Early Bird
$1,095 Through April 12, 2027RAAI ACADEMY COURSE · RAAI-AI200
Registration OpenAI-Enabled Hazard and Risk Management
SIF Prevention, Risk Intelligence, and Critical Control Assurance
OVERVIEW
Professional context and course purpose
Organizations collect large amounts of safety information through job hazard analyses, inspections, incident and near-miss reports, exposure data, operating procedures, maintenance records, risk assessments, and corrective-action systems. The challenge is not simply having more data—it is turning that information into reliable, defensible, and actionable risk decisions.
RAAI-AI200 provides a practical framework for using artificial intelligence to strengthen hazard identification, risk assessment, Serious Injury and Fatality (SIF) prevention, accident-scenario analysis, intervention design, and critical-control assurance.
Participants work through realistic safety scenarios and learn how AI can help structure work-system information, identify hazards, evaluate evidence quality, quantify and prioritize risk, model serious-event pathways, analyze barriers and controls, compare intervention options, and verify whether critical controls are functioning as intended.
The course goes beyond basic AI prompting. Participants use structured AI-assisted workflows to examine work as performed, challenge assumptions, identify missing or weak evidence, distinguish routine risk from potential SIF exposure, analyze how serious events could occur, and translate findings into risk-reduction priorities.
Particular emphasis is placed on human oversight, evidence traceability, uncertainty, calculation transparency, regulatory caution, and validation of AI-generated outputs. AI is treated as a decision-support capability—not as a replacement for competent OSH professionals, industrial hygienists, engineers, supervisors, or organizational decision-makers.
By the end of the course, participants will understand how to integrate AI into established hazard- and risk-management processes while maintaining professional accountability and producing analysis that is transparent, reviewable, and suitable for operational decision-making.
LEARNING OUTCOMES
You will learn how to:
Structure work-system, task, JSA/JHA, incident, inspection, exposure, and operational information for reliable AI-assisted hazard and risk analysis.
Use AI to identify hazards, organize evidence, distinguish documented facts from assumptions, and evaluate evidence quality, completeness, relevance, and traceability.
Build more defensible risk priorities by considering severity, likelihood, exposure, existing controls, uncertainty, data quality, and sensitivity rather than relying only on simple risk matrices.
Distinguish routine occupational risk from potential SIF exposure, including high-severity, low-frequency scenarios that may not be visible in lagging indicators.
Analyze accident pathways using Bow-Tie and STPA, including threats, top events, consequences, unsafe control actions, barrier dependencies, automation, and human-machine interactions.
Identify critical controls and evaluate their design, effectiveness, availability, ownership, performance standards, verification evidence, and potential degradation.
Generate and compare intervention options using hierarchy-of-controls principles, OHSIM-AI, multi-criteria evaluation, implementation constraints, residual risk, and economic considerations.
Prioritize critical-control verification using inspections, observations, sampling, leading indicators, barrier-health information, trends, escalation thresholds, and corrective-action follow-up.
Detect and challenge hallucinations, unsupported assumptions, fabricated references, calculation errors, weak causal reasoning, and unsafe or overconfident AI-generated recommendations.
Integrate validated AI-supported findings into existing OSH, EHS, risk, compliance, and operational systems and translate them into clear risk registers, intervention priorities, assurance records, and executive-ready decision briefs.
COURSE MATERIALS
You will receive:
- RAAI Academy Digital Participant Guide covering the complete AI-enabled hazard, risk, SIF, intervention, and control-assurance workflow.
- Work-System and JSA/JHA Analysis Templates for structuring operational information into analysis-ready risk data.
- AI-Assisted Hazard Identification and Evidence-Review Tools for organizing hazards, assumptions, evidence gaps, and traceability.
- Quantitative Risk Analytics Worksheets covering risk scoring, exposure, uncertainty, control effectiveness, sensitivity analysis, and prioritization.
- SIF and Accident-Scenario Analysis Tools including practical Bow-Tie and STPA templates for examining serious-event pathways and barrier weaknesses.
- OHSIM-AI Intervention Design Tools for generating, comparing, and prioritizing risk-reduction options using hierarchy-of-controls and multi-criteria logic.
- Critical Control Assurance and Verification Templates covering control ownership, performance standards, barrier health, verification methods, failure criteria, and escalation requirements.
- AI Output Verification and Evidence-Traceability Checklist for identifying unsupported claims, unsafe recommendations, hallucinations, and calculation errors.
- Applied Case-Study and Risk Intelligence Agent Exercises that connect hazard identification, risk analytics, SIF prevention, intervention design, control assurance, and AI validation.
- Decision-Ready Output Templates and Certificate of Completion, including hazard registers, quantified risk summaries, scenario models, intervention portfolios, assurance records, executive risk briefs, and the RAAI Academy Certificate of Completion.
PROFESSIONAL DEVELOPMENT
Continuing Education Units (CEUs)
RAAI-AI200 provides 1.6 Continuing Education Units (CEUs), based on 16 instructional contact hours and the conventional standard of 10 contact hours per CEU.
To receive CEUs and the RAAI Academy Certificate of Completion, participants must satisfy the course attendance, participation, and completion requirements established for the program.
LIVE ONLINE DELIVERY
Course Structure — Zoom Workplace — Online Access
16-hour live, instructor-led online course delivered over two days through Zoom Workplace.
Scheduled time: 8:00 AM–4:30 PM Mountain Standard Time (MST, UTC−7)
For two-day courses, the scheduled time applies on each day.
Participant technology and access requirements
- Reliable internet connection
- Computer capable of Zoom Workplace access
- Speakers or headphones and a microphone
- Camera strongly recommended
- Modern web browser
- Access to AI tools identified in pre-course instructions
Data safety: Participants should not enter confidential, proprietary, personal, export-controlled, or otherwise restricted information into public AI systems during course exercises.
PARTICIPANT TERMS
Cancellation Policy
A $150 cancellation charge will be assessed for a standard cancellation.
A late cancellation charge equal to 25% of the applicable course registration fee will be assessed for cancellations received within 14 calendar days of the course start date.
If a participant does not cancel, reschedule, transfer, or otherwise notify RAAI before the published course start date and time, the registration will be considered a No Show. No substitution, rescheduling, deferment, or refund will be available for a No Show.
No refunds, substitutions, rescheduling, or deferments will be granted after the published course start date and time have passed.
If RAAI cancels a course, registered participants will be offered a transfer to an available future offering or a refund of the applicable course registration fee.
OPEN REGISTRATION
Registration Information
Online registration is open for this published 2027 course offering.
Registration pricing
Standard
$1,295 Beginning April 13, 2027Join Academy Updates for future course announcements and program news.
Register Now Academy UpdatesAcademy Updates are informational and are not required to register for an available course.
SECURE REGISTRATION
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