As faculty director for MBA programs at the Daniels College of Business, a full teaching professor and an Executive PhD student, Michael Myers brings nearly two decades of digital marketing experience to the rapidly evolving intersection of AI, business and education. His research focuses on how generative AI can responsibly improve personalization, performance and customer value.
AI isn’t killing the MBA. It’s making MBAs indispensable.
Over the past two years, I have had weekly conversations about the value of an MBA. AI can now write detailed marketing plans, build financial models and draft strategic workforce plans in a matter of minutes. Given where we are collectively, examining the value of an MBA is a fair exercise. Most of these conversations eventually return to one or more of the questions below, so I thought I would share my perspective on how we view the changes currently taking place.
The Skill That Keeps a Role Safe
Why should I get an MBA now?
A metaphor for the traditional career is a musician. You picked an instrument, whether that’s accounting, finance or supply chain, and you spent years getting very good at it. Organizations were built around sections of these specialists, each playing their part.
Currently, AI is coming for the musicians. Not because the instruments stopped mattering, but because AI can now play many of them as competently and cheaply. What AI can’t do is decide what the orchestra should play, hear when the strings are drowning out the brass, or know that the piece needs to change because the audience has changed.
That is the orchestrator’s job, and it is precisely what an MBA trains you to do. The entire program is an exercise in seeing across functions: how a pricing decision ripples into cash flow, how an operations choice constrains marketing, how a hiring plan shapes strategy. Most MBAs still choose a concentration, and they should. But the degree’s real product has always been the generalist’s view, and that view just became the most valuable seat in the house.
Why is this more important now? Because businesspeople are being asked to manage multiple agents. And the news of agents’ pure autonomy, in many ways, has been overstated. As of today, businesses still need people who understand the business holistically, and that is exactly what an MBA is.
Why “The AI Class” Isn’t the Point
Where is your AI class?
I get this question at every information session, and I understand why the question is asked. But it reflects a misunderstanding of what AI is. AI technology is fluid and can’t be summed up in a single elective, any more than a business school in 1998 should have offered one class called “The Internet.”
AI is three things at once: a technology, a methodology and, most importantly, a leadership enabler. It touches accounting, finance, marketing, analytics and management, which is to say, it touches everything. In our program, AI shows up in roughly two-thirds of our courses, embedded in the work itself rather than bolted on as a topic. Students don’t just learn about AI. They negotiate with it, analyze with it, build with it and lead through it.
And in a handful of courses, they are not allowed to touch it at all. Which brings me to the next question.
Why can’t I use AI in every class?
Because judgment requires knowledge, and there is no shortcut to knowledge.
Here’s my confession: if I ask an AI to explain nuclear fusion, I get a thorough, confident, well-organized answer. I also have absolutely no idea whether it’s correct, because I don’t know enough about nuclear fusion to check. I am at the mercy of the output.
That’s a terrible position for a leader. When our students eventually prompt AI for a discounted cash flow analysis or a segmentation strategy, they need enough mastery to look at the output and know whether it’s brilliant or confidently wrong. AI is a phenomenal amplifier of expertise and a dangerous substitute for it. The classes where we don’t allow AI are not nostalgia. They are where we build the foundation that makes every AI-assisted class afterward actually useful.
What Kind of Work Is AI Actually Replacing?
Will there be any jobs?
Yes. But the sorting principle has changed, and it’s worth being precise about it.
Work that is fundamentally about efficiency, meaning doing a defined task faster and cheaper, is exactly what agentic AI is built to absorb. If a job’s core value is throughput, that job is exposed. Work that is fundamentally about effectiveness, deciding what should be done, for whom and why, is where humans will flourish.
The New Job Description: Managing Teams of AI Agents
Again, the MBA graduate’s job of the near future looks like this: designing and managing teams of AI agents, then collaborating with those agents to make better decisions than either could make alone. That’s management. It has always been management. The direct reports have simply changed.
How to Future-Proof Your Career, Starting Now
The nature of work is shifting under our feet, and I won’t pretend business schools have every answer. But the question was never whether AI would change the value of an MBA. It’s whether you can find a role playing one instrument, or lean in and learn to conduct.
Frequently Asked Questions
Which jobs will AI replace?
AI is most likely to replace work centered on efficiency: defined, repeatable tasks whose primary value is being completed faster and more cheaply. AI job displacement will therefore affect roles built mainly around throughput, although AI may replace portions of many jobs rather than eliminating every role outright.
What jobs can’t AI replace?
The jobs safest from AI are those that depend on judgment, context and effectiveness: deciding what should be done, for whom and why. Roles that require leaders to evaluate AI output, connect decisions across business functions and adjust when conditions change will continue to rely heavily on human expertise.
How do I future-proof my career?
To future-proof your career, build enough subject-matter knowledge to recognize when AI is useful and when its output is confidently wrong. Pair that expertise with a broad understanding of business so you can make cross-functional decisions and become effective at designing and managing AI agents.