Kennewick families often come to us after incidents where the early details are incomplete—common when a fatality happens quickly after a collision, when multiple agencies respond, or when technical evidence must be interpreted (vehicle data, medical causation, workplace procedures).
AI tools typically try to produce a “range” by using generalized assumptions. That range can be off when:
- Fault is disputed (for example, arguments about lane position, speed, following distance, or distraction at intersections and merges)
- Causation is complex (especially when injuries worsen over time or involve multiple contributing factors)
- Insurance coverage is uncertain (who is insured, what policy limits apply, and whether coverage is contested)
- Damages are not fully documented yet (funeral invoices, lost wages, benefit impacts, and related expenses)
In other words, an AI estimate may generate numbers—but it can’t evaluate whether Kennewick-area evidence will actually support the claim.


