AI and advanced analytics are revolutionizing risk modeling, but there’s one big problem—can insurers, regulators, and customers actually trust the outputs? As machine learning models grow more complex, the demand for explainable AI (XAI) is rising. Regulators want clarity, customers want fairness, and insurers need confidence in their risk assessments. This panel brings together actuaries, data scientists, and compliance experts to tackle the biggest challenge in AI-driven insurance: how do we balance predictive power with transparency? Can insurers unlock AI’s full potential without sacrificing trust, ethics, or regulatory approval? The future of AI-driven underwriting and pricing depends on it.