AI and Automation: Can technology help solve the Manufacturing industries skills crisis?
Chris Barlow · Posted on: July 4th 2025 · read
UK manufacturers are not short of ambition, but they are running short of people. With thousands of vacancies across the industry, an ageing workforce and a generation of potential recruits yet to be convinced, the skills gap is widening just as new technologies gather pace. Could AI and automation help bridge that gap?
This theme took centre stage at one of MHA’s pre-awards round tables held in Liverpool on 19 June, ahead of the 2025 Made in the UK Awards.
The session brought together senior leaders from across manufacturing and digital consultancies, and the discussion revealed both optimism and caution in equal measure. While AI offers real promise, it is clear that technology alone is not the answer. Cultural transformation, better education pipelines and inclusive recruitment are also needed if the industry is to meet future demand.
Supporting skills not replacing them
From production planning to product testing, AI is already transforming operations. One firm shared how automation had cut battery testing time from 5.5 hours to just three. In another case, AI-powered reconfiguration reduced a task from seven hours to 30 minutes. This ability to unlock time and efficiency is driving early adoption, particularly in job-shop environments where agility is essential.
However, full automation remains in the distant future. Due to the complex chemistry and variability of materials used in manufacturing, AI often supplements rather than replaces manual processes. Human oversight is still required for validation and many companies continue to rely on experienced technicians for quality assurance.
Younger workers have adapted quickly to new tools, learning through trial and error. However, older employees have expressed concern about the pace of change and fear being left behind. In many businesses, trust in AI remains low. Senior leaders are cautious about over-reliance and continue to cross-check AI outputs manually.
A divided workforce
The conversation highlighted a widening generational divide.
One participant described how a virtual welding simulator helped attract young apprentices but was rejected by experienced welders who doubted its accuracy. This type of cultural resistance remains one of the biggest barriers to widespread adoption.
There was a shared view that AI has potential to act as a bridge between generations. By supporting knowledge transfer and enabling hybrid workflows, it can help businesses retain the experience of older staff while empowering younger employees to lead innovation.
Adoption gaps and missed opportunities
Cost remains a significant hurdle. The initial investment in AI infrastructure combined with energy use and uncertainty about ROI can deter smaller businesses. Many remain unaware of tax reliefs or funding options that could ease the burden.
There was also concern that too few businesses are taking advantage of advisory support or learning from their peers. Participants noted a reluctance within UK manufacturing to share insights or showcase success which slows industry-wide progress. To make the most of AI, organisations need the right strategy, skills and cultural mindset.
AI should not be seen purely as automation but as a tool for augmentation, enhancing human roles not replacing them.
AI should not be seen purely as automation but as a tool for augmentation, enhancing human roles not replacing them.
Looking Ahead
With quantum computing on the horizon the pace of change will only accelerate. If the UK is to remain competitive, manufacturers must act now to modernise not just equipment but working practices and organisational culture.
The conversation closed with a clear call to action:
"invest in training, diversify your workforce and build digital confidence across all levels. AI may be part of the answer, but people will remain at the heart of manufacturing."
Key takeaways
- AI is already improving efficiency in planning, testing and operations but full automation is not yet practical
- Generational differences are creating digital divides; AI can act as a bridge if used effectively
- Cultural resistance and lack of trust remain major barriers to adoption
- Many businesses are unaware of funding and support available for AI implementation
- Successful adoption requires investment in both people and technology
