The rapid advancement of Artificial Intelligence (AI) has created significant opportunities to enhance occupational safety and health (OSH) across diverse industries. This study investigates the potential applications, effectiveness, and limitations of AI technologies in improving workplace safety, employee well-being, and productivity. Employing a mixed-methods design, the research integrates quantitative analyses, including hierarchical regression to examine the impact of specific AI tools, with qualitative insights from thematic analysis of expert and employee perspectives. The findings reveal that predictive analytics, wearable monitoring devices, and automated incident reporting significantly contribute to reducing workplace hazards and enhancing employee health, while other technologies, such as robotic exoskeletons, face adoption barriers due to cost and operational challenges. Additionally, the study highlights ethical considerations, employee acceptance, and training as critical factors influencing the success of AI integration. The results suggest that AI can substantially improve OSH outcomes when strategically implemented within a robust governance framework that addresses both technological and human factors. Practical recommendations include prioritizing high-impact AI technologies, providing comprehensive training, establishing ethical protocols, and continuously monitoring performance to optimize safety and productivity. These findings offer valuable guidance for organizations, policymakers, and OSH practitioners seeking to leverage AI for safer and more efficient workplaces.
STEPHEN ANANG ANKAMAH-LOMOTEY (Wed,) studied this question.
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