2451 Anglo American Quellaveco, the opportunities offered by the AI-enabled territorial diagnostic platform and digital twin models of mining territories within the shared value creation strategy are not yet being fully utilized. Table 1 – Case Positioning Matrix for Smart Mining Territories Case selection Components of the Proposal Multi-stakeholder governance coalitions AI-enabled territorial diagnostic platforms + Digital twin models of mining territories Outcome= Smart mining territories High impact in terms of territorial development Peru: Cerro Verde-Freeport McMoran, Antamina, Anglo American-Quellaveco, San Rafael-Minsur, Comité de Monitoreo Quellaveco (CMQ) and RIMAY* Chile: SQM Lithium, Minera Los Pelambres-Antofagasta Minerals, Institucionalidad Minera: Alianza Valor Minero and Alta Ley* Brazil: CarajásVale Peru: Anglo AmericanQuellaveco Model: Territorial Development and Sustainable Balanced Scorecard (TD-SBSC)** Social-innovation practice Data-driven territorial Development approach Peru: -Anglo AmericanQuellaveco * Public Policy Cases ** Extended SBSC model proposed in this paper, building on Kaplan and McMillan 4.1 Cases Cases were selected using three criteria: (1) high territorial-development impact (i.e., a demonstrably positive legacy and improved wellbeing outcomes), (2) social-innovation practice, understood as the design and implementation of novel (or significantly adapted) solutions co-created with local actors to address persistent territorial challenges and strengthen social outcomes; and (3) a data-driven territorial development approach, meaning the systematic use of data, indicators, and analytical tools (e.g., monitoring systems, dashboards, diagnostics, or modelling) to inform decisions, prioritize interventions, and track territorial results. Cases were required to meet at least two of the three criteria, ensuring that each case offered substantive evidence relevant to the TD-SBSC while avoiding the exclusion of initiatives that are exemplary in different ways (e.g., strong governance coalitions but still-emerging advanced analytics, or vice versa). This rule supports meaningful cross-case learning by preserving heterogeneity—across countries, corporate versus policy initiatives, and varying maturity levels—while maintaining a shared baseline of relevance to territorial outcomes, innovation capacity, and data-enabled governance. The selected set is therefore emblematic and intentionally non-random, designed to surface practical lessons, gaps, and enabling conditions for a forward-looking mining agenda. Complementing the matrix, a brief description of the key characteristics of the 10 successful cases meeting the criteria is presented below. At the corporate level, Peru includes Cerro Verde, Antamina, Anglo American-Quellaveco (which also encompasses the CMQ case) and Minsur; Chile includes Minera Los Pelambres and SQM Lithium Ventures; and Brazil includes the company Vale. At the public policy level, RIMAY in Peru, and the Mining Institutional Framework in Chile- Alianza Valor Minero and Alta Ley.
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