Programme Overview
A two-day programme for health, safety and environment professionals in high-hazard and regulated sectors. It covers how AI is transforming incident prediction and prevention, safety monitoring, near-miss analysis, training and compliance reporting. Participants learn to apply AI to reduce risk while navigating the ethical and regulatory questions raised by AI-based safety systems that affect workers. The hands-on work uses anonymised safety data and realistic scenarios. The programme suits oil and gas, petrochemicals, construction, manufacturing, utilities, transport and mining.
Learning Objectives
By the end of this programme, participants will be able to:
- Describe how AI is reshaping HSE practice across prediction, monitoring, training and incident response.
- Use AI tools for incident analysis, near-miss synthesis, safety reporting and training-content generation.
- Apply AI to leading- and lagging-indicator analysis and to predictive risk modelling.
- Integrate AI-based monitoring — including computer vision, sensors and wearables — into safety-management systems.
- Recognise the ethical and privacy implications of AI-based, worker-facing monitoring.
- Apply SDAIA, the PDPL, Saudi Labour Law and sector safety regulators (such as HCIS, Aramco standards and comparable OSHA standards) to AI use in HSE.
Programme Content & Modules
Day 1: The HSE landscape and AI in safety practice
How AI is reshaping HSE across sectors. Predictive risk, computer vision for safety, sensor and wearable data, and AI-supported incident analysis. Where AI has matured in this field and where it is still emerging. The Saudi regulatory and industrial context for HSE.
Practical work with AI tools for incident-report analysis, near-miss synthesis, safety reporting, training-content generation and Toolbox-Talk preparation. Prompt engineering for safety accuracy. A tour of AI-enhanced safety, inspection and monitoring platforms.
Day 2: AI-supported safety and responsible practice
Using AI for leading-indicator analysis, near-miss pattern recognition and predictive risk. Combining AI output with HSE professional judgement. A group exercise on a realistic incident investigation or risk assessment supported by AI.
Worker privacy and consent when deploying AI-based monitoring. Algorithmic accountability for decisions affecting worker safety. PDPL and Labour Law considerations. SDAIA’s AI Ethics Principles in an HSE context. Applied capstone project: each participant designs a responsible AI-based HSE process for their site.
Suggested Duration
Two training days.
Target Audience & Prerequisites
Target audience: HSE managers and officers, safety engineers, occupational-health specialists, environmental specialists, operations-risk managers and senior HSE leaders in oil and gas, petrochemicals, construction, manufacturing, utilities, transport and mining. The programme suits holders of NEBOSH, IOSH and OSHA certifications.
Prerequisites: Practical experience in HSE or operations risk. Basic computer literacy. No prior background in AI or programming is required. A laptop is required for the hands-on sessions.
