Abstract
<jats:p>Artificial intelligence (AI) has quickly become a technology that shapes both environmental systems and the way labor market’s function. This chapter examines these two sides together, because AI can support sustainability goals while also creating new risks. On the environmental side, AI helps with predictive maintenance, improves circular-economy practices, strengthens the integration of renewable energy, and offers better tools for forecasting climate-related threats. Still, these gains come with clear costs. Data centers require large amounts of electricity and water, and the production of advanced hardware relies on resource-intensive supply chains. In some cases, efficiency improvements even trigger rebound effects that offset the environmental benefits. The labor market is also undergoing a noticeable shift. AI speeds up automation in routine tasks, which puts pressure on workers in administrative and mid-skill occupations. At the same time, it opens new roles in areas such as AI ethics, algorithm auditing, and human-machine collaboration. These developments do not affect all groups equally. Differences in digital skills, gender, region, and socioeconomic background can widen existing inequalities. For this reason, the idea of a “just transition” has become central, emphasizing policies such as reskilling programs, income-support mechanisms, and more inclusive innovation strategies. The chapter also discusses governance challenges. While frameworks like the EU AI Act, the OECD Principles, and various responsible AI guidelines try to set clearer rules, countries still take very different approaches, especially on issues such as data control and cross-border information flows. These differences reflect broader geopolitical tensions and influence how benefits and burdens are distributed. Overall, the chapter highlights the need for evidence-based policies that align ecological sustainability, fair labor outcomes, and balanced global governance.</jats:p>