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Standards Development
This project will develop a guidance document that supports occupational health and safety professionals in understanding, questioning, and overseeing the use of Artificial Intelligence (AI) systems in the workplace. The scope covers the practical aspects that OH&S practitioners need in order to interact confidently with AI-enabled tools, assess their suitability, and challenge vendors, internal technical teams, or decision-makers where necessary.
The document will include:
• The key concepts, behaviours, limitations and predictable failure modes of AI systems used in OH&S contexts,
• The organisational processes that allow OH&S professionals to scrutinise AI applications, including governance, risk identification, human oversight, ethical considerations, transparency, and data quality.
• The types of questions, checks, and lines of enquiry OH&S professionals should use when engaging with vendors, IT specialists, data teams, and leadership.
• The integration of AI considerations into existing OH&S management system structures (e.g., ISO 45001, ISO 45003, ISO/IEC 42001),
• Practical examples and scenarios to illustrate how AI might behave in real workplaces,
The guidance will not cover:
• Technical development of AI models or machine learning engineering practices.
• AI applications outside occupational health and safety.
• Consumer AI products or medical/diagnostic AI tools.
Project type: New guidance standard, designed to support competent professional judgement, not to create new technical requirements for AI design.
The purpose of this work is to give health and safety professionals the practical understanding and confidence they need to ask informed, intelligent questions about AI systems used in the workplace. As AI becomes more common in safety related applications, OH&S professionals must be able to challenge assumptions, understand risks, test vendor claims, and ensure that AI supports rather than replaces competent human judgement.
This guidance will help practitioners:
• Understand what AI can and cannot do in an OH&S context.
• Identify the right questions to ask vendors, internal technical teams, and senior leaders.
• Recognise AI specific risks such as bias, data quality issues, model drift, false positives/negatives, and privacy impacts.
• Ensure that AI-enabled systems are transparent, fair, explainable, and aligned with legal and ethical expectations.
• Maintain effective human oversight and prevent over reliance on automated outputs.
• Integrate AI safely into existing OH&S risk management and management system processes.
Overall, the purpose is not to turn OH&S practitioners into AI specialists, but to strengthen their ability to exercise professional judgement, challenge AI appropriately, and ensure responsible, safe and worker centred adoption.
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