An Intensive 5-day Training Course
Artificial Intelligence (AI) for Safety Professionals
Hazard Identification & Risk Reduction Techniques: Using AI to Anticipate Hazards and Prevent Incidents
Scheduled Dates
Classroom
| 18-22 May 2026 | Dubai - UAE | $5,950 | RESERVE A SEAT |
| 17-21 Aug 2026 | London - UK | $5,950 | RESERVE A SEAT |
| 12-16 Oct 2026 | Dubai - UAE | $5,950 | RESERVE A SEAT |
| 14-18 Dec 2026 | London - UK | $5,950 | RESERVE A SEAT |
| 17-21 May 2027 | Dubai - UAE | $5,950 | RESERVE A SEAT |
| 16-20 Aug 2027 | London - UK | $5,950 | RESERVE A SEAT |
| 11-15 Oct 2027 | Dubai - UAE | $5,950 | RESERVE A SEAT |
| 13-17 Dec 2027 | London - UK | $5,950 | RESERVE A SEAT |
Would an alternative date be more suitable?
We offer a variety of tailored training options, customized to meet your organisation's needs. Delivered anytime, anywhere, we make it easy to bring expert training directly to your team.
Why Choose this Training Course?
This Artificial Intelligence (AI) for Safety Professionals: Hazard Identification & Risk Reduction Techniques training course is designed to empower safety leaders with advanced digital capabilities that transform traditional hazard management approaches into predictive, data-driven safety systems. As industries adopt Industry 4.0 technologies, Artificial Intelligence is becoming a powerful enabler of proactive safety management, enabling organisations to anticipate risks before incidents occur. Safety professionals must now understand how AI technologies integrate with operational data to enhance hazard detection, reduce risk exposure, and improve safety performance.
This training course provides a structured exploration of AI applications in industrial safety environments, including predictive modelling, intelligent surveillance, data analytics, and automated risk assessment tools. Participants will learn how to evaluate AI solutions, interpret predictive safety indicators, and integrate AI-driven insights into existing safety management systems. By completing this training course, safety professionals will gain the knowledge required to bridge the gap between traditional safety practices and emerging digital risk control technologies.
This training course will highlight:
- Strategic role of Artificial Intelligence (AI) in modern safety systems
- Predictive hazard identification using AI and machine learning
- AI-enhanced risk modelling and early warning systems
- Intelligent monitoring technologies for safety-critical operations
- Governance, compliance, and ethical considerations in AI safety adoption
What are the Goals?
At the end of this training course, you will learn to:
- Analyse how AI technologies enhance hazard detection processes
- Apply predictive analytics to strengthen risk reduction strategies
- Evaluate AI-driven safety monitoring systems and tools
- Integrate AI solutions into organisational safety frameworks
- Strengthen proactive safety leadership using data-driven insights
Who is this Training Course for?
This training course is designed for professionals responsible for safety governance and operational risk control, including:
- HSE Managers and Safety Leaders
- Risk and Compliance Professionals
- Process Safety and Industrial Safety Specialists
- Operations and Facility Managers
- Maintenance and Engineering Supervisors
- HAZOP and HAZID Team Members
- Digital Transformation and Operational Excellence Professionals
How will this Training Course be Presented?
This training course adopts an application-oriented methodology combining AI concept briefings, safety analytics discussions, structured risk modelling exercises, technology evaluation frameworks, and scenario-based safety analysis. Participants examine real operational safety contexts and explore how AI-driven systems support hazard identification and risk mitigation without replacing professional judgement.
Organisational Impact
This training course enables organisations to:
- Transition from reactive to predictive safety management
- Improve hazard detection speed and accuracy
- Reduce operational disruptions and safety incidents
- Strengthen compliance with evolving safety regulations
- Support digital transformation within safety management systems
- Enhance organisational resilience through intelligent risk monitoring
Personal Impact
Participants will develop:
- Strong understanding of AI applications in industrial safety
- Enhanced capability to interpret predictive safety analytics
- Greater confidence in adopting digital safety technologies
- Improved hazard analysis and risk evaluation skills
- Strategic insight into AI-enabled safety leadership
- Increased professional value in technology-driven safety environments
Daily Agenda
Day One: AI Fundamentals for Safety Professionals
- Evolution of safety management: from reactive to predictive safety
- Introduction to Artificial Intelligence, Machine Learning, and Analytics
- AI vs traditional safety analysis methods
- Safety data sources: incidents, near misses, inspections, sensors, permits
- Understanding structured vs unstructured safety data
- Role of AI in modern Safety Management Systems (SMS)
- Global trends in AI adoption for HSE and process safety
Day Two: AI for Hazard Identification
- Limitations of traditional hazard identification approaches
- AI-based hazard detection models
- Using historical incident and near-miss data for hazard prediction
- Natural Language Processing (NLP) for analyzing safety reports and observations
- Computer vision for site safety (PPE compliance, unsafe acts, unsafe conditions)
- AI-enhanced workplace inspections and audits
- Practical exercise: AI-supported hazard identification workshop
Day Three: AI-Driven Risk Assessment & Predictive Safety
- Predictive analytics for safety risk forecasting
- AI-based risk scoring and prioritization
- Enhancing JSA, HAZID, and HAZOP with AI insights
- Leading vs lagging indicators: AI-enabled safety KPIs
- Risk heatmaps and dynamic risk registers
- Early-warning systems for major accident prevention
- Case study: Predicting high-risk activities before incidents occur
Day Four: AI for Risk Reduction & Incident Prevention
- Translating AI insights into preventive and corrective actions
- AI-supported Permit to Work (PTW) and job planning
- Fatigue management and human factors using AI
- Contractor safety monitoring with AI
- AI for asset integrity and failure prevention
- Integrating AI with IoT and real-time safety monitoring systems
- Group exercise: Designing AI-based risk reduction controls
Day Five: Incident Investigation, Governance & Implementation
- AI in incident investigation and root cause analysis
- Pattern recognition across incidents and near misses
- Automating safety reporting and recommendations
- Ethical use of AI in safety decision-making
- Data quality, bias, and model risk management
- Regulatory, compliance, and governance considerations
- Building an AI roadmap for the safety function
- Final workshop: AI safety implementation action plan
Certificate
- On successful completion of this Training Course / Online Training Course, a PetroKnowledge Certificate / E-Certificate will be awarded to the delegates.
