by Rob Berg, Director, Applied AI, Perr&Knight
Artificial intelligence holds tremendous potential for insurance companies, promising gains in efficiency, decision-making accuracy, customer experience, and competitive positioning.
For many insurers, however, the path to realizing these benefits remains unclear. Common roadblocks include uncertainty about where exactly to start, how to prioritize initiatives, and how to manage the technical, operational, and regulatory challenges that accompany AI initiatives.
To address these challenges, Perr&Knight has published its AI Adoption Framework for Insurance Companies, a comprehensive guide developed by the experts at our actuarial consulting firm, designed specifically to support insurers through every phase of AI adoption.
This resource helps to demystify artificial intelligence enablement by providing the structure needed to pursue initiatives for AI use in insurance with confidence and clarity.
The Framework is built on an eight-phase methodology:
Phase 0: Strategy Alignment In this initial phase, we establish clear objectives and strategic fit to ensure AI initiatives contribute meaningfully to your mission and vision.
Phase 1: Process Inventory A process inventory identifies and categorizes core, supporting, and management processes to determine where AI-driven process improvements can deliver the most value.
Phase 2: Workflow Modeling Models that detail process endpoints, activity sequences, and decision points provide a visual guide that helps us to zero in on high-impact AI use cases.
Phase 3: Solution Design By documenting functional and technical requirements, we can assess organizational readiness by identifying gaps between current and envisioned process outcomes. Simulation analyses that compare current and future state workflows help validate that the designed solutions are practical and scalable.
Phase 4: Risk & Governance Conducting a thorough examination of ethical, regulatory compliance, and AI governance considerations is a critical feature of our framework that helps to proactively manage risks surrounding the use of AI in insurance.
Phase 5: Implementation The implementation phase involves detailed planning, resource allocation, vendor coordination, and risk mitigation to support the successful execution of AI solutions and improve the likelihood of beneficial outcomes from those solutions.
Phase 6: Deployment & Change Management A too-often overlooked aspect of transformation efforts, solution deployments must involve communication, stakeholder engagement, training, and support functions to promote widespread adoption of the AI-based solutions.
Phase: 7 Monitoring & Continuous Learning Continuous monitoring of performance measures (including cost, productivity, morale, and ROI resulting from AI-enabled improvements) combined with user feedback, ensures that AI solutions are frequently reevaluated to meet your organization’s changing needs.
The Framework is not a theoretical model–it offers a practical, actionable approach to AI adoption that extends familiar business process management techniques with artificial intelligence to improve an insurer’s operations across multiple dimensions: internally among employees, and externally to benefit customers. By following this structured methodology for applying AI in insurance, companies will:
Whether you’re simply contemplating the benefits of AI in insurance or seeking to scale early successes, Perr&Knight’s AI Adoption Framework offers a roadmap that’s familiar, easy to implement, and highly effective at supporting beneficial outcomes because it is backed by an experienced team of actuarial consulting and business process experts.
For insurance leaders seeking to navigate the often-confusing AI landscape with clarity and confidence, this guide is an essential resource.
Download the eBook to learn how Perr&Knight can help your organization turn AI potential into measurable business results.