The Signal July 2, 2024

Making Peace with GenAI as Job Killer 

IMF economists predict genAI will accelerate job creation, but only after five years of rising joblessness. Supply chain leaders can ease the transition by leaning into training and change management.

Kevin O'Marah Avatar
Kevin O'Marah
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A report published by the International Monetary Fund calls for fiscal policies to soften the pain of employment transitions resulting from generative AI (genAI). The big idea is captured in a graphic projecting five years of rising joblessness followed by accelerating job creation plateauing at a lower level of unemployment. Along the way, those losing jobs are expected to live less well during the transition but end up 10% better off in the long run. 

Line graph showing unemployment rate against consumption by unemployed worker by quarter.
Source: International Monetary Fund

I have been asked about this report by several supply chain leaders over the past two weeks, many of whom believe they own a big chunk of this challenging transition. The question is how to navigate technology adoption when it is obvious that jobs will be lost while business output grows. 

Everyone Gets a Super Smart Intern 

Some have described genAI as a tireless intern that can help knowledge workers get a quick start on almost any task, provided they are asked the right questions. For example, compiling a first draft of SKUs to trim in an assortment simplification effort, or a list of suppliers to upgrade to strategic status, or a record of risky ports to avoid are all natural genAI use cases that could also be handled by a smart intern. 

Applications like Aera Skills, implemented at Mars Wrigley, use AI to ferret out details behind out-of-stocks that are simplified down to a handful of “reason codes in SAP.” Just like a great intern, this system helps supply chain team members dive deep on why shipments go wrong so they can figure out how to make the process better.  

Before AI, such root cause analysis was slow, manual, and error-prone. With AI, people skip the drudgery and go straight to problem-solving, which is more valuable to the business and more rewarding for most people.  

Less Work, More Purpose 

The takeaway from the intern analogy is that leaders are increasingly in a position to elevate job design from the dehumanizing approach made famous by Frederick Taylor in 1911. Taylor said of his Scientific Management theory, “In the past, man has been first, in the future, the system must be first.” He may have been right about system productivity gains, but the resulting mindless work has been parodied by everyone from Charlie Chaplin to Lucille Ball

Job elimination through AI is certainly a concern, as chronicled in research by McKinsey and others. But it is also a powerful transformer of jobs, shifting hours spent away from rote tasks in favor of more creative work. BCG’s most recent survey on AI at work, for instance, found that over 80% of employees believe that genAI freed up more time for strategic work and decreased time spent on administrative tasks. 

Own the Transition with People Development 

For supply chain leaders facing the tug-of-war between investors expecting labor cost savings and employees worried about job security, the best answer is leaning into the transition. This means investing time, money, and credibility in educating teams about AI and its uses.  

Intuit, for example, offers lunch-and-learns, online courses, and in-person boot camps focused on AI and data science training. It has also created a seven-month apprenticeship program open to non-technical employees looking to build skills in areas like machine learning and software development. 

PepsiCo is another organization that bets big on training. In 2022, it launched the Digital Academy, which provides integrated digital learning segmented by role and level, complete with ​certification and badging. Alibaba takes this further still, offering an internally developed genAI engineering course, meant for employees, to its customers and partners. 

Speak Truth to Power 

Beyond training people and looking for ways to design better work, supply chain leaders should also be honest about the impact of AI on jobs. The IMF’s report was written by and for economists whose mission is to recommend taxes and social welfare spending to ease the transition for displaced employees. 

Economists need, but often lack, the practitioner’s view of how technology changes specific jobs. Sharing your plans and challenges publicly may influence policy while building trust and transparency in your own organization. 

There is light at the end of this tunnel.