Do You Have General Intelligence—Or Are You Just Running a Predictive Model?

The AI Question, Flipped

Herbie Hancock once shared a story about a lesson he learned from Miles Davis. Early in his career, Hancock played a phrase during a performance that felt completely wrong—so wrong that he expected Miles to stop the music. Instead, Davis took what Hancock played and responded with something that made it work.

Later, Hancock asked him about it, and Davis explained that there’s no such thing as a “wrong” note. The mistake wasn’t the problem—the problem was Hancock’s assumption that it was a mistake.

One of the ways Davis trained his musicians to think differently was by having them play a piece of music backward. The point wasn’t just to challenge them. It was to force them to stop relying on their automatic responses and hear the music in a completely different way.

Leaders often don’t realize when they are operating inside their own version of this problem, assuming they are thinking when they are really just following a piece of sheet music they have played a hundred times before.

People often ask whether AI can truly think or if it is just predicting the next most likely word. A better question is whether leaders are truly thinking.

Most leadership decision-making isn’t first-principles reasoning. It is pattern recognition. Experience, expertise, and industry norms create a kind of cognitive autopilot. This is useful for efficiency but dangerous for innovation.

In a world of rapid change, leaders who rely on what worked before risk becoming obsolete, just like an outdated AI model that cannot adapt.

Are You Thinking, or Just Predicting?

Leaders like to believe they have general intelligence. Intelligence, however, isn’t about having the right answer. It is about knowing when to question the obvious one.

AI models predict the next word based on probability. Humans do something similar with decisions, predicting outcomes based on past experience, organizational norms, and industry expectations. These patterns create blind spots, just like an AI model trained on outdated data.

A few ways this plays out in leadership:

• The Safe Play Bias: Relying on best practices that worked before, even when the landscape has shifted.

• The Expertise Trap: Mistaking deep knowledge for adaptability, assuming the right answer is buried in past experience.

• The Comfort of Logic: Choosing rational, incremental solutions over unexpected, disruptive ones.

  
  

These are not failures of intelligence. They are failures of awareness. Leaders who thrive in the AI era will be those who recognize when they are running on past assumptions and deliberately disrupt their own thinking.

Breaking the Pattern: How to Think Beyond the Predictable

If you want to be more than a predictive model, challenge your own algorithm.

Here are three ways to do it:

1. Flip Your Default Assumptions

Every leader has ingrained beliefs about their business, market, and customers. Some of those beliefs may be wrong.

Try this:

• Identify a core strategic belief in your business.

• Defend it like a debate team. Now argue the opposite side. Which one was harder?

• Ask: What if the opposite were true?

Netflix assumed streaming would never replace DVDs, until Reed Hastings questioned it. What’s your equivalent blind spot?

2. Interrupt Your Decision-Making Pattern

The brain defaults to familiar problem-solving approaches. To disrupt this, try:

• Play it backward. Just like Miles Davis had his band do with music, look at a recent decision and reverse the steps. What would it look like if you worked from the conclusion backward instead of forward?

• Industry Cross-Pollination: How would a leader from a completely different sector solve this? (e.g., What would a gaming CEO do if they ran a law firm?)

• The AI Thought Experiment: If an AI analyzed all available data and had no biases, would it make the same decision you are about to make?

Great leaders don’t just make decisions. They rethink how they arrive at decisions.

3. Redefine Risk—Creative vs. Predictive Risk

Many leaders see risk as something to be minimized. Predictive risk involves sticking with the status quo and hoping it holds. Creative risk involves pursuing something unproven but high-potential.

Risk Audit:

• Look at the last five major decisions you made. Were any of them truly disruptive?

• If an AI had your same experience, would it have made the same choices?

• If so, what does that say about how much risk you actually take?

Amazon’s biggest “risks” (cloud computing, e-commerce expansion) looked reckless—until they weren’t.

Can You Be More Intelligent Than Your Own Model?

The leaders who succeed in the age of AI won’t be the ones who think like predictive models.

They will be the ones who recognize when they are thinking like a predictive model and break the pattern.

Next time you make a big decision, don’t just ask, “What’s most likely to work?”

Ask, “What’s least expected—but might change everything?”

Final Challenge: Prove You’re Not Just Predicting

Over the next week, document your biggest decisions. How many were actually new?

If you can’t point to one moment where you challenged your instincts, were you really thinking—or just predicting?

If AI can predict your decisions, what exactly makes you different?