Digital Transformation and Generative AI for Sustainable Decision-Making in Mining - SME Annual Meeting 2026

Mining operations are increasingly data-rich yet decisionconstrained. Fragmented systems, variability in geology and operations, and sustainability obligations create multiobjective trade-offs that classic analytics cannot reconcile at operational tempo. This paper proposes an end-to-end framework that fuses digital transformation practices (governed data platform, semantic layer, feature store, and MLOps) with generative AI (retrieval-augmented generation, tool-use, and agentic workflows) and decision intelligence (simulation/digital twins and multi-objective optimization). We formalize sustainability-aware objectives, define a practical stack and governance controls, and demonstrate how an AI “decision copilot” can surface options, quantify trade-offs, and document rationale. Two figures illustrate a production-grade architecture and a Pareto frontier for cost–emissions trade-offs; two tables operationalize decision-domain mapping and a transformation maturity rubric. The approach is product- and company-agnostic.