Artificial Intelligence (AI) and Responsible Distribution: Reconciling Enhanced Performance and Environmental Impact

Stephen Hawking’s statement, “The creation of artificial intelligence (AI) would be the biggest event in human history. But it could also be the last,” perfectly illustrates the ambivalence of AI: on the one hand, a driver of economic performance; on the other, an environmental threat. In both retail and finance, it opens opportunities to reduce greenhouse gas emissions, but it also generates rebound effects, notably due to the high energy consumption of data centers and batteries (Giudici & Wu, 2025).

In large-scale retail, the magnitude of the challenge is evident: Scope 3 emissions account for 96% of Auchan’s carbon footprint and 98% of Carrefour’s and Lidl’s. As Nobel Prize-winning economist William Nordhaus stated in 2018, “Mankind is playing dice with the natural environment through a multitude of interventions.” The Paris Agreement (COP21) and COP26 highlight the urgency of concrete action to reduce emissions at both national and corporate levels.

AI can nevertheless be a powerful lever: optimizing production and supply chains (Viswanathan, 2024; Rovčanin, 2025), setting up collection points for upcycling, and collaborative platforms to curb waste. It also reshapes the customer experience: virtual try-ons, service robots, hyper-personalized recommendations—all innovations that reduce product returns and strengthen loyalty.

In finance, the paradox is similar. AI improves household decision-making through robo-advisors (Singh & Kumar, 2025), helps identify virtuous companies, and refines ESG scores, thereby reducing some risks of greenwashing (Dreyer & Smith, 2024). At the same time, it interacts with emotions triggered by climate change—so-called eco-emotions such as eco-anxiety—that influence investment choices. The warm glow effect leads some investors to favor green assets, even when less profitable, for the moral satisfaction they provide (Dreyer et al., 2023). Meanwhile, climate and regulatory risks increase both the cost and risk of corporate financing. In the short term (lead), investors may favor foreign projects, often less green, to secure quick returns. However, natural disasters and global warming make such long-term investments riskier. Consequently (lag), investors increasingly turn toward sustainable, local, long-term projects and loans, both to secure their portfolios and to support the ecological transition.

This call for papers invites researchers in marketing and finance to reflect on the overarching theme of the study day: How can we reconcile enhanced economic performance with environmental impact in the age of AI?