We are reading a lot about how AI will take our jobs, replace us, and maybe even end us. The fear is loud. It is also not new.
This year I had the privilege of speaking with young leaders at the University of New Hampshire in March and at George Mason University this week. Their excitement about the future is palpable. So are their questions. What does AI mean for my career? Will the job I am training for still exist when I graduate?
Those are fair questions. History has a good answer.
We have been here before
Every major technology arrived with a wave of fear. Each time, the fear was about what we would lose. Each time, what we gained was bigger.
In October 1889, Western Union lineman John Feeks was electrocuted in the tangle of wires above lower Manhattan while a crowd watched. New York fell into an “electric wire panic,” and magazines drew electricity as a demon trapping its victims.
In 1955, Congress held hearings on automation and what it would do to jobs. In 1964, a group of prominent scientists and economists warned President Johnson that automated machines would bring permanent mass unemployment.
In 1995, Jeremy Rifkin’s book The End of Work predicted the decline of the global labor force. Whole industries were going to disappear, and our jobs with them.
In 1889, New York feared electricity itself. Today, a dark alley is what makes us nervous, and a streetlight is what makes us feel safe. The technology didn’t change. Our perspective did.
Over each period, the disaster did not happen. And notice the time horizons: 50 years, then 40, then 30. Each wave brought faster growth, more wealth, and more people at work.
That does not mean we get a pass. Every wave demanded new skills, and people had to learn how to use the new technology. This one will too. But the lesson of history is that people and technology are better together.
The machines got better. So did we.
Most people remember May 11, 1997, when world chess champion Garry Kasparov lost to IBM’s Deep Blue. It was a shock.
The next shock came 20 years later. In May 2017, Ke Jie, the world’s top-ranked Go player, lost all 3 games of his match against AlphaGo, from Google DeepMind.
To put that in context, chess has about 1044 possible board positions. Go has about 10170, far more than the number of atoms in the observable universe.
The machines kept getting better. In 2019 came KataGo, a Go program far stronger than the AlphaGo of 2016.
Then a human won. In early 2023, Kellin Pelrine, an amateur player and a PhD student at McGill University and Mila, beat KataGo in 14 of 15 games. Researchers at FAR AI had used their own AI to play more than a million games against KataGo and found a blind spot. Pelrine learned the strategy and played the games himself, with no computer at his side.
The lesson is not that humans beat AI. It is that a human using AI beat an AI no human could beat alone.
Human + AI: better together
Those who learn to use AI will win in this new world. In the world we now live in, your agentic AI workforce handles the work machines do best, and you deliver the work only people can.
- Works 24/7, never tires
- Scales instantly
- Executes consistently
- Processes information at speed
- Relationship building
- Strategic thinking
- Complex negotiations
- Executive trust
It is the idea behind EQALL®, the agentic AI sales platform. Its 12 Agentic AI sales experts handle the research, preparation, and follow-up behind every meeting, so sellers can spend their time on the relationships, strategy, and trust that only people can build.
What I told the students
Learn the tools, and use them every day. Be curious about what they get wrong, the way Pelrine was. And invest in the skills AI cannot replace: building relationships, thinking strategically, negotiating, and earning trust.
The future does not belong to AI. It belongs to the people who know how to work with it.
Growth figures are approximate, global, and inflation-adjusted, for the periods shown. Chess and Go figures are estimates of the number of legal board positions.