Maximizing auto subrogation recovery requires a solution built to handle the full scope of the work. An end-to-end solution enables subrogation teams to manage every referral across all exposures, including PIP, collision, rental and MedPay, from a single system, whether those referrals are automatically detected by AI or flagged manually by a handler. The goal is to automate as much of the workflow as possible, from initial liability assessment through demand generation, so teams spend less time on administrative, repetitive tasks and more time on critical investigations and negotiations that matter.
AI agents can play a central role here, helping teams recover more by improving the accuracy of liability determinations and critically examining supporting evidence, while also reducing the time and expense associated with negotiation and, if needed, arbitration. AI agents provide the capabilities to track recovery progress, document the reasoning and outcomes behind each case, and report on results, giving subrogation leaders full visibility into performance across their entire auto book of business.
Detecting and maximizing subrogation potential is where a strong auto recovery program starts. AI detects and assesses recovery opportunities faster and more consistently than manual reviews. Generative AI (GenAI) interrogates free-form adjuster notes, statements, and police reports to surface subrogation indicators that could easily be missed. Subrogation viability is further assessed by AI applying state negligence laws and relevant statutes of limitations applicable to the situation. The result is more recovery opportunities identified in a fraction of the time it takes a handler to review.
Correctly estimating liability and avoiding rework drive improvements in loss adjustment expenses. Shift AI agents help remove the highly variable and subjectivity of calculating liability. Agents consistently and repeatedly evaluate evidence including points of impact, vehicle movement and statements, and whether the at-fault driver breached their duty of reasonable care and governing rules of the road. This generates precise fault percentages supported by fully explainable and defensible reasoning. As additional investigative information is gathered throughout the claim lifecycle, the liability calculation is updated to incorporate the new information. This continuous reevaluation progressively refines the liability estimate.
Flags a short Statue of Limitation based on a government vehicle involved
Prompts follow-up to secure witness statement
Recommends securing police report before finalizing liability estimate
Efficient and complete recovery preparation is critical to maximizing successful outcomes in auto subrogation claims. AI agents significantly streamline this phase by automating case triage, organizing evidence, and providing data-driven recommendations to strengthen the handler’s position. Shift agents act on all opportunities — manually flagged or automatically detected. To strengthen the recommendation, the agent layers in specifics about the case strength based on the incident details and available evidence. At the same time, additional insight about the adverse carrier is provided. This includes a profile of the adverse carrier behavior — including response timeframes and how they typically negotiate. Similar claims of the same archetype are also profiled. This includes a summary of claims with similar circumstances and the outcomes from those cases. Together, these elements give handlers a clear, evidence-backed basis for deciding how to proceed and how firmly to negotiate.
The creation of a complete, accurate demand package is critical for establishing a strong foundation for successful recovery negotiations. AI agents ensure this process remains objective and consistent, remove reliance on specific handler experience and eliminate potential handler bias from the package composition. Agents build compelling, evidence-backed arguments by pulling together the clear liability reasoning established during review, supported directly by the police report, witness statements, and any other corroborating documentation on file. The demand includes a specific damage request, calculated from the indemnity paid and relevant exposures, so the amount being pursued is fully substantiated rather than estimated.
All supporting documents, such as the police report, statements, photos, and repair or medical records, are automatically compiled and attached to the package, providing the adverse carrier a complete, well organized case. The result is a demand that is ready to send with minimal handler intervention, built to withstand scrutiny and support the strongest possible negotiating position from the outset. Ideally, it eliminates the need to pursue arbitration and avoids filing fees.
Managing many demands in different statuses across multiple adverse carriers presents a significant challenge for subrogation teams. When the adverse carrier responds, often proposing reduced damages or a reduced share of liability, the Shift agent assesses that counter-proposal against the original evidence and case facts to consider whether the reduction is justified or should be challenged. Based on that assessment, the handler can accept the counter-offer or respond with a counter of their own, attaching additional evidence with the assistance of the agent, to strengthen the position where needed. If the two parties cannot reach agreement through this negotiation, the case is escalated to the Total Recovery Solution (TRS) platform for formal arbitration. The agent carries forward the full demand package and evidentiary record avoiding the need to rebuild it from scratch.
Every step of the Shift Subrogation processing workflow offers the opportunity for human intervention, ensuring that the process remains flexible and aligned with the insurer’s standard operating procedures. Whether it’s a verification step for the AI agent, adjusting the demand letter, verifying additional documents to be added, or maintaining full control over each decision, the level of automation is at the discretion of the insurer. These settings are controlled by the insurer and can be tailored to vary based on the specific line of business, providing a seamless balance between automation and expert oversight.
The Shift Subrogation solution empowers insurers to maximize recovery in auto subrogation by leveraging agentic AI to streamline the entire recovery lifecycle — from initial detection and liability assessment to demand package creation and arbitration coordination. Automating workflow steps and providing data-backed, objective guidance for every case, enables subrogation teams to manage higher throughput and boost recovery rates and operational efficiency. This AI-driven approach eliminates the variability and subjectivity associated with handler experience, driving consistent, high-quality outcomes while reducing the need for costly rework. Throughout this process, insurers maintain full control, with the flexibility to define the level of human oversight required across different lines of business.
Learn more about Shift Subrogation.