75 resolve issues related to unclear accountability, fragmented responsibilities, or inconsistent decision authority. Where governance roles and escalation pathways are poorly defined, even well‑structured information environments may fail to ensure that circular initiatives are evaluated, approved, and implemented within appropriate risk boundaries (Franks et al., 2021; ICMM, 2020). The increasing use of data analytics and artificial intelligence (AI) introduces additional limitations that warrant careful consideration. While AI‑based methods can support efficiency in data organization, trend detection, and documentation workflows, their outputs remain dependent on the assumptions embedded in models and on the training data used. In tailings management, where rare but high‑consequence failure modes are a central concern, there is a risk that data‑driven approaches may inadequately represent low‑probability, high‑impact scenarios if not complemented by conservative engineering judgment and qualitative risk assessment (Bugayev et al., 2022; Morgenstern et al., 2016). From a technical standpoint, circular economy strategies themselves introduce irreversible interventions in tailings systems. Reprocessing, re‑mining, or modifying disposal methods can permanently alter material properties, hydraulic behavior, and stability mechanisms. Once these changes are implemented, the ability to revert to previous configurations may be limited or nonexistent. This reinforces the need for cautious, stepwise decision‑making and for explicit consideration of uncertainty and long‑term consequences when evaluating circular alternatives (Lottermoser, 2010; Franks et al., 2021). Regulatory and institutional constraints also represent significant limiting factors. The reuse of tailings materials, for example, may be restricted by regulatory frameworks that were not designed to accommodate circular applications. Similarly, approval processes for changes to tailings management strategies may vary significantly across jurisdictions, introducing delays or uncertainties that must be incorporated into decision‑making (Chinchin, 2008; ICMM, 2020). Finally, there is a critical risk associated with the conceptual framing of circular economy initiatives. When circularity is promoted primarily as a sustainability or reputational objective, without equivalent emphasis on engineering feasibility and risk management, there is a danger that such initiatives may be prioritized despite unresolved technical or governance concerns. In the context of tailings management, where failure consequences can be severe, circular economy ambitions must remain subordinate to safety, technical rigor, and regulatory compliance. Taken together, these limitations underscore the importance of viewing digitalization and circular economy strategies as conditional enablers rather than universal solutions. Their effectiveness depends on robust engineering practice, high‑quality data, clear governance structures, and a disciplined focus on long‑term risk management. Recognizing these constraints is essential to ensuring that circular approaches are applied responsibly and in alignment with the fundamental objective of safe and sustainable tailings management.
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