Opinions expressed by Entrepreneur contributors are their own.
Key Takeaways
- AI does not replace operational knowledge. It requires leaders to understand their business, customers and workflows in greater depth to produce informed outputs.
- The value of AI in leadership is not automation alone. It is the ability to create visibility across initiatives and coordinate work at scale.
- AI shifts leadership from sequential task management to directing systems and outcomes, allowing organizations to move faster without sacrificing oversight.
Inside our company, I have built what I think of as an AI executive copilot. It is integrated into how I manage the business every day, not something I check in on separately or run alongside my normal work. It is part of my normal work.
It connects to our CRM data, internal documentation and operational workflows. It monitors initiatives across divisions, tracks KPIs, flags risks and surfaces opportunities I might otherwise miss. When I need to push seven sales initiatives forward simultaneously, I prompt it to draft the relevant communications for the right people and move them to review. When I need visibility into treasury, finance and operations at the same time, I have it. I am not stopping to sequence through conversations one at a time. I am directing multiple things simultaneously in a way that was not possible before.
What surprised me is not what the system can do. It is what it demands from me as a leader.
The constraint is never the technology
There is a persistent misconception that deploying AI at an operational level is a technical challenge. It is not. The constraint is how well you understand your own business. If you do not understand your product, you cannot prompt correctly. If you do not understand your customer, you cannot prompt correctly. If you do not understand your workflows, you cannot prompt correctly. And if you cannot prompt correctly, the system cannot help you.
This is why I believe a strong operator with deep business knowledge is more valuable in this environment than a technical expert. You have to be able to educate the system on what your organization does, how it does it and who it serves. Then you have to be able to prompt toward where you want to go, without telling the system how to get there. That second part is harder than it sounds. Most leaders are trained to prescribe solutions. Here, you have to educate the system by feeding it information and prompting it, and then you have get out of the way.
What used to be programming is now prompting. What used to be execution is now direction. That shift applies to every leadership role in the organization, including mine.
What this actually required me to know
To make this work, I had to get much closer to how the business actually operates. Not how I assumed it operates. How it actually operates. That means understanding the full lifecycle from intake through underwriting, case management, risk management and account resolution. It means knowing which KPIs matter and why, which ones I might be missing and what drives enterprise value beyond internal performance.
It also means understanding the people who use our platform. A paralegal. An attorney. A healthcare provider. A revenue cycle manager. Where are the friction points in their experience? Where are we adding work instead of removing it? What does our sales cycle actually look like at each stage, and where is activity breaking down relative to close rates?
AI does not solve those questions for you. It amplifies how clearly you have already answered them. When your understanding is shallow, you scale mistakes. When it is deep, the system can analyze across more variables than any individual could and surface opportunities you would not have identified on your own. It may find a coding issue, a sales activity gap, an onboarding friction point or a margin opportunity. Depth of input determines depth of insight.
How I actually use it day to day
I still have seven direct reports. I still hold a standing Zoom with my leadership team every morning. What has changed is everything that happens around those touchpoints. I go into the system and prompt initiatives for each leader. I track where things are stalling. I surface anomalies in performance data before they show up in a meeting. I move from managing tasks to directing outcomes, and the system handles the coordination work in between.
The result is that I can advance multiple priorities simultaneously in a way that was not possible when every piece required me to move sequentially. I used to have to stop, connect with one division leader, suggest changes, move to the next one, suggest changes there and then try to get the two of them talking to each other. Now I can send it all out at once. That is not a minor efficiency gain. It fundamentally changes how fast the business can move.
To be precise about what this is: I am prompting the system and it is producing what I ask for. It is not acting independently. But it is allowing me to initiate, track and drive more than I could manage on my own.
The visibility it creates is the real advantage
Every organization has blind spots. Initiatives that go stagnant. Decisions that get delayed because no one has the full picture. Opportunities that never surface because attention is fragmented.
A system like this does not have those constraints. It tracks how long things actually take, not how long we think they take. It surfaces patterns that would otherwise take weeks of analysis to see. It gives me a level of continuous visibility across the business that is genuinely difficult to maintain manually, and that visibility changes how I lead.
My prediction is that this will not stay optional for long. Boards will build these systems. Investors will use them to evaluate performance. External stakeholders will have their own view into what is actually happening inside companies. Leaders who have already built this capability internally will be ahead of that curve. Those who have not will find themselves explaining gaps they did not know existed.
The real constraint is judgment
The question is no longer whether something can be built. It is whether it should be built, how it should work and what it should be directed toward. Those are leadership questions, not technical ones.
The leaders who thrive in this environment will not be the ones who understand the tools best. They will be the ones who understand their business, their customers and their operations clearly enough to direct those tools toward outcomes that matter. That clarity is the competitive advantage.
Key Takeaways
- AI does not replace operational knowledge. It requires leaders to understand their business, customers and workflows in greater depth to produce informed outputs.
- The value of AI in leadership is not automation alone. It is the ability to create visibility across initiatives and coordinate work at scale.
- AI shifts leadership from sequential task management to directing systems and outcomes, allowing organizations to move faster without sacrificing oversight.
Inside our company, I have built what I think of as an AI executive copilot. It is integrated into how I manage the business every day, not something I check in on separately or run alongside my normal work. It is part of my normal work.
It connects to our CRM data, internal documentation and operational workflows. It monitors initiatives across divisions, tracks KPIs, flags risks and surfaces opportunities I might otherwise miss. When I need to push seven sales initiatives forward simultaneously, I prompt it to draft the relevant communications for the right people and move them to review. When I need visibility into treasury, finance and operations at the same time, I have it. I am not stopping to sequence through conversations one at a time. I am directing multiple things simultaneously in a way that was not possible before.
What surprised me is not what the system can do. It is what it demands from me as a leader.