Trained to Be Replaced: The Hidden Cost of Building AI at Work

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The AI Champion Paradox: Are You Automating Yourself Out of a Job?

AI is supposed to make us more efficient.

It’s supposed to remove repetitive work, unlock productivity, and help organizations move faster.

But there’s a question most people aren’t asking:

What happens when the AI you helped build… replaces you?

Across industries, people are actively training systems, improving workflows, and driving AI adoption inside their organizations.

And in many cases, those same efforts are quietly reducing the need for the very roles that made them possible.

Not just entry-level positions.Not just repetitive tasks.

We’re talking about:

• Knowledge workers

• Managers

• Decision-makers

  
  

No level is untouched.

In this episode of Three Takes on AI, we dig into what we’re calling the AI Champion Paradox—a tension that sits at the center of almost every AI initiative today:

The better you are at implementing AI, the more likely you are to eliminate work—including your own.

This isn’t a fear-based conversation.

It’s a real one.

We talk through:

• Why some jobs aren’t evolving—they’re disappearing

• Why this wave of disruption feels different from anything before it

• What history gets right (and wrong) about “adapting to change”

• Where AI still falls short in ways that actually matter

• And what leaders should be thinking about before pushing AI further into their organizations

  
  

There’s no clean answer here.

Just a reality that’s becoming harder to ignore:

AI isn’t just changing how we work.It’s changing who gets to work.

🎧 Listen or watch the full episode to hear the conversation—and decide for yourself where you stand.