The technology is usually easy… leadership is the hard part.

Many years ago, I used to tell audiences that “technology has removed technology from technology.” It was my way of saying that we no longer needed instruction manuals or engineering degrees to get real value from technology. We just had to jump in, experiment and figure out where the value lived. Artificial intelligence presents technical challenges. Learning how to prompt well… learning how to evaluate the output… learning where it excels and where it still falls apart. Those are all real… but they’re also solvable. The much harder challenge isn’t technical… it’s organizational.

When it comes to artificial intelligence, I don’t think organizations are struggling because the technology is confusing.

They seem to be struggling because AI demands a different kind of leadership than most organizations have spent decades rewarding. And that’s what I’ve been thinking about since I recorded this week’s episode of Thinking With Mitch Joel that featured my old friend and one of the sharpest strategic thinkers I know, Charlene Li (you may remember her from the groundbreaking book, Groundswell and you should check out her new book, Winning With AI).

That “new leadership thinking” is a much harder problem to solve.

And it starts at the top. Most leaders built their careers by demonstrating certainty (because that’s what people and teams are looking for). Gather data… analyze options… reduce risk… build the business case… make the decision. It was a pragmatic model for a relatively stable world. It feels like AI in the workplace refuses to cooperate with that model. The technology changes (almost weekly) and the capabilities shift by orders of magnitude (almost constantly). These are not the times of “best practices” when a lot of the “wins” become almost obsolete in the short-term. Leaders like waiting until they have enough answers. In this era, waiting may be the only truly wrong answer. Charlene, in a roundabout way, is saying that leaders today have to become comfortable making important decisions before that certainty arrives.

That’s not an AI skill… that’s a leadership skill.

Now I just can’t figure out if the issue is that leadership is following other tech transformation cycles (roll it out… run a pilot… train the eager team members… measure some pre-defined ROI metrics… expand if it works) or if this is something “other” that’s forcing us to rethink how decisions get made, how work flows across the organization and, perhaps most importantly, what the organization could (potentially) become. It feels like we’re somewhere in between “this can automate a workflow” and “we don’t need any of these workflows anymore”… and, yes, that’s a chasm of unknowing as the tech continues to shift and morph.

Those are two completely different conversations.

Charlene also argues that too many of these AI pilots are just organizational theatre… a way to postpone commitment without admitting that’s what’s going on. And, if that is what’s happening, the leadership challenge extends far beyond AI. It starts looking like we’re studying the future instead of participating in it. So, the opportunity is not in trying to predict what’s coming… or even the ability to understand every new model that gets released. But the willingness to create direction before perfect clarity exists.

My bet? The organizations that succeed probably won’t be the ones with the best models.

They’ll be the ones with leaders who understand that transformation has never been about having all of the answers. It’s about creating the conditions for better answers to emerge. Give smart people powerful new tools… encourage experimentation… reward learning over certainty… and let the organization discover what works.

Because that’s what leadership increasingly looks like… not certainty… direction.

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