70 Recent developments in digital information management have focused less on automation and more on structure, continuity, and decision traceability. Advancements such as standardized data models, version control, change‑management records, and lifecycle‑based documentation support transparency and accountability, which are fundamental to both circular economy initiatives and tailings governance frameworks (Franks et al., 2021). These characteristics are especially important where tailings strategies evolve through multiple design, operational, and closure phases. The growing application of data analytics and artificial intelligence (AI) techniques in mining and infrastructure management has further contributed to improving efficiency in handling complex and large datasets. Academic studies describe the use of AI‑based methods to support data validation, trend recognition in monitoring systems, classification of technical documentation, and synthesis of information for reporting purposes (Bugayev et al., 2022; Kinnunen et al., 2022). These applications are primarily associated with efficiency gains in data organization and documentation workflows, reducing the time required for information consolidation while improving consistency and data quality. Importantly, the literature also cautions that digitalization does not replace engineering judgment, nor does it define acceptable risk thresholds or decision outcomes. Integrated systems and analytical methods function as facilitators, providing a structured and auditable information base that enables competent professionals to apply engineering expertise and governance processes consistently and transparently (Morgenstern et al., 2016; ICMM, 2020). When applied within this boundary, digitalization supports the alignment of circular economy objectives with technical rigor, disciplined risk management, and robust governance throughout the lifecycle of tailings facilities. 5. ALIGNMENT WITH GOVERNANCE FRAMEWORKS AND GISTM PRINCIPLES The increasing adoption of circular economy strategies in tailings management has reinforced the need for governance structures capable of ensuring that innovation does not compromise safety, accountability, or long‑term risk management. International governance frameworks, particularly the Global Industry Standard on Tailings Management (GISTM), provide a structured reference for aligning technical decision‑making with corporate responsibility, transparency, and societal expectations (ICMM, 2020). The GISTM emphasizes a lifecycle‑based approach to tailings management, grounded in clear accountability, technical rigor, and risk‑informed decision‑making. Its principles explicitly require that decisions affecting tailings facilities, whether related to design, operation, modification, or closure—are supported by competent technical evaluation, are transparently documented, and are aligned with the organization’s risk tolerance and governance structures. Circular economy initiatives, which often involve modifications to existing tailings systems, therefore fall directly within the scope of GISTM governance expectations. One of the core challenges in aligning circular tailings strategies with governance
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