Corporate adaptation to sustainability uncertainty through artificial intelligence: Textual insights

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Abstract
We examine how sustainability uncertainty influences firms' adoption of artificial intelligence (AI) by assessing whether companies expand their AI-skilled workforce when facing ambiguity in environmental, social, and governance (ESG) conditions. Using the ESG-based Sustainability Uncertainty Index (ESGUI) (Ongan et al., 2025) and the resume-based AI workforce measure (Babina et al., 2024), we provide firm-level evidence on this relationship. Employing fixed effects, matching techniques, and instrumental-variable strategies exploiting exogenous variation in sustainability uncertainty, we find that higher uncertainty leads to a larger AI workforce, consistent with an adaptation hypothesis in which firms strengthen analytical capabilities under ambiguity. The effect is weaker among highly leveraged firms and stronger among firms with greater cash reserves and R&D intensity, indicating that financial flexibility and innovation capacity shape responses to ESG-related uncertainty.