Building trust and AI governance

AI is rapidly becoming a core component of mining operations. It is being deployed to support exploration and improve discovery rates by using machine learning to analyse large datasets and identify hidden mineral signatures. Self-driving haulage trucks are also increasingly being used on sites, helping to reduce fuel consumption and wait times. Likewise, AI is being used to support predictive maintenance to increase equipment reliability. AI-powered ore sorting systems are now also being deployed to distinguish valuable minerals from waste rock in milliseconds.

Investors and customers are demanding that companies prove their AI systems are trustworthy, transparent, and responsible. Venture capital and procurement decisions are increasingly prioritising companies that can demonstrate robust AI governance and ethical practices. Organisations must therefore treat AI trustworthiness and transparency as a strategic priority.

‘Trust by Design’ calls for governance and continuous assurance across the entire AI lifecycle, proactively engineering trust into AI systems from day one, rather than retrofitting it later. The ISO/IEC 42001 framework provides a concrete framework to meet those challenges by establishing, implementing, maintaining, and continuously improving an AI management system. Rather than prescribing specific technical solutions, it outlines what processes and controls need to be in place for responsible AI management. In addition, the companion standard ISO42005 helps organisations systematically evaluate, document and manage the potential benefits and risks of AI on individuals, groups and society across the entire lifecycle.

This provides a holistic governance framework, ensuring that an organisation addresses all the key dimensions of trustworthy AI: ethical use, risk management, security/ privacy, transparency, human oversight, and compliance. This set of requirements and certification by an accredited body externally validates an organisation’s commitment to trustworthy AI and adherence to international best practices.

Mining companies already familiar with implementing ISO standards will find a common high-level structure, including clauses on context, leadership, planning, support, operation, performance evaluation, and continual improvement, allowing easy integration with existing corporate governance systems. For the mining industry, ISO/IEC 42001 integrates seamlessly with ISO 9001 (Quality management), ISO 14001 (Environmental management), and ISO 45001 (Occupational health and safety).

These standards support flexible, needs-based integration into existing processes. However, organisations must establish concrete and effective measures for controlling and monitoring AI, not just during deployment but throughout the whole AI lifecycle. Otherwise, the AI management system remains a paper tiger – in theory it may look good, but in practice it has no effect.

AI risk differs significantly from traditional risk because AI systems are probabilistic, not deterministic. AI, systems learn and adapt, which introduces ‘emergent properties’ that can be hard to predict. The ISO/IEC 42001 structure addresses AI technical controls, and the organisational processes and cultural elements required for trust. Its key components – governance, impact assessment, risk management, security, oversight, third-party management, incident handling, and improvement – provide a multi-dimensional assurance framework. Implementing ISO/IEC extends beyond compliance, as building trustworthiness into their AI systems and processes, companies can achieve strategic, financial, and operational advantages.

Implementing Trust by Design goals with ISO/IEC 42001 should be approached as a clear sequence of steps, as a change programme involving people, processes, and technology. The implementation pathway goes beyond achieving a certification tick-box, to embedding a sustainable capability for trustworthy AI. This will allow organisations in the mining industry to confidently pursue AI innovations.

However, ISO/IEC 42001 adoption does not need to happen all at once, as a phased approach can yield quick wins and lessons that inform a broader rollout. Many organisations therefore start with a pilot project or focus on a high-impact AI system to develop the governance approach, subsequently scaling it across other projects.

Read the article online at: https://www.globalminingreview.com/special-reports/06032026/building-trust-and-ai-governance/