In sustainability, AI becomes relevant where complexity must be made visible: data quality checks, anomaly detection, scenario analysis, supply chain risk assessment, regulatory classification, semantic structuring of sustainability information, and the interpretation of large, fragmented data spaces. This Expert View explores how AI is evolving from a productivity tool into a decision-support and steering system for sustainability. The PAC / Zeo2GoX Expert Session on AI in Sustainability already frames this shift clearly: AI becomes valuable in sustainability when it supports steering, risk analysis, and decision-making — and when trusted data, governance, and process integration are treated as prerequisites, not afterthoughts.
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