Organisations across the mining and energy sector face increasing pressure to manage psychosocial hazards while maintaining workforce safety, engagement, and productivity. This paper examines how agentic artificial intelligence embedded within employee experience platforms can deliver personalised wellbeing support at scale while strengthening organisational resilience. Traditional workplace wellbeing tools are often generic, reactive, and disconnected from the realities of modern work. Agentic artificial intelligence enables a shift from static wellbeing resources to adaptive systems that embed support directly into the flow of work and daily life. Governed by clinical and ethical guardrails, these systems coordinate intelligent agents to personalise interventions, surface organisational resources, and respond to emerging needs while maintaining organisational oversight and compliance. Two illustrative user journeys demonstrate how this model operates across different operational contexts. Jane, a corporate team leader, receives contextual guidance for psychologically safe leadership conversations and stress management integrated into her workday. Kai, a fly-in, fly-out maintenance technician, receives support aligned to site rotations, including fatigue management and recovery strategies suited to remote environments. Aggregated and de-identified interaction data generate organisational insight into workforce strain and support utilisation, enabling earlier identification of psychosocial risk and more targeted investment in workforce health and safety across safety-critical operations.
Troy Morgan (Thu,) studied this question.
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