Artificial intelligence could help manufacturers tackle a persistent shortage of skilled technicians by making technical expertise more accessible, accelerating training and opening manufacturing careers to workers from adjacent industries, according to new research from Deloitte and the Manufacturing Institute. The study estimates that employers could need to fill 2.3 million technician openings between 2025 and 2030, creating a growing role for AI in workforce development.
Manufacturing’s workforce challenge is increasingly becoming a skills challenge rather than simply a headcount problem. As factories adopt automation, connected equipment and more sophisticated production systems, employers need technicians capable of working across mechanical, electrical, digital and control technologies.
A new study from Deloitte and the Manufacturing Institute (MI) suggests artificial intelligence could help address that gap by changing how workers acquire and apply technical knowledge.
The research focuses on manufacturing technicians and workers in adjacent industries whose skills could transfer into manufacturing. Deloitte and MI identify nearly 2 million technicians in adjacent industries whose capabilities may provide a broader talent pool for manufacturers.
The opportunity is significant because demand for technicians is projected to accelerate. Deloitte estimates manufacturing technician employment could grow six times faster than production occupations between 2025 and 2030. Across manufacturing and adjacent-industry technician occupations, employers may need to fill approximately 2.3 million openings during that period because of employment growth, retirements, other labor-force exits and occupational transfers.
That changes the potential role of AI in HR and workforce management.
Rather than using AI primarily to eliminate repetitive tasks, manufacturers could use it to lower the knowledge barrier for workers entering more technical positions. A worker moving from an adjacent occupation, for example, may possess mechanical troubleshooting or equipment-related skills but lack manufacturing-specific knowledge.
AI could provide contextual guidance directly within the workflow, helping that employee understand unfamiliar equipment, procedures and technical information without requiring constant access to a senior technician.
Deloitte’s research describes this as embedding expertise into the flow of work. A maintenance technician could use AI to analyze an unfamiliar equipment problem and receive troubleshooting recommendations, while a semiconductor technician could potentially combine manufacturing execution system, statistical process control and equipment data to investigate a yield issue.
The model also has implications for experienced employees.
Instead of positioning AI exclusively as a training tool for new hires, manufacturers could use it to help existing technicians handle more complex work. AI systems could analyze equipment histories, alarms, control-system information and other operational data, allowing technicians to spend less time searching for information and more time making decisions.
That could become increasingly important as manufacturers compete for workers with technical skills.
Deloitte’s 2025 Smart Manufacturing survey found that 48% of respondents reported moderate to significant challenges filling production and operations management roles, while 46% reported similar challenges for planning and scheduling positions. More than one-third also identified adapting workers to the factory of the future as a major concern.
The new study therefore puts AI into a broader workforce strategy. The technology is not being presented simply as an automation layer but as a mechanism for expanding talent mobility, accelerating skills development and making technical expertise more accessible.
That distinction is important for HR leaders. If AI is introduced primarily as a labor-reduction program, employee resistance could become a significant barrier. If it is designed around skills development and augmentation, organizations may have a stronger argument for adoption.
The challenge will be ensuring workers know how to use and evaluate AI-generated recommendations. Deloitte recommends that manufacturers develop AI-enabled technician skills that include foundational AI literacy, output interpretation and validation, alongside higher-order capabilities such as oversight, exception handling and strategic decision-making.
Training programs will consequently need to evolve as well. Traditional classroom instruction and apprenticeships could be supplemented by AI-enabled coaching, diagnostics and digital work instructions. That could allow learning to happen closer to the point where a worker actually needs the knowledge.
There is already movement in this direction. The Manufacturing Institute announced in April 2026 that Google.org had committed $10 million to expand its Federation for Advanced Manufacturing Education (FAME) program and incorporate AI skills into technician training. The initiative combines classroom education with paid work experience and aims to connect emerging AI capabilities with advanced manufacturing systems.
For HR technology providers, the development points toward a more skills-based model of workforce management. HR platforms may increasingly need to connect employee skills, learning pathways, operational requirements and AI-enabled work environments rather than treating recruiting and training as separate processes.
It also strengthens the case for internal mobility. Workers in production or adjacent industries may have enough transferable skills to move into technician roles if organizations can provide targeted training and contextual assistance.
Yet AI will not eliminate the underlying skills challenge on its own. Manufacturers still need credible career pathways, technical education, experienced mentors and systems that encourage workers to trust and appropriately challenge AI recommendations.
Deloitte’s 2026 Global Human Capital Trends research found that 85% of respondents consider workforce adaptability important, but only 7% say their organizations are making significant progress toward it.
The emerging lesson is that AI may be most valuable when it makes human expertise more scalable.
For manufacturers, that means using AI to help more workers perform technically demanding jobs, giving experienced technicians tools to operate at a higher level and creating pathways into roles that previously required longer periods of specialized experience.
As factories become more automated, the winning workforce strategy may not be to find fewer people. It may be to make a larger and more diverse pool of people capable of doing more complex work.
Market Landscape
Manufacturing is moving toward increasingly connected, automated and technology-intensive production environments, increasing demand for technicians who can work across multiple technical domains. Deloitte’s research identifies AI as a potential bridge between existing worker capabilities and the specialized knowledge required by modern factories.
The opportunity extends across recruiting, learning and development, internal mobility and workforce planning. HR technology providers can increasingly connect skills data with learning recommendations and operational requirements, while industrial AI platforms can deliver knowledge directly to workers.
The larger competitive question is whether manufacturers use AI primarily for automation or as a workforce multiplier. Deloitte’s research strongly points toward the latter approach, combining AI with redesigned workflows and human expertise.
Top Insights
- Manufacturing technician employment could grow six times faster than production roles, intensifying competition for workers with specialized technical capabilities.
- AI could expand manufacturing talent pools by helping workers from adjacent industries bridge gaps in domain-specific knowledge.
- Embedding AI guidance directly into workflows could accelerate technician development while reducing time spent searching for technical information.
- Manufacturers will need AI literacy, validation and oversight skills alongside traditional mechanical, electrical and engineering capabilities.
- The strongest workforce strategies may use AI to augment experienced technicians while creating new pathways into higher-skilled manufacturing roles.
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