The global energy transition, catalysed by further investment in renewables, faces a critical bottleneck: there is a massive shortage of specialised energy engineering talent. International Energy Agency (IEA) projections indicate that achieving Net Zero by 2050 requires the creation of 30 million new clean energy jobs by 20301. By 2030, the world will be short by seven million skilled workers in renewable energy, requiring skills in engineering, project development, and technical installation2. Looking at the utility-scale sector alone, $12 billion will be spent on designing utility-scale solar projects over the next five years, which translates to roughly 12,000 work years.
“This imbalance points toward the urgent need for engineering automation tools to dramatically accelerate the output and effectiveness of the existing global engineering workforce,” says Paul Nel, CEO of 7SecondSolar. “Computational tools like AutoPV™ can knock months off a project timeline for a utility-scale solar plant. Software like this can generate construction-ready outputs for multiple utility-scale solar designs for a project in a matter of a few hours. This enables energy engineers to compare multiple layouts and configuration options, and focus on value engineering.”
The severity of this skills shortage is evident across major international markets. South Africa, a growing renewable energy hub, operates with fewer than 40,000 registered professional engineers3. In Germany, more than 18,300 vacancies could not be filled in energy transition-related sectors in 20244. France’s electricity network alone needs to recruit 43,000 people by 2030 to adapt its grid for renewables, while Australia anticipates a shortfall of 17,400 critical energy sector workers by the same year. This global challenge confirms that human capacity, not just finance, is the core limiter of renewable energy deployment.
The scale of the clean energy transition needs more capacity and output from the engineering workforce. By 2030, global installed solar PV capacity is expected to exceed 7 Terawatts (TW), representing roughly 65% of the 11 TW global renewable energy target set at COP28. To manage the design and deployment required to meet this massive capacity, engineering toolboxes should include automation software.
A major focus should also be placed on the educational pipeline. Research shows that 68% of the world’s energy education degrees are still focused on fossil fuels, while only 32% cover renewable energy5. As this balance rapidly shifts toward clean energy, it is vital that tertiary institutions incorporate the use of automation and computational tools into their curricula. This will ensure that emerging engineers entering the field are immediately capacitated to manage the complexity and scale of modern renewable infrastructure projects.
“The energy sector can no longer afford the months-long manual processes traditionally required for a single utility-scale project design. Computational software must become the new baseline for engineering education and practice,” adds Nel. “The reality is that we are unlikely to add the required seven million skilled renewable energy engineers to the workforce by 2030. In light of this, we now need to look at multiplying the productivity of every single engineer and guaranteeing we deliver optimal, bankable projects at the speed.”
