Czy AI zastąpi zawód: osoba dozoru ruchu w górnictwie?

Osoba dozoru ruchu w górnictwie faces a high AI disruption risk with a score of 64/100, indicating significant transformation ahead rather than full replacement. While administrative and monitoring tasks—such as production reporting and operational record-keeping—are increasingly automatable, the supervisory, safety investigation, and strategic planning dimensions of this role remain fundamentally human-dependent. The occupation will likely evolve rather than disappear over the next decade.

Czym zajmuje się osoba dozoru ruchu w górnictwie?

Osoba dozoru ruchu w górnictwie (Mining Operations Supervisor) coordinates and oversees all activities in deep mines, open-pit mines, and quarries. These professionals supervise mining personnel, manage work schedules, monitor operational processes, and organize site activities across extraction facilities. They ensure compliance with safety protocols, maintain operational efficiency, and serve as the critical management link between frontline workers and senior leadership. Their responsibilities span personnel management, resource allocation, process oversight, and day-to-day problem-solving in complex underground and surface mining environments.

Jak AI wpływa na ten zawód?

The 64/100 disruption score reflects a nuanced vulnerability profile. Administrative and data-management tasks—writing production reports, maintaining operational records, monitoring mine costs, and managing site data—are highly susceptible to automation, with Task Automation Proxy scoring 57.69/100. These structured, repetitive documentation tasks represent approximately 30-40% of current workload and will likely transfer to AI systems within 3-5 years. However, supervisory resilience remains substantial. Core functions like supervising mine construction, investigating accidents, and evaluating development projects scored in the resilient range, as they require contextual judgment, stakeholder management, and accountability that AI cannot yet replicate. The AI Complementarity score of 66.08/100 is notably positive: AI tools will enhance rather than replace critical thinking in financial optimization, mine planning software usage, and mineral resource evaluation. Near-term (1-3 years): routine administrative burden decreases through automation, freeing supervisors for higher-value strategic work. Long-term (5-10 years): hybrid roles emerge where supervisors become AI-augmented coordinators, using machine learning for predictive safety and cost analysis while retaining decision authority and personnel oversight.

Najważniejsze wnioski

• •Administrative tasks like production reporting and records management face the highest automation risk; supervisory and safety investigation duties remain resilient.
• •AI will likely enhance rather than replace this role—66.08/100 complementarity score indicates tools amplify supervisor effectiveness in planning and financial analysis.
• •Core job security depends on developing competency with AI mining software and predictive analytics alongside traditional supervisory skills.
• •The role will evolve toward strategic coordination and AI-augmented decision-making rather than disappear within the next decade.

Wynik zakłócenia AI NestorBot obliczany jest na podstawie 3-czynnikowego modelu wykorzystującego taksonomię umiejętności ESCO: podatność umiejętności na automatyzację, wskaźnik automatyzacji zadań oraz komplementarność z AI. Dane aktualizowane kwartalnie.