If you listen to enough AI conversations these days, you might start to believe that the future of business decision-making will be entirely automated.

• Algorithms analyze the data.
• The system generates insights.
• Leaders simply approve the recommendation.

But something interesting is starting to happen in companies that are deeply integrating AI into their decision-making processes.

The more data they analyze, the more they are rediscovering something important.

Data does not replace judgment.

In fact, the explosion of data and AI-driven insights may actually make human judgment more important than ever.

In our work designing business acumen simulations for leaders around the world, we constantly emphasize that data is only one part of the decision-making process.

The real skill of leadership is knowing how to interpret the data and when to challenge it.

Here are five reasons why human judgment still plays a critical role in the age of AI.

If you listen to the business headlines these days, you might conclude that artificial intelligence should be used for everything.

How many times a week are you in a virtual meeting where you can literally see in the reflection of someone’s eyeglasses that they are doing something else?

Not “kind of distracted.” Not “quickly checking something.”

Completely somewhere else.

It happened to me this week with a vendor we are considering working with, and it was so rude and off-putting that it immediately changed my perception of them. It is one thing to fake attentiveness with the occasional nod and a half-hearted, “Yeah, good point.” It is another thing entirely to be visibly engaged in something else; smirking, smiling, reacting, even laughing at whatever is on your screen while someone else is speaking. Seriously, dude?

That is not multitasking. That is messaging.

And the message is loud and clear.

In a business world obsessed with efficiency and productivity, many professionals convince themselves that multitasking is harmless, even necessary. But the reality is, every time you divide your attention in a meeting, you are sending a series of powerful subliminal signals.

The question is: what exactly are you signaling?

Here are five answers.

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As artificial intelligence transforms sales analytics, sales leaders must learn new coaching strategies to help their teams interpret AI insights, challenge assumptions, and turn data into action.

If you haven’t heard the news yet, AI has changed everything.

Historians may eventually look back on this moment as one of the great pivot points in human productivity.

From a business perspective, I see it as a major pivot point in business acumen.

For decades, leaders have been trying to get their sales teams to become more data-driven—using customer insights, prescription trends, territory analytics, and performance dashboards to make smarter decisions.

Now something new has entered the equation.

AI.

In a world driven by data, data analytics, and now artificial intelligence layered on top of it, entirely new challenges are emerging for sales leaders and the way they coach their teams.

Whether companies have formal policies about AI or not, their sales teams are already using it.

Last week, I was immersed in a fascinating project focused on building sales leaders' business acumen in the pharmaceutical industry.

A major part of the program focuses on how sales leaders coach their teams using sales data, helping them interpret prescribing patterns, identify opportunities, and take the best actions to grow new prescriptions and revenue.