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Case Study 4.9

Adoption Barriers in Explainable AI for Insurance Underwriters: Post-Pandemic Lessons

22
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Harvard
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~ 23–33 mins
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AIOps CV Marketing
Abstract

This case study investigates “Adoption Barriers in Explainable AI for Insurance Underwriters: Post-Pandemic Lessons” using a time-series forecasting. Through a economic lens, the analysis integrates multi-source data to derive a validated measurement model for researchers and practitioners.

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Adoption Barriers in Explainable AI for Insurance Underwriters: Post-Pandemic Lessons

ABSTRACT
Adoption Barriers in Explainable AI for Insurance Underwriters: Post-Pandemic Lessons is unpacked across themes: risks, governance, usability, and KPIs. Limitations and future research paths are noted.
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