Artificial Intelligence‐Enabled Life Cycle Sustainability Assessment as a Tool for Sustainability Coordination

Firms increasingly use sustainability information based on life cycle assessment, yet coordinated and accountable action requires more than richer assessment. This conceptual article develops a literature‐informed model of artificial intelligence (AI)‐enabled life cycle sustainability assessment (LCSA) as a tool for sustainability coordination in corporate social responsibility and environmental management, corroborating and refining a provisional architecture through a structured integrative analysis of 138 works spanning LCSA, AI and digital assessment, sustainability management, and coordination and accountability research. The model distinguishes assessment, decision support, and coordination, and specifies six recursive coordination movements: signal qualification, cross‐functional interpretation, priority formation, trade‐off and tension handling, responsibility allocation, and follow‐through. It proposes five governance conditions for accountable use, including visibility, contestability, and capacitated ownership, and distinguishes literature‐supported elements from theoretical propositions. AI‐enabled LCSA can support coordinated sustainability action when analytical outputs and the configuration choices behind them remain interpretable, contestable, and connected to organizationalresponsibility.