Objectives to cover:

• Introduction – Overview of machine learning’s role in insurance recovery post-pandemic.
• Impact of the Pandemic on Insurance – Challenges faced by the insurance sector due to COVID-19.
• Evolution of Machine Learning in Insurance – Transition from traditional to AI-driven models.
• Key Machine Learning Applications – Uses in claims processing, risk assessment, and customer retention.
• Challenges and Ethical Considerations – Issues like data privacy, bias, and regulatory compliance.
• Industry Case Studies – Examples of successful AI-driven recovery strategies in insurance.
• Future AI Trends in Insurance – Integration with blockchain, IoT, and emerging technologies.
• Policy and Regulatory Implications – The need for frameworks ensuring responsible AI adoption.
• Conclusion – Summary of findings and recommendations for AI-driven insurance recovery.

Reference:  IEEE style