Digging Deeper: How AI is Reshaping Canada's Mining Industry and Workforce
Photograph: Agnico Eagle Mines Limited - Meadowbank Complex
Author
Andrew Scarlato
Editor
Maryam Khan
Introduction
The mining sector is the cornerstone of the Canadian economy. It provides high-paying jobs and employs 649,000 people, 17,300 of whom are Indigenous. Many of these jobs are in remote areas, where individuals do not have as many employment options as those in major cities, making the mining industry an essential part of their lives. While the mining sector has been a reliable source of job creation and wealth, it is currently undergoing a revolution with the adoption of AI being seen at all levels of the mining supply chain. As AI is adopted, it drives automation in the industry, leading to benefits such as increased safety but it also risks taking away jobs in an industry that many Canadians rely on.
The Adoption of AI in the Mining Industry
To understand the effect that AI has on the industry and labour supply, it is imperative to
discuss how the technology has already been implemented and, the ways in which it will be in the future.
Automation
AI is a pervasive technology in the mining industry, finding ways to improve all points of the supply chain by removing labour-intensive methods. One of the earliest forms of automation introduced by AI in the mining industry is the use of automated vehicles. Mining companies, such as Rio Tinto, already use automated trucks and trains to transport ore and waste to processing locations, without the need for human drivers.
Processing and Fulfillment
AI systems can also be used in processing plants to optimize operations and reduce energy consumption. One application of AI in processing plants is ore sorting, where AI is used to sort ore from waste material more efficiently, reducing processing costs.
Further down the supply chain, AI can be integrated into ports, where AI-powered cranes can be used to load cargo ships with shipping containers, improving the speed at which ships are loaded and reducing order fulfillment time.
Predictive Maintenance
According to BHP, maintenance and unexpected failures are among the largest costs incurred by mining companies. Using AI to monitor machinery through sensor data and historical trends is useful for analyzing the condition of machinery and preventing unexpected breakdowns. These breakdowns are both harmful to workers near machinery and cause significant downtime, reducing the efficiency of mining operations.
Exploration and Extraction
One of the most important parts of the mining industry is surveying and mineral discovery. As the world’s demand for minerals such as copper increases, there is a growing need for more efficient discovery of deposits to prevent shortages. Traditionally, the mining sector has relied on geologists to collect samples and analyze them. Today, the geologists’ role has been elevated thanks to AI with samples being analyzed using software in labs to identify chemical anomalies and measure the probability of ore below the surface.
This modern use of software for analysis also increases the accuracy and speed of survey methods as AI systems are extremely effective in analyzing large datasets, finding patterns or anomalies within them. In the mining industry, AI can analyze geological data such as surveys, soil compositions, and historical records to determine where mineral deposits are located and assess their quality more quickly than previous methods.
Safety
Advancements in AI pertaining to the mining industry contribute to a safer working environment in mines. AI systems can reduce the amount of human error during operations. Humans are also removed from potentially dangerous situations such as blasting, drilling, and unexpected machinery breakdowns. While the potential reduction in loss of life and injury is one of the most attractive aspects of adopting AI, it is clear that the strategy to eliminate threats often involves removing the human input from the operation or, at the very least, reducing the number of people needed to operate a mine.
How Mining Companies Benefit From AI
Those who implement AI and own AI-enabled assets will benefit the most. Automated vehicles, blasting devices, and drills will replace many jobs traditionally done by humans. Automation fosters increased efficiency and reduced reliance on labor lowering costs and increasing profits in the long run.
In addition to cost reduction, increased productivity through reduced downtime can raise the output from a mining operation. This enables mining companies to meet the growing global demand for critical minerals, increasing the export potential of countries where the mines operate. These minerals support other sectors, such as green energy companies requiring them for batteries or technology companies utilizing rare earth metals for electronic components.
Overall, these factors will help the bottom line of companies that adopt AI for their operations, making implementation of AI attractive to management.
How Does AI Implementation Affect Workers?
The productivity gains, efficiency improvements, and cost reductions that AI brings to the mining sector will not be felt equally throughout society. In Canada, the mining industry is a major employer, particularly in communities that do not benefit from the opportunities available in major cities. These jobs are not only important to diverse communities but also pay well. According to the Government of Canada, the average annual total compensation per job in the mining industry is $139,217. Mining wages are income that communities heavily rely on, and cutting the human workforce in the mining industry would negatively impact the well-being of individuals and communities.
AI implementation will also lead to a change in the type of jobs that are available in the industry. Although labor-intensive jobs will be replaced by automation due to AI, it will also create new jobs. These will be high-skill roles often performed remotely, which may lead to fewer jobs being physically based in the mining communities that rely on them most, especially indigenous communities.
Nuance in the Labor Structure of the Mining Industry
The labour impact of AI in the mining industry is nuanced. While job displacement due to automation is real, the industry is also facing a labour and talent shortage. According to a Deloitte study, mining employment rates have been falling, even as the demand for workers remains high. In Canada, the industry needs 80,000–120,000 workers by 2030 to maintain operations at a reasonable pace.
Further, 50% of mining engineers are expected to reach retirement age within the next decade. The aging workforce is a challenge, exacerbated by declining interest in mining jobs among younger generations. From 2016–2020, the number of mining, geophysical, and geological engineering undergraduate students in Canada dropped by a third.
Younger generations prioritize work-life balance and remote work opportunities over high wages. Additionally, 66% of Generation Z respondents in a BDO survey indicated a preference for careers that benefit local communities and positively impact the environment.
Thus, the labour challenges in the mining industry are not solely about AI taking jobs; there are plenty of jobs currently available in this field, but demand for them among the labour supply is low.
Positive-Sum Solutions
The issues of labour shortages, talent gaps, and job displacement due to AI may have solutions that benefit mining companies, workers, and the communities they operate in. As miners retire and create skill gaps, AI can help address this problem by automating some of the roles they leave behind.
At the same time, current employees whose jobs are at risk of being replaced by AI need opportunities to reskill for roles that remain necessary with AI implementation. As AI takes over manual tasks, there will still be a demand for skilled technicians and data analysts to oversee and manage AI systems. Reskilling these workers not only helps retain valuable talent but also ensures that, rather than relying solely on external hires, companies have employees who understand the realities of mining operations.
While reskilling is beneficial, it cannot fully compensate for the reduction in jobs caused by automation. To address this, additional measures are required to ensure the economic well-being of the communities where mining companies operate. One solution is the increased use of impact-benefit agreements (IBAs) – contracts between extraction companies and local communities that outline the expected impacts of mining operations and the shared benefits for those communities. To ensure IBAs are fair and effective, governments may need to assist communities by providing legal support and representation during contract negotiations. This would help balance the power dynamics between large mining corporations and smaller, often under-resourced communities.
IBAs also increase institutional investor interest in responsible investing such as the Canadian Pension Plan's adoption of sustainable investment strategies, which are similar to Environmental, Social, and Governance (ESG) principles. This has encouraged mining companies encouraged mining companies to engage in greater corporate social responsibility to retain and gain investment. Companies that prioritize ESG principles have been proven to benefit from increased long-term profitability, improved shareholder confidence, and fewer legal disputes.
Adopting ESG principles and engaging in corporate social responsibility can also help mining companies attract young workers. The sustainability commitments many companies are making align with the values of Generation Z who prioritize community impact and environmental sustainability. An opportunity to drive meaningful change means they can work in roles that improve the industry's environmental practices or create innovative solutions to increase sustainability.