FEATURE Workforce management
Workforce investment is now an operational and strategic imperative. Manufacturers that combine skilled people with intelligent workforce technology will be better equipped to deploy their capabilities where they are needed, respond to market volatility, withstand prolonged economic uncertainty and build sustainable long-term resilience
and experience on which workforce agility depends. At a time when many firms are delaying recruitment and investment, retaining and making better use of existing talent has become even more commercially important. In contrast to previous periods of uncertainty, manufacturers have another
weapon in their efficiency armoury: AI. Our survey reveals that just over three-quarters (76%) of manufacturers are already using AI to support workforce or production operations. However, only a tenth (11%) say AI has been deployed at scale. Indeed, most organisations remain in the early stages of adoption, with AI confined to pilots or limited use cases. To unpack this a little further, manufacturers primarily view AI as a way to improve efficiency and productivity, with 53% citing these as the main investment drivers. Far fewer (7%) are investing in AI to improve the shopfloor experience. More specifically, AI is being used by manufacturing businesses to reduce the administrative burden on frontline supervisors by automating routine workforce tasks such as shift scheduling or allocating training. Used in this way, AI can support workforce agility by making it easier for managers to respond to changing requirements while enabling organisations to extract greater value from the people and skills they already have.
So, why is there such a pronounced implementation gap? Let’s be clear, running pilot projects is important, but these are generally designed to test individual use cases rather than transform operations. When a pilot needs to be extended across multiple sites and teams, increased organisational complexity is inevitable. So, as AI deployment expands, consistent processes become more important. Ultimately, scaling AI successfully requires organisational readiness as well as technical capability. Another big part of the challenge is that AI implementation is about more than introducing new technology. Employees need to understand how new tools fit into existing workflows, and they must also feel comfortable that it supports their work, rather than complicates it. AI can automate processes and improve decision-making, but it is skilled frontline employees who ultimately drive productivity, quality and innovation on the factory floor.
WorkJam
www.workjam.com
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Automation | September 2026
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