Keywords
AI
ESG
ESG Performance
RLR
How to Cite
Abstract
This exploratory study examines the relationship between artificial intelligence (AI) and corporate ESG performance. It considers both the positive impacts and potential limitations of AI deployment for ESG outcomes at the firm level, identifying key moderating variables through the lens of the Dynamic Capabilities Framework (DCF). A rapid literature review (RLR) was conducted, supplemented by a snowball search focused on Q1 and Q2 journal publications. The findings indicate a predominantly positive relationship between AI and firm-level ESG performance. The mechanisms through which AI contributes to ESG outcomes cluster around three interrelated domains: firm-level capabilities and characteristics; technological and operational mediators; and regional and contextual factors. Key contributions of AI include improvements in data processing and information governance, innovation, mitigation of greenwashing, facilitation of digital transformation, enhanced ESG operational efficiency, and stronger internal control mechanisms. However, the effectiveness of AI in improving ESG outcomes remains highly context dependent. This study contributes to the growing discourse on AI-enabled ESG transformation by offering a structured synthesis of existing research and outlining a future research agenda.
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