Artificial Intelligence and the twin transition: the good, the bad, and the ugly

Artificial Intelligence (AI) is the critical test case for the twin transition, the interplay of the digital and the green transformation, as it can reduce but also increase negative environmental effects. By synthesising recent advances, this paper develops an integrative firm-level understanding of AI’s role in the twin transition. First, we propose a typology of effects through which AI shapes environmental outcomes: efficiency and footprint effects, prebound and rebound effects, and unlocking and path-escalating effects. Second, we show that these effects are not properties of AI itself but emerge from how firms choose to manage interactions between effects strategically. To nuance the interplay of effects and strategic choices, we develop and illustrate three AI adoption configurations: sustainability-amplifying, productivity-stabilising, and harm-amplifying AI adoption. Our paper offers new research avenues on AI and environmental sustainability as well as actionable guidance for managers and policymakers seeking to steer AI deployment towards sustainable effects.