Harnessing AI in renewables| power and nuclear

Only 18 months ago, artificial intelligence shot to mainstream fame with the unassuming launch of ChatGPT. Now, generative AI discussions are ubiquitous. In parallel, the energy industry has been quietly innovating use cases for AI for some time, explains Peter Denham of Airswift.

The results of this year’s Global Energy Talent Index (GETI) suggest the industry may be on the verge of a significant uptick in AI use, as growing interest motivates more power, renewables and nuclear companies to explore ways to integrate AI tools into their operations.

Around one-third of professionals in renewables (32%) and power (30%) already use AI as they stand on the brink of a technological revolution. Meanwhile, 27% in the nuclear sector say the same.

This compares favourably to more traditional industries such as oil and gas, where less than a quarter (24%) of professionals use AI.

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Thirty-three per cent of companies have an AI policy, a figure that aligns closely with the proportion of companies that use AI.

However, about a third of professionals admit they haven't read these policies. This oversight leaves companies vulnerable to data misuse, ownership disputes, intellectual property issues, and cybersecurity.

Over the coming months and years, focusing on training and change management will be crucial. This approach will help manage risks and seize opportunities in the rapidly evolving AI landscape, ensuring resources are aligned with these objectives.

Popular AI use cases in energy

Across the energy industry, professionals say that a lack of clarity and insufficient investment are the main challenges to making greater use of artificial intelligence. This hesitance is reflected in the relatively limited AI use cases identified by GETI respondents.

That said, most respondents are optimistic about the future, highlighting a recognition that AI use is only likely to accelerate from here.

As global skills shortages increase demands on existing workers, automating repetitive tasks has become a strategic priority for many companies across power, renewables and nuclear.

The report also reveals a clear trend in using AI to mine data for insights – whether to improve safety, increase energy production, optimise energy products and services, or support the innovation of new ones.

AI is increasingly being used to tap into the vast amounts of untouched data that energy companies own to create new differentiators and increase market share.

Power

Professionals in power report that the top uses of AI are automated workflow and workplace collaboration tools (27%). This is followed by:

• Remote monitoring and automation (26%)
• Data analytics to improve energy production (25%)
• Safety and inspection improvements (25%)
• Innovating new products and services (22%)

Renewables

In renewables, the results are broadly similar, with automated workflow and workplace collaboration tools (30%) and data analytics to improve energy production (28%) being popular use cases.

The use of AI for customer engagement (23%) comes slightly ahead of safety and inspection improvements, remote monitoring and automation, and optimising energy products and services (all 22%).

Nuclear

In nuclear, professionals highlight the same trends with the use of AI to:

• Automate workflow and workplace collaboration tools (26%)
• Improve energy production with data analytics (23%)
• Manage safety and inspection improvements (23%)
• Innovate new products and services (19%)
• Although AI-enabled remote monitoring is used to a lesser extent (18%)

The report suggests that several AI use cases will continue to have positive benefits over the next two years

Respondents across the energy sector say AI will continue to:

• Improve predictive analytics and forecasting
• Reduce labour costs through automation
• Increase research, development and innovation.

Interestingly, respondents are less convinced about AI's ongoing improvement of workplace safety.

This is perhaps partly because some workplace safety benefits are borne out of continuous plant monitoring and better predictive analytics.

The outlook for the future

The subsectors tend to agree that productivity will increase.

Yet, power and renewables professionals are much more confident in seeing AI-related salary increases (50% versus 31%) and job satisfaction (63% versus 47%) improvements compared to their nuclear counterparts.

Nuclear professionals are also much less likely to believe that AI will positively impact the time they spend with family and friends (57% versus 31%).

While there's a broad consensus on AI's potential, it's acknowledged that tapping into these opportunities will take effort.

Skills development

Rather than replacing human workers, AI is expected to open new areas that require human skills.

In fact, nearly all (92%) energy professionals say they may be influenced to develop new skills because of AI, and over three-fifths (63%) expect pressure to do so to increase.

Power

In power, the demand for skills across these areas is expected to increase, with power professionals responding in step to meet this demand.

• Programming/software engineering (27%)
• Data science (24%)
• Machine learning (24%)

Critical thinking and IT skills are also high on the list of skills that power professionals say they may develop because of AI.

Renewables

In renewables, there is a demand for skills in:

• IT (27%)
• Programming/software engineering (27%)
• Machine learning (26%)
• Cyber security (24%)

Although there is a slight disconnect in the skills, professionals expect to develop. Programming/software engineering and cyber security appear much further down the list.

While this may not be an immediate cause for concern, given the potential cyber security issues associated with greater AI use, it is undoubtedly one to watch.

Equally, with the proliferation of start-ups and scale-ups within renewables, software skills are critical for supporting the launch and improvement of innovations.

Any skills gap may slow industry progress.

Nuclear

Finally, in nuclear these are the skills that respondents expect to be in greatest demand:

• Critical thinking/problem solving (28%)
• Machine learning (24%)
• IT (22%)
• Creativity / innovative thinking (22%)

However, most nuclear professionals indicate they are more likely to develop skills in:

• Project management (29%)
• Data science (29%)
• Machine learning (23%)
• Data visualisation (23%)

Again, while this may not be an immediate concern, the availability of crucial AI skills should be closely tracked to head off any skills gaps early.

To fully embrace AI in the workforce, businesses must balance transformation and challenge

AI adoption is transforming everything from business processes to energy production, rapidly becoming a key driver of new job and skill requirements.

However, it presents a double-edged sword; while it aims to revolutionise performance, it also introduces cyber security and intellectual property risks.

AI’s impact on the workforce is profound, serving as a crucial enabler of growth by attracting talent and fostering skill development.

Companies that harness AI’s potential to deliver greater productivity, job satisfaction and career progression will likely retain talent more effectively.

About the Author
Peter Denham is senior vice president of Europe & Africa, ensuring Airswift provides an industry-leading service to current and future clients, as well as driving growth across the regions in line with company and regional strategy and goals. Peter has over 20 years of business experience with the last 10 years spent specifically in workforce solutions within the energy market.