The Future of Skills in the Insurance Industry

    Automation may replace up to 23% of insurance industry jobs in 5 years, highlighting the importance of rethinking necessary skills and critical roles for success.

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    Skills Transformation in the US Insurance Industry

    Within the next five years, the insurance landscape in the United States is poised for a profound transformation. Automated technologies are expected to replace as much as 26% of the insurance workforce, necessitating a swift and comprehensive reevaluation of critical skills and roles to ensure long-term success.

    In this report, you will discover:

    • Digital Transformation Enablers: Gain insights into the enablers of digital transformation in the insurance industry, including pivotal roles like Software Application Developers, Computer and Information Systems Managers, Software Quality Assurance Engineers, Information Security Analysts, Network and Computer Systems Administrators, and Project Management Specialists.

    • Workforce Priorities: Explore the emerging priorities in the insurance workforce, emphasizing skills in customer-centricity, data, ethics, and quality. Discover how continuous learning, goal orientation, and customer service capabilities will empower employees to thrive in the era of digital transformation.

    • Key Upskilling Requirements: Identify the top four expected upskilling requirements by 2028, focusing on Achievement Focus, Personal Learning and Mastery, Customer Focus, Agility, and Collaboration.

    • Emerging Insurance Skills: Examine the skills that are rapidly gaining importance in the job market and understand how they align with insurers' priorities for enhancing customer experiences and optimizing organizational performance.
    • Core Capability Upskilling: Learn about the five core capabilities that the US insurance workforce will need to majorly upskill by 2028, including Achievement Focus, Personal Learning and Mastery, Agility, Collaboration, and Customer Focus.

    Download the report below.

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