How Students Can AI-Proof Their Careers
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How Students Can AI-Proof Their Careers

Artificial intelligence is going to eliminate a lot of jobs in the future. It’s possible to reduce the risk that it will be yours.

By JAMES R. HAGERTY
Thu, Nov 21, 2024 10:17amGrey Clock 5 min

The current generation of college students is facing a challenge that those who came before never had to worry about: They’ll be competing with AI for jobs.

What can they do to get ready?

After all, artificial intelligence is likely to eliminate at least some jobs that formerly served as first rungs on career ladders. “We have to accept and embrace the idea that in fact with AI we are going to have jobs that are going to be eliminated and jobs that are going to be created, and we don’t know which ones,” says Joseph E. Aoun , president of Northeastern University.

That uncertainty leaves today’s college students struggling to prepare for a workplace that is changing faster than ever. We asked a range of career counselors and employers how they would suggest students AI-proof their careers. One consensus: It’s important to master skills not easily matched by machines, such as human-style communications and the ability to understand and work smoothly with people who have different perspectives and personalities.

“In many ways the human skills are going to be more fundamental than they are now,” as machines take over some routine tasks, Aoun says.

A survey of 255 employers by the National Association of Colleges and Employers last year found that the three top “competencies” they sought in job candidates were communication, teamwork and critical thinking.

Communication and teamwork rely on emotional intelligence, or EQ. “AI has probably won the IQ battle,” says Tomas Chamorro-Premuzic , chief innovation officer at Manpower Group and professor of business psychology at Columbia University, “but the EQ battle is up for grabs.”

Of course, that doesn’t mean students shouldn’t master AI. Skill in using AI as a productivity-enhancing tool can give them an edge over older workers who haven’t mastered ChatGPT and other AI programs.

But knowing how to use AI effectively isn’t enough. Here are some suggestions from the experts on how students—or really anybody—can reduce the risk they will eventually be replaced by AI.

Cultivate your ability to work with other people, including jerks

AI can write computer code, improve grammar and solve math problems, but so far it lacks the ability to mediate squabbles among colleagues, charm potential clients over cocktails or soothe angry customers. So developing those skills may be one of a job applicant’s best selling points.

Anything that requires talking and cooperating with strangers is helpful. That includes volunteering in a nursing home or an after-school youth program, or leading an on-campus club or sport. Jobs that require dealing directly with lots of other people, including jerks, are an educational opportunity. “If you’re a waiter you will understand human beings better,” says Chamorro-Premuzic.

Go wide and avoid hyper-specialisation

Focusing too heavily on one type of expertise could be a mistake if, as expected, AI eliminates lots of jobs in some specialties. It isn’t a risk only for technology fields like computer science; other fields such as accounting and finance are also being transformed by AI.

Instead, experts recommend having a portfolio of skills.

“If you have one skill, you compete with the masses that have that same one skill,” says Anna Esaki-Smith , author of “Make College Your Superpower.” In contrast, she says, “Should you stack on another skill, you become qualified for a wider range of opportunities.”

That could mean adding a minor or two to a major or going for a double major. It also could involve a strategic selection of electives. D. Raja , chief executive of CEI, a Pittsburgh information-technology consulting firm, says he increasingly looks for job candidates who have both technical skills and a grounding in business, enabling them to understand clients’ needs. An M.B.A. stacked atop a computer-science degree is one good strategy, he says.

Though a range of skills and knowledge is an advantage, it’s still important to develop deep expertise in at least one or two areas. “AI has disrupted superficial expertise,” Chamorro-Premuzic says. In other words, you have to know more than generative AI programs can spit out in a minute or two.

Show you can organise a big project and get it done

If AI will do at least some of the grunt work, people will still be needed to devise strategies and carry out complicated projects. Machines do pieces of work, but “we still need big-picture humans to put it all together,” says John Behrens , director of the technology and digital studies program at the University of Notre Dame.

To help students learn how to manage complexity, many universities require them to complete a capstone project before graduation. Those can include primary research, ambitious artworks or community-service projects.

Vanderbilt University calls such projects “immersion.” For his Vanderbilt project, Logan Glazier is converting an old school bus, once consigned to the junkyard, into an RV with solar panels mounted on the roof to power his refrigerator and other appliances.

He expects to finish the project within a few months, before graduating next spring with a degree in civil engineering. Glazier had to sell his idea to university administrators, persuade them to give him space to work on the bus, develop a plan and find materials. He watched dozens of YouTube videos and consulted with Vanderbilt professors.

He recalls the reaction he got from people at the engineering consulting firm HNTB when they heard about the project: “Wow, that’s really cool!” He got an HNTB internship in 2023 and recently accepted a full-time job at the firm starting in May, after his graduation.

Be open to new experiences

As AI and other technological changes make career paths less predictable, adaptability will be an advantage. “We don’t know what the world is going to be like in five years or 10 years,” says Behrens.

Students can develop their adaptability by seeking out new experiences, such as studying abroad or taking unconventional courses. At Carnegie Mellon University, renowned for computer science and robotics, one of the most popular electives is “Acting for Non-Majors,” offered by the Pittsburgh school’s drama department. Students have long taken the course, but now demand has soared as students see it as a plus in the job market, forcing them to shed their inhibitions and engage with other people in unscripted ways.

This year, to accommodate demand, CMU quadrupled the capacity of the course.

“It’s exhilarating,” says Emily Ma , a math major. “Acting forces you to step outside your comfort zone.” That’s particularly important for a generation of young people who were isolated during the Covid-19 pandemic and spent far more time staring at screens than they did engaging directly with people.

