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Mark Cuban Predicts Which Jobs AI Will Erase (And the Skills It Won't Touch)

The billionaire investor's picks for what survives are not obvious.

By Josh Koebert , Edited by Calista Headrick

Updated Sept. 15, 2026

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Mark Cuban made his fortune as a visionary entrepreneur and investor who identified trends ahead of time. He's been very bullish on AI for several years now, and he has some bold predictions for how it would and wouldn't change the future of work. Whether or not he is right about every category, his read is a decent argument to prepare yourself financially before the shift reaches your industry.

Here is what Cuban thinks AI would erase in the job market, and what jobs he says it would not touch.

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Entry-level programming jobs

Software is increasingly writing itself, and Cuban thinks that removes the floor from under junior developers.

"So, jobs like writing software and programming that seem like great jobs, at the lower end, they'll be gone," Cuban said. "We're going to come back full circle where the valuable crafts are going to be teaching, liberal arts, philosophy, math and science. Because once all the machines are doing all the work of calculating, someone's got to interpret. You have to be a thinker. You have to learn how to learn."

One developer with good tooling now covers ground that used to take a team. What survives is the part of the job that involves deciding what to build in the first place and judging whether the output is any good. Writing the code was never the valuable part. It just used to be the expensive part.

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Repetitive office and spreadsheet work

Any rote office work is also on the chopping block. The days of staring at Excel spreadsheets seem to be ending. This extends to any office task that is repetitive and time-consuming.

"Every company has stuff that doesn't get done because it would require someone to sit with a spreadsheet for hours. Or to count things. Or to edit. Or to check receipts for accuracy," Cuban said. "These things can be done with agents and save small companies cash and improve productivity and competitiveness."

Again, the productivity gains from full or near automation might make many of those spreadsheet jobs vanish as companies downsize. While the mark of growth for many pre-AI-era companies was adding headcount, the mark of growth for many now would be generating as much revenue per employee as possible.

Healthcare administrators

Cuban believes that administrative roles could see massive reductions, particularly in the medical field.

"AI will replace most doctors' tasks," he wrote on X (formerly Twitter). "Because most of their tasks are bullshit administrivia introduced by the huge HC conglomerates that serve no purpose. Asking whether AI can replace doctors practicing medicine is the wrong question and approach to improving care. The question is whether there is anything middlemen like PBMs and ASOs and their subsidiaries do that AI can't replace? Doing so will give doctors far more time with patients and improve the quality of life for healthcare providers and patients. And it will reduce the cost of healthcare dramatically. Replace the middlemen with AI."

Much of the technological promise of AI is that it would speed up the production of documentation and allow experts to focus on their jobs rather than drowning in paperwork. Given how the healthcare field continues to grow and the massive amounts of patient information that need to be interpreted for treatment, AI appears poised to significantly reduce the number of administrators. He also has skin in the game. Cuban co-founded Cost Plus Drugs with radiologist Alexander Oshmyansky, a company built on cutting middlemen out of pharmaceutical pricing.

What jobs Cuban thinks won't get replaced by AI

While Cuban believes that AI could dramatically change the job market, he believes that certain industries might not be heavily impacted.

Radiologists and technicians

Hands-on medical workers who handle radiology and complex imaging systems might still be in high demand even with the development of advanced AI technology.

"No chance radiologists get replaced," Cuban said on X (formerly Twitter). "A model is outdated the minute it is released. Model usage costs money. A lot more than a radiologist. Medicine is a business. Putting together AI with domain knowledge is complex. When it can be the difference between life and death, who do you want building it and using it? People forget that using AI and trying to get accurate answers is a skill that will need to be taught in med school. AI won't replace radiologists. But every radiologist will use AI."

There still has to be a human operating the machine and interpreting the results. Even if a robot could do it, a human would still need to be present. And it's much cheaper than running a full model every single time.

Liberal arts majors and the people paid to interpret data

Cuban predicts that companies might start to focus on hiring people who think outside the box and are above the normal distribution in certain creative areas. This is because AI averages all things. Average writing, music, programming, etc. Cuban's bet is that companies would pay a premium for people who could see past it.

"I personally think there's going to be a greater demand in 10 years for liberal arts majors than there were for programming majors and maybe even engineering, because when the data is all being spit out for you, options are being spit out for you, you need a different perspective in order to have a different view of the data. And so having someone who is more of a freer thinker."

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Bottom line

Cuban's line runs between work that follows a script and work that requires judgment. Boilerplate code, receipt checks, prior authorization paperwork: that is what he expects agents to absorb, and quickly. What survives is the part of the job where a person has to decide what the output actually means. That is why he lands on radiologists and liberal arts grads rather than junior developers.

Payroll data points in the same direction. Stanford's Digital Economy Lab found that employment for workers ages 22 to 25 in the most AI-exposed occupations is now about 19% below where it would be if it had kept pace with their less-exposed peers, and that the gap stems from companies not hiring rather than cutting jobs. Experienced workers in the same jobs show no comparable gap. If you are early in a career, the danger is the bottom rung quietly disappearing before you reach it. It is also an argument for building extra income outside of work while your role is still stable.

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