AI and Your Transition: What Actually Changes

This is one of the most common questions we get now, in one form or another. Does AI make the MBA pointless? Is it too late to go into tech? Will the job I am training for still exist in five years?

Here is our honest read, pulled from three years of answering this question live.

Where We Actually Are

We are early. Not "nothing is happening" early, but "the shape of it is not settled yet" early.

The comparison we keep coming back to is the iPhone. We are somewhere around 2008. The device exists, everyone can see it matters, and almost nobody has correctly guessed which businesses it is about to create or destroy. There is enormous corporate investment going into practical applications, which is what makes this different from the crypto cycle, where the investment was mostly hype with very little shipped.

Five to ten years from now the applications of AI will be embedded in daily work the same way the internet and smartphones became embedded. Cars are already driving themselves. Phones are running models on the device. That is coming whether or not you have an opinion about it.

So the useful question is not "will AI change my industry." It will. The useful question is what it changes about the decision in front of you right now.

What AI Does, and What It Does Not

Be specific about this, because the vague version of the question produces vague answers.

AI is genuinely good at data processing, pattern recognition, and routine analysis. If your plan was to be valuable primarily because you can build a model, format a deck, or summarize a document faster than the next person, that plan is weakening.

What AI does not do, and what defense tech, startups, and executive leadership all absolutely require:

• Navigate ambiguity
• Manage human dynamics
• Make judgment calls on incomplete information
• Build trust with stakeholders

Read that list again, because it is a fairly precise description of what you did in the military. That combination of military experience and business training is not the thing being automated. It is the thing that becomes scarce when the analytical work gets cheap.

It will also create work that does not exist yet. One example already appearing: people who can audit an AI model and explain how it arrived at a decision. That is going to matter enormously to regulators, to customers, and to anyone deploying these systems commercially. AI will displace jobs and create jobs, the way every significant technology has.

Does It Change the Math on an MBA?

AI is changing the MBA's value. It is not killing it.

Understand what you are actually buying with a top MBA. It is not a credential in the way a law degree or a medical degree is a credential. You are buying an education, yes, but more importantly you are buying access to a network and a recruiting pipeline, and you are buying a signal.

Now think about what happens to that signal in a world where access to knowledge is commoditized. If anyone can get the knowledge, the filter becomes more valuable, not less. That is the argument for the degree getting stronger rather than weaker.

What has genuinely shifted is that data fluency is now table stakes. You need to understand how these systems work, where their limits are, and how to actually use them for a real decision. That is additive to an MBA, not a substitute for one. And it is worth saying plainly: understanding how to lead an AI implementation, manage the organizational change around it, and make sure it is deployed responsibly (which matters more in defense than almost anywhere) is a leadership skill. It is not a data science skill. You do not need to become an engineer to be the person who makes this work.

There is a caution here too. AI is not a reason to talk yourself out of a decision you were otherwise going to make. Veterans already have a habit of self-selecting out of top programs over cost. Do not add "but AI" to the list of reasons not to go. Run the actual numbers: probable salary increase from the program against the monthly loan payment. For most people that comes out clearly in favor.

If You Are Going Into a Technical Role

The expectation has moved. Going in, assume you need to learn to build using AI agents, and that doing so is what lets one person do the work that used to take a team.

Practically, that means:

• Do projects end to end rather than in pieces
• Build complete, working applications, not tutorials
• Show a product manager's instinct for what is worth building, not just the ability to build it
• Specialize. Cybersecurity, cloud architecture, and AI/ML infrastructure are where the demand is concentrated

A course or a certificate is a starting line here, not a finish line. Use it to build something real, then let the work speak.

If You Are Not Technical

You have more angles than you think, and this is the most common thing veterans get wrong about tech.

The path in is usually customer-facing. Engagement, sales, account management, customer success, business operations. What those roles need is someone who genuinely understands the problem and the customer, and who has a decent working understanding of how the product actually functions. You do not need to write the code.

We see far more technical people move into customer-facing and strategy roles than the reverse, which tells you those roles are not a lesser tier. They are a different skill.

And there is a whole category of companies right now, from robotics to manufacturing to reindustrialization generally, that badly need people who can sell and manage accounts and run operations while genuinely understanding a technical product. AI is a big part of why those companies are suddenly able to build what they are building.

What It Looks Like Industry by Industry

Defense tech. AI is unlocking real capability, not just marketing. The clearest example is space imagery. There was always a tension between selling data, which is easy and scalable for the business, and selling insight, which is what the customer actually wants but which nobody could deliver at scale. AI collapses that tension. Companies can now sell the insight. Expect more of this pattern: places where the analysis was the bottleneck and now is not.

Consulting. AI will be embedded in every tool you touch and will make the work faster. It does not remove the reason clients hire consultants, which was never primarily the analysis.

Law. AI will change the industry, and we are optimists about it, in the sense that it will let lawyers do more rather than replace them. The separate and more important point about law school is unchanged: if the goal is big law money, it is hard to justify unless you are going to a T14 school, or you are confident of finishing near the top of the class at a strong regional one.

Licensed and regulated roles. Worth being clear-eyed. In a lot of these jobs the technology could already do most of the task, and the reason it does not is regulation rather than capability. That is real protection, but it is protection that depends on rules holding, which is a different thing from the work being irreplaceable.

Hardware and semis. AI demand and hardware demand need each other. Remember that the hardware industry is cyclical. Companies buy heavily, then digest, then buy again. A slow quarter is not the end of the story.

The Bottom Line

Business is not new to this. In the whole history of it, the people who were good at business have always found ways to use new tools to create value. AI is the next big productivity tool, and it will let entrepreneurs build business models nobody has thought of yet. Being the person who can figure out and run those models is a good place to stand.

None of this changes the fundamentals of a good transition. Understand the market you are entering. Be honest about what you are actually good at. Build something real rather than collecting credentials. Get access to the networks that open doors.

AI raises the value of judgment and lowers the value of routine analysis. If you were counting on the routine analysis, change the plan. If you were planning to lead, you are in a better position than you were.