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Key Takeaways
- Everyone wants to use AI to move faster. But speed alone doesn’t create results. What really matters is clarity.
- When AI starts making decisions faster than people can keep up, it’s not the technology that causes problems. It’s the lack of clear leadership systems to keep people aligned.
Not too long ago, I worked with a leadership team that had just launched a new AI dashboard. It was truly state-of-the-art and was designed to shorten meetings and speed up decisions. Instead, it caused massive amounts of confusion.
One reason for that was that different departments analyzed the same data through their own lenses. The result was that meetings actually became longer, instead of shorter, and no one could say who made the “final call.”
The truth of the matter was that their real problem wasn’t AI at all. It was the total absence of clarity.
This isn’t rare, by the way, because every day, more companies face the same problem where leaders think faster tools will produce faster results.
The truth is different.
AI systems don’t fix leadership issues. They reveal them. Without clear ownership, priorities and accountability in the first place, AI simply exposes what’s missing.
AI can’t solve problems that come from weak leadership structures, but it can — and does — shine a light on them.
The speed trap
Many leaders fall into what I call the “speed trap.”
By this, I mean that they believe the faster their team moves, the better they perform. Sadly, speed without clarity creates mistakes.
Imagine a team using AI to automate reports and analyze data. On the surface, it sounds like progress; however, within weeks, the team has more dashboards, more alerts and more confusion.
In these situations, three things usually happen.
When you chase speed without a defined structure, you don’t move forward — you just move faster in circles.
What’s the real cost of confusion?
Confusion doesn’t just waste time; it also erodes trust.
I worked with a regional team that used AI tools to forecast results across several countries. The data itself was accurate, but every region interpreted it differently. Unsurprisingly, instead of one plan, they ended up with three competing ones.
The real issue wasn’t technology, but leadership. No one (in leadership) had defined who made the final call.
When your team doesn’t know who decides, execution breaks down, and AI can’t fix that. It can only speed up the breakdown that already exists.
What AI is really testing
Sometimes it’s easy to think that AI is testing how smart your team is. It isn’t. What it’s testing is how organized your leadership is.
I’ve discovered that AI does a great job at:
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Highlighting whether your systems are strong enough to handle faster decisions
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Exposing gaps in communication
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Exposing gaps in ownership
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Exposing gaps in accountability
If those systems are missing, then AI becomes a stress test. People will hesitate, projects stall, and decisions pile up.
And it’s not about technical capabilities either. Leaders who succeed with AI aren’t actually the most technical. They’re the ones who stay clear about who decides what and, more importantly, why.
The new job of a leader
AI fundamentally changes what leadership means.
The good news is that you don’t need to be an expert in machine learning or Large Language Models (LLM), but you do need to help your team stay clear about purpose and direction.
In a nutshell, your job is to translate speed into focus, and here’s how to start — by asking the following three simple questions:
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Who owns this decision?
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What information actually matters?
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Where does human judgment begin and end?
These questions sound simple, but they keep teams grounded when everything else is moving fast.
To be a strong leader, you need to intentionally slow down to define ownership before you speed up execution. You shouldn’t let AI run the show; instead, you should use it to support a system that already works.
How to catch up
Feel like your team is falling behind? If you do, you probably don’t need more AI tools. You need more clarity, and here are three steps for how to get it.
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Start by mapping your key decisions: To do this, write down who owns them and who gives input. As you do this, you’ll often find overlaps or missing names. Cleaning that up will save you hours every week.
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Next, make decision rights explicit: Who approves, who acts and who reviews? People move faster when they know exactly where they fit.
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Finally, make priorities visible: AI gives data, but clarity gives meaning. Everyone should know what matters most and, more importantly, why it matters.
When people see the same priorities in the same order, execution becomes easier.
What winning looks like
Winning with AI isn’t about replacing people but about equipping them to make better decisions, faster.
When your team knows who owns decisions and why they matter, a number of things will happen.
I’ve seen teams improve project delivery by simply creating a shared decision map. Once they knew who decided what, the arguments immediately stopped, and progress accelerated.
Nothing about their AI changed. Their clarity did.
That’s the difference between moving fast and moving forward.
AI will keep getting faster, but clarity will always decide who stays in control.
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When you define how decisions happen, your team can follow.
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When you teach people what matters, your team can scale.
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When you lead with clarity, AI becomes your ally instead of your obstacle.
Key Takeaways
- Everyone wants to use AI to move faster. But speed alone doesn’t create results. What really matters is clarity.
- When AI starts making decisions faster than people can keep up, it’s not the technology that causes problems. It’s the lack of clear leadership systems to keep people aligned.
Not too long ago, I worked with a leadership team that had just launched a new AI dashboard. It was truly state-of-the-art and was designed to shorten meetings and speed up decisions. Instead, it caused massive amounts of confusion.
One reason for that was that different departments analyzed the same data through their own lenses. The result was that meetings actually became longer, instead of shorter, and no one could say who made the “final call.”
