Navigating Labor Force Implications in an Era of Uncertainty

Ongoing economic uncertainty, evolving trade policies, and rapid advances in technology have converged to create a new sense of urgency around how companies manage risks within their supply chains. While some organizations are responding to uncertainty with long-term supply chain shifts, others are leaning into asset optimization – a strategy focused on maximizing the value of assets an organization already owns – as a way to potentially offset operational impacts of various supply chain risks while at the same time maximizing assets and unlocking competitive advantage.

Yet, as some supply chain leaders have discovered, the journey toward asset optimization can also bring a host of labor force implications that must be addressed to realize this strategy’s full potential.

The labor equation in asset optimization

Labor market pressures in supply chain operations are nothing new: high turnover, skills shortages, and demographic shifts have tested organizations for years. According to a 2025 survey of chief procurement officers (CPOs), nearly 45% of surveyed CPOs continue to struggle with attracting top supply chain talent, while 31% say retaining that talent is a persistent challenge. Coupled with an aging workforce and evolving skills requirements, these stressors all underscore why supply chain labor remains central to any supply chain strategy discussion, including asset optimization.

This is a good reminder that decisions about how assets are managed can significantly influence both operational outcomes and the workforce. When organizations lack efficient processes or timely, actionable information about asset health and performance, both operator and technician roles can be affected, making it harder to operate equipment safely, respond to maintenance needs, and coordinate activities across teams. Addressing these challenges is essential not only for operational success, but also for supporting and empowering the people who use and maintain these assets.

Training and upskilling: Critical pathways

As companies ramp up utilization rates of machinery, facilities, and technology, the demand for skilled workers intensifies—not just to operate assets, but to maintain them. And yet the skilled labor needed to support higher asset usage is not always available to tap into: a 2025 study found that 80% of the surveyed manufacturers have experienced production disruptions due to workforce turnover alone, with over half reporting moderate to severe bottom-line impacts.

These disruptions elevate the importance of talent retention and skills development strategies, especially when institutional knowledge and experience are at risk of being lost. To address this, some organizations are scaling up training initiatives – especially related to AI. Others are leaning into automation and digital solutions to help bridge human labor shortages in select operational areas.

AI as a workforce multiplier

Technology’s role in optimizing supply chain assets extends well beyond automating manual tasks or robotics, with a lot of energy now focused on AI as a key differentiator and workforce companion. In fact, nearly half (49.4%) of surveyed procurement leaders reported that one of the top value drivers of Generative AI (GenAI) within sourcing and procurement will be productivity gains.

AI-powered predictive maintenance solutions, for example, are enabling organizations to track asset performance, anticipate repair needs, and schedule maintenance proactively, rather than just when things go wrong. Poor maintenance strategies can reduce an asset’s overall productive capacity by 5-20%, so a focus on proactive, predictive maintenance can not only lengthen asset lifespans and support cost savings efforts, but can also energize the workforce—transforming technology from a potential threat into an empowering tool for technologically-savvy employees. By integrating AI with maintenance processes, companies can help workers collaborate with advanced technology, fostering innovation and engagement on the shop floor, and even helping employees feel directly connected to the success of their organization.

Supply chain leaders also recognize the value that AI can have in workforce knowledge management, a key area of growing concern as many supply chain professionals who hold vast amounts of industry knowledge and on-the-job experience approach retirement age. In that same CPO survey referenced earlier, nearly 23% of procurement leaders identified improvement of knowledge management across sourcing and procurement functions as a value driver of next-generation AI technologies.

By cataloging historical maintenance decisions and best practices, organizations can use AI to preserve both explicit and tacit knowledge from their existing workforce, as well as to offer tailored repair suggestions for future maintenance needs. This AI repository of collective workforce expertise can further be refined by technician feedback to enrich the knowledge base, support ongoing improvements in asset health, and drive overall organizational resilience.

Turning challenges into opportunity

Asset optimization offers companies a powerful way to bolster supply chain resilience and maximize return on investment in uncertain conditions. But its success depends heavily on the teams that operate, maintain, and improve those assets. Labor force implications—from upskilling and talent retention to technology adoption and knowledge transfer—should  be considered early and often to help ensure that organizations are not just maximizing machinery, but also empowering the people that power them for the future.

As leaders continue to rethink assets and labor alike, integrating technology, process improvements, and data-driven insights will be essential to navigating uncertainty while building a supply chain that is both resilient and ready for what comes next.