I Planned Military Ops. AI Just Made It My Most Valuable Skill | Opinion

I didn’t realize the most valuable thing the Marines gave me until I watched artificial intelligence struggle with a problem everyone assumed it should solve easily.

I was working on an enterprise AI project when a talented developer asked the system to consolidate dozens of software functions into a single platform. The AI worked quickly, but the results drifted from reality. Records landed in the wrong places. Business rules no longer matched operations. After several attempts, the conclusion seemed obvious: the technology wasn’t ready.

Watching it unfold, I asked a different question: Had we actually thought the problem through before asking AI to solve it?

That moment changed how I viewed artificial intelligence, and my own career. I realized the thinking process the Marines drilled into me over seven years as an infantry officer (what I now describe as constraint-first thinking) had become one of the scarcest skills in the AI economy.

We were trained to define the mission, understand the constraints, challenge our assumptions, and only then begin execution. AI rewards that same discipline.

AI Rewards Contingency Planning

When people talk about military service, they often focus on leadership, discipline, or resilience. Those lessons mattered. The lesson that has proven unexpectedly valuable, though, was learning how to think through uncertainty before taking the first step.

Much of my time in the Marines involved planning complex amphibious operations. Every mission required coordinating people, equipment, logistics, communications, and timing while assuming conditions would change once execution began. We expected friction, so we spent more time testing assumptions than admiring them. Every contingency had to be explored before anyone moved.

That discipline became instinct.

Years later, in enterprise technology consulting, I discovered AI rewards the same habit of mind. Enterprise systems contain countless business rules, security requirements, and interconnected platforms. AI can generate enormous amounts of work quickly, but success depends on something less glamorous than speed: defining boundaries before execution begins.

The project that first opened my eyes proved exactly that.

Instead of abandoning AI, I stepped back and studied the destination. I mapped the platform’s business rules, documented its data model, and identified the constraints the system needed to respect. Only after those guardrails existed did I ask AI to build.

The difference was immediate. The technology stopped improvising because it understood the environment where it was expected to operate.

That experience reshaped my thinking.

Quality of Thinking Affects the Input (and Output)

Many conversations about AI focus on more powerful models and faster tools. My experience keeps leading me somewhere simpler: AI executes the instructions we give it. The quality of those instructions depends on human judgment, experience, and the ability to think through a problem before searching for a solution.

I see that lesson every day. I build AI systems for my own businesses and help enterprise organizations redesign complex technology environments. The projects vary, but the pattern remains the same: the bottleneck isn’t the software. It’s the quality of the thinking that comes first.

Every successful project begins with questions I learned years ago in the Marines. What are we trying to accomplish? Where could this fail? Which assumptions deserve another look? Which decisions should remain in human hands?

Those questions existed long before artificial intelligence. AI simply made them more valuable.

The longer I worked with AI, the more I realized this lesson reached beyond my career.

Veterans often ask whether they need to become software engineers to stay relevant. Students ask which AI certification will matter most in five years. I understand the uncertainty because the technology changes constantly.

Compounded Expertise

My advice is to use AI enough to remove the intimidation factor. Build something small. Ask questions. Experiment. Once you see AI solve a real problem, fear gives way to curiosity. Then invest your time becoming deeply knowledgeable in a field you care about. AI tools will evolve. Expertise compounds.

Every profession contains knowledge that never fully makes it into a manual. Firefighters understand how emergencies unfold. Nurses recognize subtle changes in patients. Construction supervisors spot problems drawings never reveal. Those instincts come from experience, and they become the constraints that allow AI to produce meaningful work.

Constraint-first thinking isn’t limited to the military. It grows wherever people spend years mastering a craft, learning where things fail, and understanding the boundaries that separate a good outcome from a costly mistake.

That’s why I believe the next generation of AI builders will come from every profession, not just technology. Their advantage won’t come from learning a programming language first. It will come from knowing their domain so well that they can teach intelligent systems how excellent work is performed.

AI Will Enter the Physical World

The biggest opportunity is still ahead. Today’s AI is transforming digital work, but tomorrow’s breakthroughs will increasingly reach into the physical world through robotics and humanoid systems. Those technologies will need people who understand construction sites, hospitals, factories, farms, warehouses, and emergency response through lived experience. Their expertise will become the operating principles that make those systems useful.

That realization changed how I think about military service. Veterans already possess years of training in uncertainty, questioning assumptions, planning contingencies, and making decisions before execution begins. The technical skills needed to work with AI can be learned. The habit of thinking this way often takes much longer to develop.

The same applies to leaders. As organizations race to adopt AI, the most valuable people may not be those who know the newest tools. They may be those who think through problems, define boundaries, and anticipate failure before building begins. They give AI its direction.

People sometimes ask whether AI threatens careers like mine. I see something different. Technology keeps accelerating, while thoughtful planning becomes more important. AI has increased the value of the mindset I developed in the Marines because execution is no longer the slowest part of the process. Thinking is.

I joined the Marines expecting to learn how to lead people. Years later, I discovered the lesson I carried with me had little to do with rank. It was a way of approaching difficult problems with patience, discipline, and the understanding that success begins long before execution.

I didn’t expect that lesson to become my greatest advantage in the age of artificial intelligence.

It just quietly did.

Jon Licht is a salesforce solution architect, enterprise AI transformation strategist, and former Marine Corps infantry officer. He helps organizations modernize complex technology environments through AI, governance, and secure platform architecture while building AI systems for businesses of every size.

The views expressed in this article are the writer’s own.