I do not mean executives need to become engineers. I mean something more practical: they need enough fluency to inspect what is being built, understand the assumptions underneath it, and know when a system is genuinely useful versus merely impressive.
For most of my career, there was a comfortable distance between a business idea and the machinery required to execute it. You could set direction, allocate a budget, hand the problem to a specialist team and wait for the result. That still happens, and sometimes it should.
But the distance is shrinking fast.
The gap between an idea and a working thing is collapsing.
I can now take a rough operating question and turn it into a model, a workflow, a prototype or a working internal tool in a fraction of the time it used to take. That changes more than productivity. It changes what a leader can reasonably understand firsthand.
When the cost of testing an idea falls, there is less excuse for staying abstract. You can see where the data comes from. You can watch the logic fail. You can find the handoff that makes no sense. You can discover that the “simple” part of the plan is actually the brittle part.
That kind of proximity improves judgment.
Technical fluency is becoming business fluency.
The questions I care about are not particularly technical: Where did this number come from? Which part of the process is a rule and which part requires interpretation? What happens when the input is wrong? Who is accountable for the output? Are we automating something valuable, or simply automating a bad process?
Those questions matter in marketing, finance, operations, customer service and product work. AI just makes them harder to avoid.
A leader who cannot inspect the logic underneath a system is still dependent on someone else to tell them whether it is sound. That is not automatically a problem—specialists matter—but it creates a different kind of dependency when software and AI are touching more of the operating model.
Delegation without inspection is getting riskier.
AI can produce an answer that looks finished long before it is trustworthy. The same is true of dashboards, forecasts, automations and software.
This is where I think executive work changes. The advantage is not in doing every task yourself. It is in being able to get close enough to the work to challenge the assumptions, understand the tradeoffs and decide where human judgment still belongs.
That is a different standard than “being good with technology.” It is closer to understanding construction.
Stay close enough to see the machinery.
I do not want a CEO or CMO spending half the day writing code. I do think the best leaders will spend less time treating technology as a black box.
The more useful question is not, “How do we use AI in this department?” It is, “If we designed this work today, knowing what people, software and AI can each do, would we build it the same way?”
That question gets uncomfortable quickly. It reaches into workflow, staffing, ownership, measurement and sometimes the org chart itself.
That is the point.
The future executive does not need to be the most technical person in the room. But I think they will need enough understanding of how things are built to know what is possible, what is fragile and what should never have been built that way in the first place.