An Artificial Intelligence Based Predictive Safety Management Framework for High Risk Industries in Saudi Arabia

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@article{1723783,
      author = {Abdul Rauf},
      title = {An Artificial Intelligence Based Predictive Safety Management Framework for High Risk Industries in Saudi Arabia},
      journal = {Iconic Research And Engineering Journals},
      year = {2026},
      volume = {10},
      number = {4},
      pages = {789-799},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1723783.pdf},
      abstract = {High-risk industries in Saudi Arabia are expanding while major construction, mining, energy, logistics and industrial programmes increase the scale and complexity of occupational risk. Conventional safety management remains essential, yet lagging indicators, periodic inspections and rule-based controls often identify deterioration only after exposure has accumulated. This structured review develops an artificial intelligence-based predictive safety management framework suited to Saudi operating conditions. It integrates leading indicators from permits, inspections, sensors, equipment systems, workforce records, environmental monitoring and incident narratives; applies transparent risk models; and routes predictions through human review and proportionate controls. The synthesis shows that artificial intelligence can improve prioritisation, early-warning capability and learning across dispersed sites, but only when data quality, privacy, workforce participation, model drift, cybersecurity and accountability are governed explicitly. The proposed framework therefore treats artificial intelligence as a decision-support layer within an ISO 45001-aligned management system, not as an autonomous replacement for competent safety judgement. Its principal contribution is a risk-based operating model linking data governance, prediction, verification, intervention and continuous assurance to Saudi Vision 2030 objectives.},
      keywords = {artificial intelligence; predictive safety; occupational health and safety; high-risk industries; Saudi Arabia; risk governance; leading indicators; Industry 4.0},
      month = {October},
  }