Australia faces a significant shortfall of engineers. As the net-zero transition accelerates, demanding agile recruitment, targeted upskilling, and smarter tech adoption can help to keep projects on track.
It’s no secret that Australia has a dearth of engineers; we know that Australia’s public infrastructure agenda alone points to an immediate shortfall of roughly 30,000 engineers.
The Australian Engineering Labour Market Overview, published by Engineers Australia in August 2024, revealed that vacancies for engineering roles remain stubbornly high, with 6293 advertised positions in May 2024 – 16.8 per cent above the January 2006 baseline.
But it’s not just a matter of head count. These figures highlight an enduring recruitment challenge even as skilled migration rebounds.
Furthermore, the transition to net zero will sustain exceptionally high engineering demand for decades. Engineers Australia forecasts that demand for electricity-sector engineers will remain elevated up to 2030, with the transport and stationary-energy sectors accelerating from 2030 to meet Australia’s 2050 decarbonisation goals.
This demand is further underscored by the rapid expansion of utility-scale renewables and energy storage, which have reshaped the sector’s scale and complexity over the past decade.
Preparing for a renewable future
The renewable energy landscape has shifted significantly in the last 10 years. In 2015, renewable energy contributed roughly 15 per cent of our national electricity, with utility-scale battery storage essentially non-existent on Australia’s grid.
Less than a decade later, Australia’s renewable energy share climbed to 36 per cent, with 12 new large-scale battery projects coming online in the past year alone.
With this growth at scale over a short period of time, Yan Neo, Group Energy Sector Lead at Wallbridge Gilbert Aztec, said it’s unrealistic to expect local engineers to have decades-long experience in this sector.
“The industry didn’t exist then as it does today, and the technology was not applicable,” he said.
The nature of Australia’s renewables sector, which at times struggles to maintain momentum, has also made it challenging to nurture and retain talent.
“The renewables sector, at the moment, is still trying to transition,” Neo said. “We go through periods of big construction and then it drops off, so we haven’t nurtured that skill set consistently.”
And as renewable infrastructure evolves, even engineers considered to have the right skill set will need to be able to adapt.
“We can’t guarantee that it will always be the same for the next jobs,” he said. “So we need to be quite responsive to how things are changing.”
Learn more about the crucial role engineers will play in ensuring Australia can respond with agility and innovation as it heads towards net zero, in this report from Engineers Australia and Mott MacDonald.
Harnessing technology to enhance workforce capabilities
Technology will play a significant role in bridging the engineering skills gap, particularly through infrastructure peaks, Neo thinks.
“There’s been a push to offshore a lot of traditional engineering work, such as engineering drawings, to cut costs,” he said. “Instead, we should look at how some of the smart tools such as AI can be used to help our current engineers locally be more efficient – particularly as we move towards new and emerging sectors. We need to look at it with an agile mindset.”
Take digital twins, for example. These virtual replicas integrated with real-time data can be used to monitor, analyse and proactively maintain solar and wind assets – increasing efficiency and output while minimising downtime and operational risks. They could also help to smooth out extreme labour swings.
“If you can tap into skills that are somewhere else nationally, which has more of an abundance of those skill sets, this can address those skill-shortage issues, and level out those boom cycles you might get.”
Meanwhile, AI-powered predictive maintenance systems can analyse vast quantities of sensor and operational data from renewable energy infrastructure, predicting and preventing failures before they occur – which prolongs asset lifespans and improves sustainability.
But from Neo’s perspective, there needs to be more of a concerted effort to bring these tools into the mainstream.
“I think we still have legacy views of what we can effectively trust with technology, and where it’s being applied,” he said. “Some of the digital twins models, for example, are still very much a nice-to-have. The way some businesses and industries use it, it’s not yet getting into mission-critical type environments.”
This is something Neo thinks needs to shift. “We are under cost pressures, there’s labor shortages and we need to do things efficiently – so we don’t want to have large workforce requirements, and we want to be able to roll out things as optimally as possible.”
Read more: An overview of the engineering labour market in 6 graphs
Cross-skilling talent pools
Beyond efficiency, use of AI and digital platforms can serve as powerful recruitment magnets. For an industry often seen as traditional and process-driven, the lure of cutting-edge AI projects can open doors to candidates who might never have considered engineering.
“The vision is that it can replace a lot of the mundane, repetitive work in engineering, which can attract a different pool of talent that’s maybe not available traditionally,” Neo said. “So it opens up more options in different areas.”
While digital natives may swiftly embrace new tools, seasoned engineers may remain cautious. But it can cut both ways.
“The new generation is adopting tools like AI very quickly, but they likely don’t know where to best apply it,” he said. “And the older generation still may be somewhat resistant to it.”
The next generation of engineers also risks losing sight of foundational principles.
“There is a danger that if we’re too reliant on AI, we won’t know how it came to certain conclusions. So understanding the process is still fundamentally important for engineers,” he cautioned.
Neo believes the future of engineering hinges on tailored training that speaks to both digital natives and seasoned professionals. Think programs where bite-sized e-modules introduce core concepts and interfaces before small cohorts tackle real project challenges together. This way, junior staff share emerging techniques while veterans ground those experiments in domain expertise.
Transparent audit trails, capturing assumptions and versioning, will also help to ensure accountability and preserve deep technical understanding even as machines shoulder routine tasks.
But as tools such as AI become woven into engineering practice, the sector must establish clear guidelines for safe application and accountability to navigate the inherent conundrums of liability and trust.
“If we trust an AI design calculation and something goes wrong, where does the responsibility end, and are we liable for trusting the AI? That’s the conundrum.”
Catch Yan Neo at the Engineers Australia Climate Smart Engineering (CSE) 2025 conference in Adelaide from 27-28 August.
