: If your treating provider’s restrictions are vague (or don’t address essential job functions), insurers may argue you were capable of more work than you could actually perform.
- Industrial and commute-related job conditions: Many injuries occur in environments where documentation is split across supervisors, safety coordinators, and medical providers—making it easier for an insurer to challenge the story.
- Earnings proof quality: If your wage loss documentation doesn’t reflect real schedules, shift differentials, or overtime patterns, the “lost wages” portion may be discounted.
The result: an AI range can look reasonable while being disconnected from the evidence your insurer will actually rely on.


