Could AI And Machine Learning Be The Answers To The Shrinking Semiconductor Workforce
By John Oncea, Editor
The semiconductor industry is staring down the barrel of a potentially crippling labor shortage. One possible fix is leveraging artificial intelligence and machine learning, both of which can help expand talent, augment specialists, and boost semiconductor production.
The semiconductor industry is facing a critical workforce challenge in the coming years. According to a recent McKinsey report, the sector could experience a significant talent shortage of up to 146,000 workers by 2029, spanning both engineering and technician roles.
Despite support from initiatives like the CHIPS Act – which is itself potentially in the GOP’s crosshairs – current workforce development efforts are projected to fall short of meeting the industry’s growing demand. The report projects a shortfall of between 59,000 and 77,000 engineers and up to 69,000 technicians.
These projections highlight the critical importance of developing innovative strategies to address the widening skills gap in the semiconductor industry. As demand for semiconductors continues to surge, this talent gap becomes increasingly vital for the sector's growth and competitiveness.
The industry, along with government and educational institutions, must create comprehensive workforce development programs that can rapidly scale up the skilled labor force needed to meet the challenges and opportunities ahead. It must also consider technologies such as artificial intelligence (AI) and machine learning (ML), both of which are emerging as powerful tools.
Revolutionizing Hiring, Expanding Roles, Retaining Talent
Averroes.ai CEO and AI expert Tareq Aljaber notes that AI is “changing the game by lowering the technical bar required for roles like process engineering and visual inspection.” Where deep technical expertise was once a barrier, AI-driven tools are now stepping in, allowing companies to hire more flexibly without sacrificing productivity.
“The semiconductor industry is facing a critical shortage of skilled workers, particularly in roles like visual inspection and process engineering,” Aljaber says. “However, AI is allowing us to automate complex, repetitive tasks and augment human teams, which makes hiring easier and expands the talent pool.”
Furthermore, AI allows engineers to focus on higher-value tasks like innovation and strategic decision-making. “AI doesn’t replace process engineers but enhances their capabilities,” says Aljaber. “By automating tedious tasks, AI gives engineers more bandwidth to work on solving complex challenges."
As chip complexity and manufacturing demand grow, adds Semiconductor Engineering, AI and ML solutions can accelerate the onboarding process for new hires in the semiconductor industry. AI-powered training programs can provide personalized learning paths tailored to each employee’s background and role. In addition, virtual and augmented reality simulations enhanced by AI can offer hands-on practice in a safe environment while intelligent tutoring systems can provide on-demand guidance as new employees learn complex processes.
By streamlining training, AI enables companies to get new talent up to speed more quickly and efficiently.
Enhancing Productivity Of Existing Workforce
AI tools can boost the capabilities and output of the current semiconductor workforce. For example, according to Applied Energy Systems, AI-driven automation can handle routine tasks, allowing skilled workers to focus on higher-value activities.
In addition, predictive maintenance powered by AI can reduce equipment downtime and increase overall productivity and AI assistants can provide real-time guidance and decision support to workers on the factory floor. This allows companies to maximize the impact of their existing talent pool.
One strategy to help bridge the engineering talent gap is using AI to upskill technicians and expand their responsibilities. According to McKinsey, AI systems can provide technicians with advanced diagnostic and troubleshooting capabilities. At the same time, ML models can assist technicians in performing more complex analyses and optimizations.
Finally, AI-enabled remote collaboration tools can connect technicians with engineering expertise when needed. This approach helps companies address certain engineering shortages by enhancing the capabilities of their technician workforce.
Not only can AI and ML improve hiring and training, it also brings with it the ability to keep talent through tools that can identify promising candidates from non-traditional backgrounds, adds Manufacturing Dive. Predictive analytics can forecast future talent needs and inform proactive hiring strategies. Also, AI systems can analyze employee data to identify flight risks and recommend retention measures.
By taking a data-driven approach to talent management, companies can make smarter decisions about workforce planning.
Fostering Innovation And Research
AI is accelerating semiconductor R&D and enabling breakthroughs that can help address talent shortages. According to Semiconductor Engineering, AI models can rapidly explore new chip designs and materials. Furthermore, machine learning can optimize manufacturing processes to increase yields and AI-assisted knowledge management systems can capture and disseminate expertise across organizations.
Collectively, these AI-driven innovations can help the industry do more with less human capital in certain areas. While AI cannot fully solve the semiconductor talent crunch, it is proving to be an invaluable tool in helping companies navigate this challenge.
By augmenting human capabilities, streamlining operations, and driving innovation, AI is enabling the semiconductor industry to continue advancing despite workforce constraints. As the technology continues to evolve, its role in addressing talent shortages is likely to grow even further.
That said, implementation of AI and ML will require strategic investment in both technology and workforce training to fully realize its potential in augmenting human capabilities rather than replacing them.