KEYWORDS Responsible acceleration, Data governance, Mining intelligence, Technical assurance, GeoData Quality Management, AI-assisted validation, Reporting 1. CONTEXT The energy transition to low-carbon economies, digitalization, and the geopolitical reorganization of mineral supply chains are driving demand for critical minerals to unprecedented levels. Governments and industries recognize that access to these resources is essential to the shift toward clean energy and to other critical sectors, including defense, aerospace technologies, digital infrastructure, semiconductor-based systems, and, more recently, artificial intelligence (AI). However, as demand accelerates, the development of new mining projects is resulting in progressively slower, more complex, and riskier processes. While this paper focuses on the development of critical mineral projects, the slow pace of new mining project development is similar for other minerals key to economic development. Kulik et al. (2025) estimate that approximately 20% of the global mineral supply required by 2035 remains undiscovered, and that projected demand for several critical minerals is increasing sharply, while a significant portion of future supply remains uncertain. Despite significant technological advances in mineral exploration, modeling, and processing, the average time between discovery and production has increased exponentially over the past few decades. Regulatory processes, environmental complexity, social demands, and technical uncertainties contribute to development cycles that are increasingly longer and more costly. The result is a paradox: the world needs minerals more rapidly, yet projects take longer to reach operation (Noppe et al., 2025). Much of the discussion around accelerating mining projects focuses on permitting, financing, and social acceptance. However, one critical factor remains underestimated: the quality, governance, and reliability of technical information supporting decisions throughout the project life cycle. Inconsistent data, late-stage validations, weak chain of custody, and traceability frequently lead to successive model revisions, scope changes, and loss of confidence among investors, regulators, and stakeholders. Structured and objective assurance systems result in systematic, disciplined processes that improve the effectiveness and efficiency of grade control, reconciliation, Mineral Resource and Reserve risk management, and support good governance. And identify valuable technical improvement opportunities (Noppe, 2017). These deficiencies and operational gaps not only delay technical schedules but also amplify financial, environmental, and social vulnerability. Projects initiated on fragile assumptions are subject to revisions, interruptions, and, in extreme cases, loss of social license to operate. Accelerating projects without fortifying their informational foundations may therefore increase risk rather than deliver value. This work proposes that a key dependency for the responsible acceleration of mineral development is the transformation of technical data into governed, auditable, and reliable decisionmaking assets. The TIME TO MINE (“Time Intelligence for Mining Excellence”) initiative integrates data governance, technical assurance, and artificial intelligence-assisted validation to reduce uncertainty and rework throughout the project life cycle, enabling faster and more reliable decisions. By structuring data and technical decisions under the principles of quality, traceability, and accountability, TIME TO
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