The higher education ecosystem is a vital supply pipeline for mining occupations. However, the industry faces both an ageing workforce and a constricting supply pipeline, which perpetuates critical skills shortages. As the demand for skills is closely tied to commodity price cycles, this also increases job security risks. Pathways such as micro credentials can provide lateral opportunities for reskilling, potentially improving employment outcomes, ensuring a more stable supply of skills, and strengthening alignment between industry and education providers. This reduces supply backlogs and ensures productivity outcomes. 

Higher education has long served as a critical workforce pipeline for the Mining industry. Many mining occupations, such as Mining Engineers, Geologists, and Metallurgists require skills that are closely tied to higher education. As of 2021, around 24% of the mining workforce held a qualification at or above a bachelor’s degree.²  

Falling enrolments and completions 

Between 2014 and 2023, both enrolments and completions in mining engineering degrees at the bachelor and postgraduate levels declined. The steepest drop occurred between 2014 and 2018, when enrolments fell from 2,420 to 770 (-68%). Similarly, completions declined by 65% during the same period (Figure 1a). 

Female enrolments in mining engineering degrees have remained relatively low, ranging between 9% and 13% from 2014 to 2023. This proportion is lower than that of vocational education. Approximately 16% of RII (Resources and Infrastructure Industry Training Package) mining qualifications were driven from female students, while 12% of enrolments were from female students in higher education in 2023 (Figure 2a).³ Mining engineering enrolments are concentrated in New South Wales (NSW) and Western Australia (WA) (Figure 2b). 

International students are also declining with no exceptions 

Following the general pattern of enrolments and completions, international student enrolments in mining engineering have also fallen over time (Figure 3). 

Succession Planning and Critical Shortages 

The consistent fall in the mining engineering enrolments has translated to a constricted supply of Mining Engineers, which then creates critical shortages in the workforce across all states (Table 2). 

Given the importance of the mining engineering occupation, a constricted supply pipeline can: 

Is the commonwealth funding policy helping? 

A Commonwealth Supported Place (CSP) is a subsidy that reduces the cost of courses for students. It is a place at a university or approved higher education provider, where the Australian Government covers part of the course fee for students.⁹ The CSP mostly supports bachelor's degrees, although it was extended to include enabling degrees and postgraduate studies in 2014.¹⁰ 

With demand-driven funding frozen from 2017, this may have contributed to the lower and flat enrolment trend observed between 2018 and 2023 (Appendix A). However, mining engineering enrolments have been declining steadily since 2014, suggesting that funding policy changes are unlikely to be the primary driver of the decline. 

AI-led jobs upheaval 

As AI leads the automation and augmentation of jobs, occupations that are less susceptible to automation offer job security and better employment outcomes for students and new workforce entrants. The Australian mining industry is a leading adopter of AI-led job evolution.¹¹ AI offers numerous benefits, such as removing workers from hazardous environments, providing real-time environmental impact assessments and assisting companies in meeting regulatory compliance requirements.¹² 

Core mining roles, such as mining engineers, as well as geologists, geophysicists, and hydrogeologists, have relatively low automation risks. The index reports probabilities of 0.32 for geologists, geophysicists, and hydrogeologists, and 0.14 for mining engineers (Table 3). Occupations with the highest probabilities of automation include accountants and earthmoving plant operators, both with probabilities of 0.94.¹³ While AI can automate and streamline certain repetitive tasks, it is not expected to eliminate entire professions.¹⁴ As a result, entry-level roles are likely to diminish, while engineers with skills in system interpretation and oversight will remain in strong demand. Ultimately, engineers are expected to evolve into “AI-augmented problem solvers”. ¹⁵ 

Case in point – AI augmentation 

Rio Tinto has implemented a GPT-style assistant that helps mine planners search through hundreds of documents within seconds, which previously took humans months. A computer vision model is used to analyse 2.6 million wildlife-camera images to detect endangered palm cockatoos around the Weipa bauxite pit, helping the company ensure it meets environmental regulations and compliance requirements.¹⁶