Download this article in PDF format.

Just when it felt like supply chains couldn’t come under any more pressure or have the room to manage any other challenges, a new Accenture report finds that the sector is going to be short more than 1.1 million workers by 2035. Technology, automation and artificial intelligence (AI) may help pick up some of the slack, but the number is staggering in an industry that requires a human touch, expertise and oversight to run right.

Accenture does the math in its new report, Turning the supply chain talent shortage into strength. The bottom line: demand across core supply chain occupations in the U.S. will rise by 1.34 million roles by 2035 (19% growth), but the labor force will only add roughly 221,000 workers (just 3.2% growth). That leaves a gap of over 1.1 million.

“Supply chains in the US are facing a serious labor shortage, which threatens the efforts to reshore supply and production,” Tracey Countryman, global lead, supply chain and engineering at Accenture, says in the report. “Companies can tackle this challenge with AI and other technologies, but only if they reshape their workflows and roles within it.”

Accenture says several forces are driving the demand, including economic expansion, nearshoring, agentic commerce, delivery compression, supply base diversification and rising compliance complexity. “Simply hiring more workers is not enough; the math doesn’t work,” it says. “Reshoring efforts, AI-driven commerce, faster delivery expectations and rising regulatory requirements are all accelerating demand for supply chain talent at once.”

Can’t Keep up With Industry Growth

Warehousing, logistics, transportation and everything else that goes into running a supply chain hasn’t historically been a big draw for recent grads, professionals or even career-changers. The global pandemic altered that, bringing supply chain up onto the radar screen of individuals, professional organizations (ASCM, CSCMP, ISM, etc.) and educational institutions, many of which have since rolled out new supply chain-related programs and certifications or refreshed existing ones.

Still, the industry is growing at a clip that’s outpacing those programs—right at a time when roughly 11,000 Baby Boomers reach retirement age every day. That combination, along with various other factors, is leaving a gap in the supply chain sector that can’t always be filled through the usual means (i.e., posting an opening on LinkedIn and expecting the right candidate to come along).

The good news is that technology is helping to even out the imbalance a bit. For example, Accenture simulated how technology adoption could flip the script: In one scenario, the 1.1-million worker shortfall turns into a surplus of approximately 360,000, but that’s only if 75% of the existing supply chain workforce adopts agentic AI, autonomous vehicles, drones and exoskeletons.

3 Ways Tech Can Help Close the Gap

As some industries use AI in place of people, supply chain organizations face a different problem: not enough workers to fill open jobs. Accenture recommends that supply chain executives use technology to reduce routine work, rethink job responsibilities and prepare employees for new duties. 

• Target routine work first. Identify the repetitive tasks consuming employees’ time, such as inventory tracking, record updates, shipping documentation and shipment scheduling, then determine where technology can take over. Accenture says this can help operations handle higher volumes without hiring at the same rate while employees concentrate on exceptions, customer problems and decisions that require judgment. 
  
  
• Redefine roles as tasks change. Decide which responsibilities employees will take on as technology absorbs more administrative work, including system oversight, exception management, data validation and decision-making. Review each occupation separately, Accenture recommends, because office-based jobs may change substantially while roles requiring physical presence or judgment may not. 
  
  
• Train employees for the new work. Focus less on systems that AI and automation can handle (e.g., entering and updating information in enterprise resource planning [ERP] systems, recordkeeping and workflow coordination) and help employees learn how to manage more value-added projects. For example, show them how to review AI output, validate data, manage exceptions and intervene when automated systems fall short.