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A Generational Turnover Could Jeopardize the Nuclear Industry’s Recent Momentum

In the coming decade, the nuclear industry faces the daunting prospect of seeing one in four employees retire. According to the 2022 Global Energy Talent Index, 25% of its current workforce is over 55, compared to 20% in the oil and gas industry, and only 10% in the renewable energy sector. And, at age 65 and above, 9% of the nuclear industry’s employees are already eligible for retirement.

This generational shift represents a significant concern for an industry that has finally been recognized as a clean energy source at the United Nations Climate Change Conference (COP28) and is seeing an influx of new projects. It will amplify already significant skill shortages that are already causing a fierce war for existing talent, with 19% of nuclear employees approached for a new position more than once a month.

But nuclear operators worldwide are also increasingly turning to technology to reduce potential effects, digitize their work processes, preserve informal know-how, and transform operations to reduce the learning curve encountered by new hires. The result is a gradual redefinition of how nuclear technicians and engineers perform their tasks.

Maintenance Jobs at the Forefront of a Generational Shift

A field where this phenomenon is most visible is maintenance—one of the areas where hiring difficulties are the greatest across the energy sector, according to a recent report by the International Energy Agency.

In the nuclear sector, this problem is compounded by the need for highly specialized workers such as welders or pipefitters, who are not only in high demand but also older than the general population. In the U.S., for example, the average age of welders is 55. Due to the growing number of aging plants worldwide, these workers are in high demand. In France, it is estimated that the industry will have to double the number of welders it currently employ by 2030. This perspective means that operators may need to train these technicians themselves—a challenge that EDF decided to tackle head-on by training and qualifying 500 welders a year to support the Hinkley Point C project in Somerset.

Another essential effort to address these shortages is to optimize the time and tasks these technicians perform. This is most effectively done by digitizing processes such as permits-to-work, logbooks, and work orders, using specialized operations management software. Such software is designed to meet the criteria of internationally recognized standards, notably the health and safety guidance HSG250 and HSG253 in the UK.

This digitization can also help reduce the time spent on reporting or routine checklists, and therefore, maximize the time-on-tools of skilled workers. Combining this digitization of operations to other streams of data, such as programmable logic controllers (PLCs) and supervisory control and data acquisition (SCADA) or enterprise resource planning (ERP) systems, is key to make health monitoring and maintenance more predictive and maximize the effectiveness of existing maintenance workers.

AI to the Rescue

Another crucial operational challenge in the wake of this generational shift is the risk of losing implicit and tacit knowledge from seasoned employees if this wisdom is not captured or passed on. The problem is two-fold: identifying how work is actually performed and making this knowledge accessible to reduce the learning curve and avoid human errors by new hires. These challenges have led several nuclear operators to invest heavily in the digital capture and organization of operating procedures, which can run into tens of thousands.

This is a field where the application of artificial intelligence (AI) is increasingly prevalent, whether to convert paper-based and computer-based procedures into truly digitalized ones, organize information, standardize the language used and adopt a step-by-step structure, or make procedures reusable across similar equipment. The objective is not to have the machine write procedures, but drastically reduce the time and effort required from subject-matter experts and eliminate the clerical work traditionally associated with procedure management. The International Atomic Energy Agency (IAEA) sees such uses of AI as holding “promising potential for advancing nuclear energy production” while alerting on the need for supervision and explainability of the models being used.

This outcome is critical as the industry faces the prospect of seeing a generation of experts retire and a relative lack of junior experts. The end-goal is to ultimately connect those two efforts—digitization of operations and digitization of procedures—to facilitate learning, ensure compliance, and deliver material safety improvement.

Next-Generation Tools for the Next Generation of Workers

As the industry shifts to automation and digitization, a question remains: Will it be enough? One thing is certain—no matter how productive these efforts are, the industry will still need to hire massively if it is to meet global objectives and increase capacity to meet COP28 objectives.

In 2023, McKinsey estimated that the industry would need to grow its global headcount to 5 million people to increase its output by 50 GW every year and thus meet 2050 net-zero objectives. In some countries, such as the U.S. and Canada, this could represent a five-fold jump compared to current numbers—a particular challenge when the number of engineering students choosing to specialize in nuclear engineering reached an all-time low in 2022.

However, these technological advances remain critical to reduce these numbers and minimize the operational impact of the generational handover. And, as the industry tries to attract new workers and boost its attractivity by showcasing new projects, such as small modular reactors (SMRs), the European Pressurised Reactor or Evolutionary Power Reactor (EPR), or sodium-cooled reactors, it is essential that the work experience it provides does not remain stuck in the past century.

Peter Wilson is an executive industry consultant in the Asset Lifecycle Intelligence division with Hexagon.

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