AI for Risk Assessment & Early Warning
Overview
Many incidents give warning signs before they happen, but those signals are often scattered across reports, sensors and inspections. This course shows how AI can bring them together to assess risk more accurately, detect early warnings and help safety and risk teams act before harm occurs.
Who should attend
HSE managers, risk officers, safety engineers, and operations managers.
Training methodology
Interactive presentations, live demonstrations of AI tools, hands-on exercises using participants' own work examples, case studies, group discussion, and a personal action plan.
Objectives
By the end of this course, participants will be able to:
- Combine risk data sources with AI support
- Apply AI to hazard identification and risk assessment
- Design early warning indicators and alerts
- Analyse near misses and observations at scale
- Integrate AI into the risk management system
Course outline
Day 1Risk Data and AI
- Sources of risk information
- Leading and lagging indicators
- AI capabilities
- Data review
- Safety culture
- Data gaps
Day 2AI-Supported Risk Assessment
- Hazard identification support
- Learning from past incidents
- Consistency in risk ratings
- Exercise
- Permit to work support
- Risk matrices
Day 3Early Warning Systems
- Designing indicators
- Alerts and thresholds
- Sensor and camera analytics
- Case study
- Wearables
- Response procedures
Day 4Text Analytics for Safety
- Analysing near-miss reports
- Themes and trends
- Prioritising actions
- Hands-on analysis
- Audit findings analysis
- Reporting
Day 5Integration and Governance
- Fitting AI into the risk system
- Human judgement and accountability
- Privacy of workers
- Action plan
- Vendor selection
- Measuring impact
