AI tools generally work by comparing your inputs (injury type, treatment timeline, missed work, and limitations) to patterns from other claims. That can create a comforting sense of clarity.
The problem is that Greenwood cases often turn on issues that an AI prompt can’t fully capture—like:
- When symptoms were first reported (and whether the timeline matches early medical notes)
- Whether treatment was consistent after the workplace incident
- How job restrictions were documented when you tried to return to work around your regular route/shift demands
- Whether wage loss is supported with records that reflect your real earnings
If the insurer believes those pieces are incomplete or inconsistent, they may value the claim lower—even if an AI estimate looks reasonable at first glance.


