Artificial intelligence policy uncertainty and corporate Greenwashing: Evidence from China

While the economic consequences of general policy uncertainty are well-documented, little is known about how uncertainty surrounding the governance of transformative technologies like Artificial Intelligence (AI) shapes corporate non-market strategies. This study investigates whether and how AI Policy Uncertainty (AIPU) drives corporate greenwashing. Using a large panel of Chinese listed firms from 2010–Q1 2025 and a novel text-based index of AIPU, we establish a causal link through a multi-pronged identification strategy that includes Propensity Score Matching (PSM), a multi-period Difference-in-Differences (DID) design, and an Instrumental Variable (IV) analysis. We find robust evidence that AIPU significantly increases corporate greenwashing. Crucially, this effect is attenuated for firms led by CEOs with strong IT backgrounds, who can better navigate technological turbulence. We further unveil the micro-foundations of this effect, showing that AIPU fuels greenwashing through three distinct mediating pathways: splitting managerial attention toward external risks (a cognitive channel), increasing precautionary cash holdings (a financial channel), and directly inhibiting substantive green innovation (a strategic channel). Heterogeneity analysis also shows the effect is more pronounced for non-state-owned enterprises and non-high-tech firms. Our findings reveal an important unintended consequence of technology governance and offer crucial insights for managers, investors, and policymakers. • We develop a textual AI policy uncertainty (AIPU) index, distinct from general economic policy uncertainty. • AIPU significantly heightens corporate greenwashing, exposing a key risk of technology governance. • AIPU drives greenwashing through attention split, higher cash holdings, and reduced substantive green innovation. • CEOs with IT background weaken AIPU’s effect on greenwashing, showing tech expertise buffers uncertainty.