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Policy Brief 4.4

Adoption Barriers in Explainable AI for Regulated Utilities: A mixed-methods case study

14
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IEEE
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~ 14–22 mins
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AIOps Green Finance Marketing
Abstract

This policy brief investigates “Adoption Barriers in Explainable AI for Regulated Utilities: A mixed-methods case study” using a survey-based structural equation modeling. Through a economic lens, the analysis integrates multi-source data to derive a practical decision framework for researchers and practitioners.

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Adoption Barriers in Explainable AI for Regulated Utilities: A mixed-methods case study

ABSTRACT
Adoption Barriers in Explainable AI for Regulated Utilities: A mixed-methods case study is unpacked across themes: interoperability, ethics, change enablement, and equity. Limitations and future research paths are noted.
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