U.S. manufacturing will need to fill approximately 2.3 million technician positions between 2025 and 2030, with nearly half the solution coming from workers in adjacent industries like construction and retail who possess transferable skills. Embedding generative AI directly into technician workflows, rather than layering it on top of existing processes, can close skill gaps and accelerate productivity while making technician roles more attractive to younger workers.
- 2.3 million technician openings will need to be filled in U.S. manufacturing by 2030, with roughly 500,000 roles open today
- Nearly 2 million qualified technicians work in adjacent industries (construction, retail, wholesale, government) with transferable skills in troubleshooting and equipment maintenance
- AI works best when embedded directly into technician workflows rather than added as separate training, enabling real-time guidance and reducing barriers to entry
- Companies that redesign workflows around human-AI collaboration are twice as likely to outperform on AI ROI compared to those bolting AI onto existing processes
- AI fluency is becoming essential to technician job descriptions, including prompt design, output interpretation, and ethical decision-making skills
Between 2025 and 2030, Deloitte and the Manufacturing Institute (MI) estimate that U.S. manufacturing technician employment will grow six times faster than employment in production occupations. When retirements and other workforce exits are included, employers will need to fill roughly 2.3 million manufacturing and adjacent-industry technician openings over that period. Roughly half a million manufacturing-technician roles are open today.
Expanding the Skilled Manufacturing Workforce with AI, published this month by Deloitte and MI, argues the shortage cannot be closed by faster hiring alone, but that generative and agentic AI, applied deliberately, can widen the pipeline and shorten the runway to productivity. Four takeaways from the study stand out for packaging and processing OEMs.
- The next wave of technicians will come from adjacent industries. Deloitte’s analysis identifies nearly 2 million technicians working outside manufacturing — in construction, retail trade, wholesale, government, and other services — whose broad capabilities and preparation pathways (technical certificates, apprenticeships, associate degrees) map cleanly to the three manufacturing categories the study defines: advanced manufacturing technicians, maintenance and repair technicians, and quality and laboratory technicians. These workers share transferable skills like troubleshooting, equipment maintenance, and quality control analysis. What they typically lack is domain-specific knowledge of production processes and electronics. The report suggests AI is well suited to close this gap.
- AI’s role is to put expertise inside the workflow, not around it. The core mechanism the report describes isn’t AI-driven hiring or AI training courses; it’s embedding learning, guidance, and expertise directly into the tools technicians use. Deloitte’s example: a new manufacturing maintenance technician could capture a video of an unfamiliar equipment problem, have AI analyze it, and receive recommended troubleshooting steps within minutes rather than waiting for a remote expert. That capability lowers barriers to entry for less-experienced workers and frees experienced technicians to focus on higher-value tasks like process improvement.
- Companies that redesign workflows outperform those that layer AI on top. According to a Deloitte study cited in the report, companies that redesign technician workflows around human-AI collaboration are twice as likely to outperform on AI-related return-on-investment expectations as those that bolt AI onto existing processes. That distinction matters because the report frames the goal as building for what technicians will need in the next three to five years, not what today’s workflows require.
- “AI-fluent” is becoming part of the technician job description. The study argues that manufacturers should be defining new skill sets now — foundational AI literacy (prompt design, output interpretation, validation) alongside higher-order skills like oversight, orchestration, exception handling, and ethical decision-making. The dual benefit is that technicians become more effective, and the roles themselves become more attractive to Gen Z and millennial workers, who value on-the-job learning and clear development pathways.
“AI has the potential to change not only how manufacturing work gets done, but how people prepare for and succeed in these critical roles,” said Manufacturing Institute President Carolyn Lee. “By building AI fluency and digital skills into the training programs we already know work, we can prepare more people for the jobs of the future, close critical skills gaps, and strengthen America’s manufacturing workforce.”
“AI could help manufacturers make technical expertise more accessible while preserving the judgment and experience of the people doing the work,” said Steve Shepley, Industrial Products and Construction Sector leader at Deloitte. “The industry now has the opportunity to redesign workflows, broaden pathways into technician roles, and give workers the support they need to develop and perform in more complex jobs.”
Packaging and processing OEMs face the same technician shortage the report describes, as the maintenance techs, controls specialists, and quality engineers who install and support machines are the same population Deloitte says is running out. But OEMs also sell into customer environments where those roles are increasingly hard to staff. Machines that come with embedded AI-assisted troubleshooting, guided-changeover workflows, and controls that surface the right information to a less-experienced operator will move faster in this environment than machines that assume a veteran technician is always on shift. The workforce constraint is not an HR problem happening somewhere else on the plant floor. It is a design constraint that is starting to shape what OEMs need to build.
