P&C
Agentic AI
Research

Consistency as empathy: how agentic AI restores trust to bodily injury claims

The landscape of casualty claims is undergoing a seismic shift. Specialized legal AI platforms, such as EvenUp, Eve, Supio, and Darrow, have raised $682 million to automate demand packages and maximize settlements. At the same time, bodily injury claims have become a larger share of auto claims, growing annually by an average of 5.9% since 2023. The traditional playbook - reliant on rigid matrices, manual review bottlenecks, and delayed communications - fails to keep pace, widening a trust deficit that is driving claimants into legal representation.

With agentic AI, carriers are empowered to restore claimant trust through consistency, protecting against indefensible litigation backlash. Shift Technology’s ARISE framework defines five levels of AI agent capability: Answers, Recommends, Initiates, Solves, and Exceeds. This paper, co-authored by Razors Edge Consulting, applies the ARISE framework to bodily injury claims management. Rather than replacing human judgment, the Shift Injury agent equips adjusters with transparent settlement rationale and next-best actions, enabling them to “act in person” with speed, clarity, and empathy.

 

Download the paper to learn how Shift's AI agents allow carriers to

  • Act with speed: Integrated directly into the intake workflow, Shift’s AI high-risk files are on the adjuster’s dashboard, accelerating time-to-contact and enabling carriers to establish proactive, empathetic engagement.

  • Act with accuracy: Shift’s solution deploy specialized agentic capabilities to execute complex background data interrogations and provide consistent recommendations on liability, medical record review, compensation, and attorney analysis for adjuster review.

  • Act in person: Equipped with verified facts, clear liability allocations, and attorney insights, adjusters can conduct empathetic, direct conversations that build trust and achieve fair, final resolutions faster.
    Download the paper to learn how AI agents