This article explores the multifaceted implementation of artificial intelligence in insurance claims processing, examining both transformative successes and persistent challenges. It analyzes how AI technologies automate workflows, enhance fraud detection capabilities, improve customer interactions, reduce processing errors, and accelerate claim settlements. The discussion extends to critical implementation barriers, including legacy system integration difficulties, algorithmic bias concerns, resource constraints for smaller insurers, model explainability issues, and regulatory compliance challenges. By providing a balanced technical assessment of current applications alongside practical solutions for common obstacles, this article offers insurance professionals a comprehensive framework for navigating AI adoption decisions while maintaining ethical standards and stakeholder trust.
Keywords: Fraud Detection, algorithmic transparency, claims processing, ethical AI, insurance automation
