Industry Primer for Insurance: Technology, Innovation, and AI
1h 40mBeginner2026-07-27
Authors

Starweaver
Course details
This industry primer builds the technology fluency consultants need to work with insurance clients. Get grounded in the core systems that run insurance operations, from policy administration and claims through underwriting, distribution, CRM, and actuarial platforms. Then see how cloud adoption is reshaping these systems, and how workflow automation and enterprise data platforms are driving digital transformation across underwriting and claims operations.
Move on to AI use cases in insurance, including pricing, fraud detection, retention, and embedded insurance products. Look at the risks that come with them, from bias and explainability challenges to model governance under regulatory scrutiny. Finish with a look at emerging technologies like telematics and insurtech partnerships, and at where consulting opportunities sit in AI strategy, modernization, data strategy, and automation.
Move on to AI use cases in insurance, including pricing, fraud detection, retention, and embedded insurance products. Look at the risks that come with them, from bias and explainability challenges to model governance under regulatory scrutiny. Finish with a look at emerging technologies like telematics and insurtech partnerships, and at where consulting opportunities sit in AI strategy, modernization, data strategy, and automation.
Concepts
Introduction
- Getting started
Technology Landscape Overview
- Core systems and the industry tech stack, part 1
- Core systems and the industry tech stack, part 2
- Infrastructure and security considerations
- Emerging technology trends and adoption patterns
Digital Transformation Trends
- Cloud, automation, and the role of data
- Transformation challenges and customer experience
AI and Advanced Analytics in the Industry
- Decision intelligence and AI maturity
- AI use cases and associated risks, part 1
- AI use cases and associated risks, part 2
Innovation and Emerging Technologies
- Emerging technologies and innovation models
- Platform shifts and ecosystem change
Technology Challenges and Risks
- Legacy constraints and data quality
- Security, compliance, and change management
Consulting Opportunities in Tech and AI
- Data strategy and automation initiatives, part 1
- Data strategy and automation initiatives, part 2
Conclusion
- Course wrap-up