Be a moderate misfit

Amid all the changes AI is bringing, companies want fresh thinking. So one route to success is to be a “moderate misfit,” unhappy with the status quo and ready to innovate, says Chamorro-Premuzic. By moderate, he means that “you fit in well enough and work well with others but are not so bland and risk-averse as to lose the desire for change and progress.”

Chamorro-Premuzic advises young people not to seek employers that fit perfectly with their values but rather to “look for places they like but which they also dream of transforming and improving.”

AI is like a B+ student and can tell you what the average person would say, says Matthew Rascoff , vice provost for digital education at Stanford University. A+ work, he says, is the product of an individual brain with a distinctive voice. So he urges students to develop their own voices and identities. “The more you outsource” to AI, he says, “the less you are developing that muscle.”



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In a Sea of Tech Talent, Companies Can’t Find the Workers They Want

A divide has opened in the tech job market between those with artificial-intelligence skills and everyone else.

By CALLUM BORCHERS
Thu, Oct 2, 2025 4 min

There has rarely, if ever, been so much tech talent available in the job market. Yet many tech companies say good help is hard to find.

What gives?

U.S. colleges more than doubled the number of computer-science degrees awarded from 2013 to 2022, according to federal data. Then came round after round of layoffs at Google, Meta, Amazon, and others.

The Bureau of Labor Statistics predicts businesses will employ 6% fewer computer programmers in 2034 than they did last year.

All of this should, in theory, mean there is an ample supply of eager, capable engineers ready for hire.

But in their feverish pursuit of artificial-intelligence supremacy, employers say there aren’t enough people with the most in-demand skills. The few perceived as AI savants can command multimillion-dollar pay packages. On a second tier of AI savvy, workers can rake in close to $1 million a year .

Landing a job is tough for most everyone else.

Frustrated job seekers contend businesses could expand the AI talent pipeline with a little imagination. The argument is companies should accept that relatively few people have AI-specific experience because the technology is so new. They ought to focus on identifying candidates with transferable skills and let those people learn on the job.

Often, though, companies seem to hold out for dream candidates with deep backgrounds in machine learning. Many AI-related roles go unfilled for weeks or months—or get taken off job boards only to be reposted soon after.

Playing a different game

It is difficult to define what makes an AI all-star, but I’m sorry to report that it’s probably not whatever you’re doing.

Maybe you’re learning how to work more efficiently with the aid of ChatGPT and its robotic brethren. Perhaps you’re taking one of those innumerable AI certificate courses.

You might as well be playing pickup basketball at your local YMCA in hopes of being signed by the Los Angeles Lakers. The AI minds that companies truly covet are almost as rare as professional athletes.

“We’re talking about hundreds of people in the world, at the most,” says Cristóbal Valenzuela, chief executive of Runway, which makes AI image and video tools.

He describes it like this: Picture an AI model as a machine with 1,000 dials. The goal is to train the machine to detect patterns and predict outcomes. To do this, you have to feed it reams of data and know which dials to adjust—and by how much.

The universe of people with the right touch is confined to those with uncanny intuition, genius-level smarts or the foresight (possibly luck) to go into AI many years ago, before it was all the rage.

As a venture-backed startup with about 120 employees, Runway doesn’t necessarily vie with Silicon Valley giants for the AI job market’s version of LeBron James. But when I spoke with Valenzuela recently, his company was advertising base salaries of up to $440,000 for an engineering manager and $490,000 for a director of machine learning.

A job listing like one of these might attract 2,000 applicants in a week, Valenzuela says, and there is a decent chance he won’t pick any of them. A lot of people who claim to be AI literate merely produce “workslop”—generic, low-quality material. He spends a lot of time reading academic journals and browsing GitHub portfolios, and recruiting people whose work impresses him.

In addition to an uncommon skill set, companies trying to win in the hypercompetitive AI arena are scouting for commitment bordering on fanaticism .

Daniel Park is seeking three new members for his nine-person startup. He says he will wait a year or longer if that’s what it takes to fill roles with advertised base salaries of up to $500,000.

He’s looking for “prodigies” willing to work seven days a week. Much of the team lives together in a six-bedroom house in San Francisco.

If this sounds like a lonely existence, Park’s team members may be able to solve their own problem. His company, Pickle, aims to develop personalised AI companions akin to Tony Stark’s Jarvis in “Iron Man.”

Overlooked

James Strawn wasn’t an AI early adopter, and the father of two teenagers doesn’t want to sacrifice his personal life for a job. He is beginning to wonder whether there is still a place for people like him in the tech sector.

He was laid off over the summer after 25 years at Adobe , where he was a senior software quality-assurance engineer. Strawn, 55, started as a contractor and recalls his hiring as a leap of faith by the company.

He had been an artist and graphic designer. The managers who interviewed him figured he could use that background to help make Illustrator and other Adobe software more user-friendly.

Looking for work now, he doesn’t see the same willingness by companies to take a chance on someone whose résumé isn’t a perfect match to the job description. He’s had one interview since his layoff.

“I always thought my years of experience at a high-profile company would at least be enough to get me interviews where I could explain how I could contribute,” says Strawn, who is taking foundational AI courses. “It’s just not like that.”

The trouble for people starting out in AI—whether recent grads or job switchers like Strawn—is that companies see them as a dime a dozen.

“There’s this AI arms race, and the fact of the matter is entry-level people aren’t going to help you win it,” says Matt Massucci, CEO of the tech recruiting firm Hirewell. “There’s this concept of the 10x engineer—the one engineer who can do the work of 10. That’s what companies are really leaning into and paying for.”

He adds that companies can automate some low-level engineering tasks, which frees up more money to throw at high-end talent.

It’s a dynamic that creates a few handsomely paid haves and a lot more have-nots.

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