Governing Environmental Decisions with Artificial Intelligence: Algorithmic Sustainability for Accountability and Lifecycle Impact, a Policy Review

Artificial intelligence is increasingly incorporated into public environmental decision-making processes, directing the classification of risks, the distribution of resources, and the implementation of regulatory measures. Current policy discussions tend to emphasize predictive performance and ethical principles. Institutional conditions play a lesser role in determining the decision authority of algorithm-generated outputs. This policy review bridges this gap by examining environmental artificial intelligence as part of administrative decision processes rather than as neutral analytical software. Building on recent work on algorithmic sustainability, the review assesses how existing governance instruments engage with lifecycle environmental impacts, organizational responsibility, and procedural legitimacy. The analysis of international frameworks indicates that transparency and risk-based governance are receiving increasing attention, particularly in relation to their effectiveness in addressing environmental concerns and ensuring accountability in AI applications. At the same time, lifecycle environmental impacts remain weakly integrated into decision justification and oversight, which undermines the effectiveness of governance frameworks in addressing the environmental impacts associated with AI technologies. To overcome this limitation, the paper proposes a way of examining how artificial intelligence is integrated into decision processes. The results show that effective governance depends on aligning institutional design with sustainability objectives at the points where algorithmic outputs affect public decisions.