AI is transforming insurance operations across the value chain. Claims automation: 1) Computer vision for auto claims - analyze photos of vehicle damage to estimate repair costs (CCC One, Mitchell) with 94% correlation to human assessors. 2) NLP for claims document processing - extract relevant information from medical reports, police reports, invoices. 3) Straight-through processing: AI auto-approves straightforward claims (<$5000, clear liability) - 30-40% of claims handled without human intervention. Fraud detection: network analysis identifying rings of claimants, medical providers, and attorneys in coordinated fraud schemes. Anomaly detection on claim patterns vs historical baselines. Underwriting: gradient boosted trees for risk scoring using 100+ variables - telematics data for auto insurance, satellite imagery for property, wearable data for life insurance. Behavioral economics: AI-driven pricing personalization balancing risk and retention. Customer churn prediction: 6-month advance notice of high-risk renewals for proactive retention interventions. Regulatory challenge: many jurisdictions restrict use of certain variables (race, zip code proxies) requiring careful feature selection and bias auditing.