Despite the growth of automation in the supply chain, manufacturers and distributors still face numerous labor challenges driven by increased demand, rapid fulfillment cycles, and SKU proliferation. Many businesses are building inventory levels to avoid tariffs, creating additional labor needs for storage and handling. As peak season demand spikes, warehouses struggle to maintain a full labor pool. Turnover rates that often exceed 40-50% annually make it even harder to retain skilled labor.
Other labor challenges stem from an aging workforce, with a significant portion of the U.S. warehouse workforce aged 50 or older. As these workers retire, hard-to-fill positions open. Younger workers lack the knowledge of more experienced workers, and the younger generation doesn't particularly want to work in high-intensity environments. Veteran workers often hold deep tribal knowledge, such as how to manage a bottleneck or how to balance labor across zones. This loss of tribal knowledge reduces operational efficiency and decision quality.
When employees spend long hours picking, packing, and loading with little variation, it's easy for motivation to drop. That disengagement deepens when workers don't have a clear sense of how their efforts connect to bigger company goals—like meeting on-time, in-full delivery targets or maintaining strong customer service levels. Miscommunication or lack of context often leads to frustration, mistakes, and wasted effort.
To address these labor challenges, companies deploy automation to take on repetitive, time-consuming tasks and streamline manual processes. Robots, AGVs, AS/RS, automated palletizers, and more are costly. They can improve efficiency and performance, but the return on investment can take a long time to recover.
While automation can improve efficiency and performance, there comes a point when the equipment is only as fast as the humans that run it. Workers are often required to work alongside automation, ensuring it functions correctly, intervening when it malfunctions, and providing the human touch where automation falls short.
When it comes to tackling today's warehouse labor challenges, companies usually take one of two paths: work harder or work smarter.
· Working harder means getting more out of the existing team through stronger training programs, clearer performance goals, and better recognition or incentives that keep people motivated on the floor.
· Working smarter focuses on rethinking how the work gets done. This includes simplifying processes, investing in better systems, and adopting technologies that remove friction so every shift runs more efficiently.
The labor challenge isn't just about hiring more people; it's about how intelligently and dynamically organizations deploy the people they have.
From labor management to labor intelligence
A labor management system (LMS) is software that helps warehouses and distribution centers understand and improve how work gets done. It tracks how employees spend their time, how long specific tasks take, and how performance compares to established standards. With this information, managers can detect improvement opportunities such as balancing workloads and planning shifts. But while traditional LMS tools do a great job of tracking and reporting what's already happened, they often struggle with last-minute changes and balancing peak workloads.
The next evolution in labor management is intelligence, with newer AI-driven systems that add predictive and adaptive capabilities. These systems use data, analytics, and AI to understand and optimize work. They can forecast workload hour by hour, simulate labor needs across shifts, and dynamically reprioritize tasks based on real-time conditions.
When an inbound truck is delayed or a production run finishes early, the system can suggest how to reallocate teams to prevent downtime. Labor intelligence systems focus on predicting needs, anticipating disruptions, and guiding action in the moment. They create adaptable plans that improve productivity and reduce labor strain.
As supply chains embrace intelligent systems that connect planning with execution, labor will cease to be a constant emergency and become a controllable variable. Companies that master this shift will outperform peers not because they have more workers, but because they make better, faster decisions with the workers they have.
How Agentic AI can empower humans
The biggest fear around accelerating decisions is losing control. Many operations hesitate to delegate decision authority, whether to algorithms or frontline teams, because visibility and trust are lacking. This is where Decision Agents enhanced by Agentic AI come in. Rather than removing people from the process, these systems orchestrate data and recommendations to enable faster, context-rich decisions with transparency.
AI agents think, learn, and act independently. They make decisions, adapt, and learn in real-time. However, humans are still needed within the decision-making agenda. Machines lack emotional intelligence, ethical reasoning, and contextual nuance—and it is these qualities that build trust. Human supervisors remain the final authority, but they operate with real-time foresight rather than post-event hindsight.
When issues are resolved in seconds rather than hours, everything starts working better. On-time performance improves. Labor is used more effectively. Equipment and docks stay balanced. Planners can adjust to demand changes before they get out of hand.
The speed at which an organization can make decisions is called decision velocity, and it is fast becoming a measure of warehouse performance among ongoing labor challenges. In fast-moving environments where demand, order mix, and workforce availability shift hourly, the ability to make quick, informed decisions directly impacts throughput, cost, and employee morale.
High decision velocity empowers managers to move from firefighting to forward planning—ensuring labor resources are deployed where they'll have the most significant impact. In an era where every minute of labor counts, faster, more intelligent decision-making is the new competitive advantage.
