Summary
Fears of AI replacing jobs are reminiscent of the debut of the tractor in the late 1800s—the workforce evolved, spectacularly.
AI will disrupt labor more than technology. The global workforce of 3.5 billion people—each earning $15,000 per year, on average—will evolve in similar fashion.
Employers have an obligation (and an opportunity) to retrain employees, particularly roles must susceptible to AI elimination. Employees also have a decision: hate it, or harness it.
Fear on the farm
In 1892, a German Iowan named John Froelich (fray-LICK) invented the first gas-powered tractor. It weighed over 10,000 pounds. But the cost was light: you could run one for $2 a day ($70 today)—50-70% less than the steam alternative. And more reliable than the incumbent horse.
Like most new technologies, society didn’t welcome tractors. “Our livelihood is threatened,” exclaimed one South Dakota farmer. Not surprising at a time when agriculture employed 33% of Americans producing 15% of GDP. Surely, a rustic farmstead was no place for hulking machinery. Nevertheless, capitalism thrusted forward:
Farmers could now manage more land with the same number of workers.
Millions of workers were freed up to work in manufacturing and services.
In the moment: terrifying. In hindsight, spectacular.
AI will disrupt labor more than technology
Last month I presented at an AI conference in Chicago. My lofty topic: “The Future of Work in the AI Era.” I opened with the below slide depicting the Mensa IQ of OpenAI’s latest model (o1-preview). The audience leaned in.
Not unlike the tractor’s debute, most of the questions I received were around AI replacing jobs. My reply: “It depends on how you define ‘job.’ AI replaces tasks. And if your job is solely those task, AI will replace it.”
[silence]
I continued with cautious optimism: “So we are at a collective decision point as a workforce: Hate it, or harness it.”
The latent fears during my presentation capture a truth the headlines often miss: AI will predominantly disrupt labor. For every headline on LLM wizardry, Nvidia Blackwells, or Mag 7 compute, the inevitable truth remains: AI will shift the definition of work. And from an evolutionary perspective, that’s okay.
Workers of the world, defined
There are 3.5 billion workers in the world contributing to a global GDP of $100 trillion (the US is $27 trillion of this). Wages now constitute 52.3% of global GDP (in the 1940s it was 64%), so suffice to say $52.3 trillion hits paychecks each year. Across the 3.5 billion workers, this equates to an average annual income of ~$15,000.
Behold, our worker bee.
And, crucially, this income drives “consumption”—what we spend our money on—which is 60% of global GDP. AI-replaced jobs, therefore, threaten consumption. But only if you ignore evolution.
Workers of the world, retrain!
Claims of AI creating a “cognitive revolution” or “a new electricity” are likely hyperbolic. Let us be grounded by the words of John McCarthy (who coined the term artificial intelligence):
“As soon as it works, no one calls it AI anymore.”
Mustafa Suleyman, cofounder of DeepMind and current CEO of Microsoft AI, builds on McCarthy’s observation:
“AI is—as those of us building it like to joke—what computers can’t do. Once they can, it’s just software.”
What should we focus on? How we re-skill employees. The AI wave is building, and we must teach people how to surf—or in the very least, swim. Let’s start with the to-be swimmers.
According to one study, the top 5 jobs at-risk of AI subsummation are:
Data Entry and Processing (Applied Industrial Technologies case study)
Customer Service Representatives (Klarna case study)
Manufacturing and Assembly Line Workers (Westheimer Brewery case study)
Transportation and Logistics (McKinsey study)
Retail Salespeople (Statistica study)
These folks have a right to know. Employers would be well-suited to 1) identify their transferable skills during performance reviews, 2) be candid about the future, and 3) give them opportunities/support to interview for new roles—inside our outside the company.
For the to-be surfers, most of the opportunity is in training them to leverage the AI being woven into most B2B technologies. The AI future is (right now) being distributed broadly across the enterprise stack. Knowledge workers must learn to surf better than their peers, less they miss the wave.
Resources
Intellectual growth should commence at birth and cease only at death. —Albert Einstein
Below are some of the more useful training resources I’ve found, coupled with visuals of in-demand skills.
Harvard: introduction to AI with Python, 5 tips for changing careers
Coursera: Supervised Machine Learning: Regression and Classification, 8 High-Income Skills
Microsoft AI Learning Hub: Microsoft 365 Copilot
Amazon AI Training: GenAI, foundational models.
DataCamp, e.g. Pytorch, LLMs, ChatGPT prompting
Linkedin: upskilling vs. reskilling, earn professional certificates
BerkeleyX: Empathy and Emotional Intelligence at Work (don’t underestimate the soft skills!)
The Princeton Review: Career Quiz
Google Data Analytics: R, SQL, Tableau
