Generative AI is having a profound impact on the property and casualty insurance (P&C) world, promising to save insurers up to $100 billion by cutting claims handling costs and reducing costly “leakage”—when what’s paid out doesn’t match what’s contractually owed. Bain & Company estimates AI could lower loss-adjusting expenses by 20-25% and reduce leakage by a hefty 30-50%. But scaling up successful AI pilots will be key to unlocking this potential, requiring insurers to revamp workflows and adopt fresh tech capabilities.
Claims processing is the core of an insurer’s operations and the biggest cost center too. With inflation, supply chain issues, and climate impacts pushing up expenses, insurers are looking for ways to cut through the chaos. And Generative AI could do just that, by improving payout accuracy, reducing time spent on admin tasks, and even helping adjusters make quick decisions on litigation based on historical case data. A few big players are already testing the waters: Zurich, for instance, is using six years of claims data to refine underwriting with AI, while a South American insurer reports a 50% productivity boost and a potential 40% drop in leakage through AI-powered claims management.
The potential impact of AI spans from customer experience to employee productivity. For example, AI-powered virtual assistants can handle simple customer inquiries, freeing up human agents for trickier cases. AI also enables more accurate payouts by speeding up coverage verification and investigations, reducing manual errors that drive up costs. And for adjusters? AI tools can summarize complex documents in seconds, cutting time spent on mundane tasks and letting them focus on helping customers.
But AI isn’t a silver bullet, and insurers need to tread carefully, cautions the consulting firm.
Accuracy, fairness, transparency, and data privacy are major concerns, especially as AI begins to make more critical decisions.
Insurers should start with high-impact, low-risk cases that benefit from human oversight, like creating claims summaries or assisting with initial customer intake. Over time, they can build up to more complex use cases, such as on-the-job coaching for adjusters or even virtual claims assistants.
Scaling up means going beyond pilots. Insurers can expand AI by replicating proven use cases or by embedding multiple AI tools within a single workflow. For example, integrating AI for call summarization and follow-up tasks can streamline claims adjuster workloads and boost productivity. These approaches reduce the need for “shadow IT” solutions and enable faster, more consistent deployment across the organization.
Generative AI holds massive promise for insurers willing to tackle the challenges head-on. Imagine adjusters instantly accessing full claims histories, or supervisors receiving real-time analytics to improve team performance. With the right calculus, insurers could see competitive advantages that go beyond cost savings.
