From Intelligence to Impact: Associations Between AI Maturity and Corporate Sustainability Performance Across Industries

Despite growing interest in artificial intelligence (AI) as a sustainability capability, evidence of its association with distinct environmental, social, and governance (ESG) outcomes remains inconclusive. Grounded in the Resource-Based View, Natural Resource-Based View, and stakeholder and institutional perspectives, this study examines IMD AI-maturity scores and Refinitiv ESG ratings for 119 large firms across ten industries. Hierarchical ordinary least squares regressions adjusted for industry, with HC3 robust inference, multiple-testing corrections, influence diagnostics, and industry interaction tests. AI maturity showed no statistically significant association with overall ESG (B = 0.121, p = 0.087) or Governance (B = −0.002, p = 0.986). Positive Environmental (B = 0.222, p = 0.019) and Social (B = 0.200, p = 0.022) associations did not survive Holm correction (adjusted p = 0.077); the Environmental finding was sensitive to an influential observation. Industry moderation was not detected (F(9,99) = 0.494, p = 0.876), although small sector samples limit precision. The study contributes by distinguishing aggregate from pillar-specific AI–ESG relationships and testing their sensitivity to alternative inference procedures. Theoretically, the findings qualify expectations that digital capabilities uniformly translate into sustainability advantages; practically, they favor evaluating AI investments using distinct, directly observed sustainability indicators rather than presuming broad ESG gains.