Mining and Geological Engineers, Including Mining Safety Engineers

Prepare technical reports for use by mining, engineering, and management personnel.

AI: Fully automatable - AI tools in 2025 can synthesize data and standards to draft polished, actionable technical reports given structured inputs and templates.

Prepare schedules, reports, and estimates of the costs involved in developing and operating mines.

AI: Fully automatable - AI scheduling and cost-estimation systems can produce detailed schedules, reports, and cost estimates from project and historical data with high accuracy, enabling full automation of this task.

Monitor mine production rates to assess operational effectiveness.

AI: Fully automatable - AI can continuously ingest sensor and production data to monitor rates and assess operational effectiveness in real time, enabling fully automated monitoring and alerts.

Inspect mining areas for unsafe structures, equipment, and working conditions.

AI: Partial - AI-enabled drones and vision models can detect many hazards remotely but cannot fully replace human judgment and hands-on inspection for complex or ambiguous unsafe conditions.

Test air to detect toxic gases and recommend measures to remove them, such as installation of ventilation shafts.

AI: Partial - AI combined with sensor networks can detect toxic gases and suggest mitigation measures automatically, but installation of ventilation infrastructure and nuanced ventilation design require human engineering and site assessments.

Select or develop mineral location, extraction, and production methods, based on factors such as safety, cost, and deposit characteristics.

AI: Partial - AI can model and optimize extraction methods using geological, safety, and cost data, but ultimate selection requires human engineering judgment and on-site validation.

Select locations and plan underground or surface mining operations, specifying processes, labor usage, and equipment that will result in safe, economical, and environmentally sound extraction of minerals and ores.

AI: Partial - AI can generate location analyses and operational plans and optimize processes, but comprehensive planning that ensures safety, regulatory compliance, and on-the-ground practicality still requires human leadership and local expertise.

Implement and coordinate mine safety programs, including the design and maintenance of protective and rescue equipment and safety devices.

AI: Partial - AI can help design, document, and monitor safety programs and predict risks, but implementing, coordinating personnel, and maintaining rescue equipment are human-led, safety-critical activities.

Devise solutions to problems of land reclamation and water and air pollution, such as methods of storing excavated soil and returning exhausted mine sites to natural states.

AI: Partial - AI can analyze site data and generate land-reclamation and pollution-control plans, but real-world implementation, regulatory approval, and complex field judgment require human engineers.

Lay out, direct, and supervise mine construction operations, such as the construction of shafts and tunnels.

AI: Partial - AI can produce construction layouts, schedules, and risk analyses for shafts and tunnels, yet directing and supervising on-site construction requires human oversight and safety responsibility.

Supervise, train, and evaluate technicians, technologists, survey personnel, engineers, scientists or other mine personnel.

AI: Partial - AI can support supervision with training modules, monitoring, and evaluation analytics, but human leaders are still required for real-time safety decisions, mentorship, and personnel management.

Examine maps, deposits, drilling locations, or mines to determine the location, size, accessibility, contents, value, and potential profitability of mineral, oil, and gas deposits.

AI: Partial - AI can analyze geophysical data, maps, and drill logs to estimate deposit size and value, but geological uncertainty and access issues require field verification and expert interpretation.

Design, develop, and implement computer applications for use in mining operations such as mine design, modeling, or mapping or for monitoring mine conditions.

AI: Partial - AI tools can design, prototype, and help implement mining software (modeling, mapping, monitoring) but full end-to-end development, integration, and operational validation still need human engineers.

Design, implement, and monitor the development of mines, facilities, systems, or equipment.

AI: Partial - AI can design and simulate mine systems and monitor development progress, but implementing physical construction and complex engineering integration requires human teams and on-site decision-making.

Select or devise materials-handling methods and equipment to transport ore, waste materials, and mineral products efficiently and economically.

AI: Partial - AI can optimize and propose materials‑handling methods and equipment through simulation and data analysis, but final selection, procurement, and field adaptation need human engineering judgment.

Evaluate data to develop new mining products, equipment, or processes.

AI: Partial - AI can evaluate large datasets to suggest new mining products, equipment, or processes, however experimental validation, prototyping, and commercialization require human-led development.

Design mining and mineral treatment equipment and machinery in collaboration with other engineering specialists.

AI: Partial - AI can assist in designing mining and treatment machinery and perform simulations, yet collaborative multi-disciplinary design, manufacturability, and certification remain human-driven.

Conduct or direct mining experiments to test or prove research findings.

AI: Partial - AI can design experiments, run simulations, and analyze results, but actually conducting and directing physical mining experiments with safety and logistics constraints requires humans.