Human-in-the-Loop AI Becomes Essential in Claims Management Workflows

In insurance claims and litigation workflows, trust is non-negotiable. As AI penetrates document review, triage of losses, and even settlement recommendation, organizations face a key barrier: the reluctance to allow machines to decide alone. Survey data and industry commentary reveal that claims professionals believe AI can significantly boost efficiency—yet adoption remains cautious because of concerns around accuracy, compliance and explainability.

Enter the ‘human-in-the-loop’ (HITL) model. Rather than replacing human judgment, the HITL approach embeds experts at critical junctures—training the models, validating outputs, correcting mis-classifications and taking final decisions. In doing so, it bridges the gap between the speed of automation and the defensibility of human oversight.

For claims adjusters and litigation managers, HITL changes the dynamic: it means the adjuster remains central, empowered by AI rather than replaced by it. In high-stakes environments—catastrophic losses, liability cases, regulatory exposures—the combination of machine speed plus human judgment becomes the operational standard.

Implementation considerations include: identifying where in the workflow human intervention adds most value, building audit trails and explainability to satisfy regulators and stakeholders, designing scalable feedback loops so the AI improves over time, and integrating with legacy claims systems rather than ripping them out. Finally, with a significant share of experienced adjusters expected to retire in the next few years, HITL offers a way to scale institutional expertise even as headcount shrinks.

In short: the future of claims management is not automation versus humans, but automation with humans. HITL is emerging as the trust-multiplier that carriers, TPAs and legal teams need to adopt now if they want to lead in speed, accuracy and defensibility.