{"id":35245,"date":"2026-07-06T12:06:30","date_gmt":"2026-07-06T09:06:30","guid":{"rendered":"https:\/\/esi.edu.sa\/?post_type=courses&p=35245"},"modified":"2026-07-06T14:56:38","modified_gmt":"2026-07-06T11:56:38","slug":"%d8%a7%d9%84%d8%b0%d9%83%d8%a7%d8%a1-%d8%a7%d9%84%d8%a7%d8%b5%d8%b7%d9%86%d8%a7%d8%b9%d9%8a-%d9%84%d9%84%d8%b3%d9%84%d8%a7%d9%85%d8%a9-%d9%88%d8%a7%d9%84%d8%b5%d8%ad%d8%a9-%d8%a7%d9%84%d9%85%d9%87","status":"publish","type":"courses","link":"https:\/\/esi.edu.sa\/en\/courses\/%d8%a7%d9%84%d8%b0%d9%83%d8%a7%d8%a1-%d8%a7%d9%84%d8%a7%d8%b5%d8%b7%d9%86%d8%a7%d8%b9%d9%8a-%d9%84%d9%84%d8%b3%d9%84%d8%a7%d9%85%d8%a9-%d9%88%d8%a7%d9%84%d8%b5%d8%ad%d8%a9-%d8%a7%d9%84%d9%85%d9%87\/","title":{"rendered":"AI for Health, Safety & Environment (HSE)"},"content":{"rendered":"
\n

Programme Overview<\/h3>\n

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.<\/p>\n<\/section>\n

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Learning Objectives<\/h4>\n

By the end of this programme, participants will be able to:<\/p>\n

    \n
  • Describe how AI is reshaping HSE practice across prediction, monitoring, training and incident response.<\/li>\n
  • Use AI tools for incident analysis, near-miss synthesis, safety reporting and training-content generation.<\/li>\n
  • Apply AI to leading- and lagging-indicator analysis and to predictive risk modelling.<\/li>\n
  • Integrate AI-based monitoring \u2014 including computer vision, sensors and wearables \u2014 into safety-management systems.<\/li>\n
  • Recognise the ethical and privacy implications of AI-based, worker-facing monitoring.<\/li>\n
  • 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.<\/li>\n<\/ul>\n<\/section>\n
    \n

    Programme Content & Modules<\/h4>\n

    Day 1: The HSE landscape and AI in safety practice<\/h5>\n
    \n
    Module 1: <\/span>AI in Health, Safety & Environment<\/div>\n

    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.<\/p>\n<\/div>\n

    \n
    Module 2: <\/span>AI Tools in Safety Practice<\/div>\n

    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.<\/p>\n<\/div>\n

    Day 2: AI-supported safety and responsible practice<\/h5>\n
    \n
    Module 3: <\/span>AI-Supported Incident Prevention & Response<\/div>\n

    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.<\/p>\n<\/div>\n

    \n
    Module 4: <\/span>Responsible AI in HSE<\/div>\n

    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.<\/p>\n<\/div>\n<\/section>\n

    \n

    Suggested Duration<\/h4>\n

    Two training days.<\/p>\n<\/section>\n

    \n

    Target Audience & Prerequisites<\/h4>\n

    Target audience:<\/strong>\u00a0HSE 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.<\/p>\n

    Prerequisites:<\/strong>\u00a0Practical 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.<\/p>\n<\/section>\n","protected":false},"author":2043,"featured_media":35257,"template":"","course_category":[1370,945],"class_list":["post-35245","courses","type-courses","status-publish","has-post-thumbnail","hentry","course_category-sectoral","course_category-ai","infinite-scroll-item","no-featured-image-padding"],"acf":[],"_links":{"self":[{"href":"https:\/\/esi.edu.sa\/en\/wp-json\/wp\/v2\/courses\/35245","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/esi.edu.sa\/en\/wp-json\/wp\/v2\/courses"}],"about":[{"href":"https:\/\/esi.edu.sa\/en\/wp-json\/wp\/v2\/types\/courses"}],"author":[{"embeddable":true,"href":"https:\/\/esi.edu.sa\/en\/wp-json\/wp\/v2\/users\/2043"}],"version-history":[{"count":4,"href":"https:\/\/esi.edu.sa\/en\/wp-json\/wp\/v2\/courses\/35245\/revisions"}],"predecessor-version":[{"id":35357,"href":"https:\/\/esi.edu.sa\/en\/wp-json\/wp\/v2\/courses\/35245\/revisions\/35357"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/esi.edu.sa\/en\/wp-json\/wp\/v2\/media\/35257"}],"wp:attachment":[{"href":"https:\/\/esi.edu.sa\/en\/wp-json\/wp\/v2\/media?parent=35245"}],"wp:term":[{"taxonomy":"course_category","embeddable":true,"href":"https:\/\/esi.edu.sa\/en\/wp-json\/wp\/v2\/course_category?post=35245"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}