A hidden growth barrier for industrial manufacturers? Their workforce

As industrial manufacturers race to invest in technology, some may be overlooking a more central issue: the capabilities of their workforce. In PwC’s Global Industrial Manufacturing Sector Outlook 2026, companies expect tech enablement and automation to more than double by 2030. Leaders are investing in AI to improve operations and rolling out integrated, connected products and services. To win in that environment, 70% of IM executives rate “developing new capabilities internally” as their top means of accessing growth opportunities.

Yet the survey also suggests that key capabilities required to realise these ambitions could be underdeveloped relative to their importance. In particular, the findings show potential blind spots in digital and data infrastructure, workforce upskilling and reskilling, and analytics and decision intelligence. These are all prerequisites for the faster learning and smarter decision-making needed to compete in a more AI-enabled and automated industrial future.

Other research reached similar conclusions. Previously unpublished data from PwC’s Global Workforce Hopes and Fears Survey 2025  shows that fast, agile cultures may be less common in IM than other sectors. Consider that just 56% of industrial manufacturing workers (above entry level) felt it was safe to try new approaches, 55% said failures were treated as learning opportunities, and 46% said it was safe to experiment. These numbers were all lower than for executives.

Similar disparities appear in upskilling, where fewer than half of non-managers said they had adequate access to learning resources, versus two-thirds of managers. And trust levels were low. Just half of industrial manufacturing workers above entry level said they trust their managers, and just 42% trusted top leadership, both markedly worse than global averages.

IM companies can build an AI-enabled culture and workforce by focusing on three areas:

Benchmark your performance against peers. Leaders often have an overly positive sense of their organization. A formal benchmarking process covering operational and culture metrics gives clearer signals grounded in objective data about where to double down, course-correct, or rethink assumptions.

Give employees the digital skills they need. The best upskilling and reskilling programs embed tools directly in workers’ daily processes. They also use technology to teach technology, like virtual- or augmented-reality solutions to make training more effective. And they emphasize data literacy.

Double down on trust. As our experience (and the Hopes and Fears survey findings) suggests, trust is a measurable operational constraint—affecting willingness to learn, experiment, and adopt new ways of working. Scan carefully for ‘say–do’ gaps on issues of training and capability development, as discrepancies will quickly corrode trust.