Any big change in business or technology sends ripples through the job market. In the '80s and '90s, with mergers and acquisitions and junk bonds all the rage, corporate finance was the sexy new job you could get after college, and as a result, many students spent a class or two retrieving the subject.
Similarly, when the Internet boomed, undergraduates and MBAs eager to impress future dot-com employers pored over case studies of Amazon and eBay.
Fast forward to the present day, and with the proliferation of companies adopting generative AI and large-scale language models, this is arguably the dawn of the AI era.
There is an emerging consensus that AI will be critical to core business applications, from customer acquisition and interactions to dynamic or real-time pricing. In a 2024 survey by consulting firm KPMG, 65% of U.S. executives said AI will have a “very significant impact” on their companies in the next few years.
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“I think young people need to know that AI is going to touch everything, and that just about every field will need some level of AI capabilities,” ZipRecruiter chief economist Julia Pollack told ZDNET. “We're seeing a growing need for business analytics in all kinds of business functions.”
Still, as is often the case at the beginning of any transformational period, it's still early days and there's a lot of uncertainty about how to integrate this technology into business.
For those trying to enter the job market, that ambiguity could have an even bigger impact.
Not knowing how companies will react to this structural change, especially when it comes to hiring, will add uncertainty and anxiety on top of the usual worries about finding a job and paying off student loans.
Who needs AI?
Nick Drydakis, a labor economist and director of the Centre for Inclusive Economics at Anglia Ruskin University in the UK, wanted to understand what types of applicants are able to get interviews and then land jobs in today's precarious job market.
For a study published in the journal Oxford Economic Papers in May, Drydakis ran a research experiment in which he asked two groups of students with similar backgrounds to submit cover letters and resumes to apply for the same jobs across 10 industries.
The pupils (1,360 boys and 1,316 girls) were by no means poor achievers: all achieved 2:1 grades in mathematics, statistics and econometrics, an excellent result for the UK.
The only difference between the groups was that half of the students had taken an AI module consisting of lectures and computer-based seminars. Topics included the role of AI in strategy and decision-making, AI tools for the economy, machine learning and its role in econometric approaches, challenges and biases of AI tools, and ethical and legal considerations related to AI.
The other half had no prior experience with AI.
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To gauge the level of employer interest in students with AI experience, Drydakis ensured that the group who took the AI module included a paragraph highlighting the course content in a few lines.
Over the next five months, Drydakis’ research team sent each participant job offers that aligned with their course of study and tracked subsequent correspondence.
AI Factors Survey Results
The results of this experiment are an eye-opener on how the industry is adapting to this new situation and a strong indicator of how college graduates should start looking at course content, regardless of their major.
54% of male applicants and 50% of female applicants with AI “capital” (a term coined by Drydakis to describe “knowledge, skills and abilities related to AI technologies that have the potential to enhance an individual's productivity, employment and income”) were called back for an interview, compared with just 28% and 32%, respectively, of applicants who did not take the AI module.
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Most surprisingly, the study found that people with the AI module are 36% more likely to be invited for an interview at large companies with high hiring activity.
Additionally, male job seekers who included an AI module on their resume were, on average, able to land jobs with a starting salary 12% higher than those who did not; for women, the figure was 13%.
Every career field will be affected in some way.
“The financial industry is leveraging AI for financial modeling, fraud detection, and algorithmic trading, and AI expertise is also in demand,” Drydakis told ZDNET in an email. “Marketing and e-commerce businesses are using AI for customer targeting, personalized marketing, and sales optimization. Additionally, the manufacturing and logistics sector is using AI for automation, predictive maintenance, and supply chain optimization.”
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Students and professionals who think they are not aspiring to a role in the data processing industry and therefore do not need to have an AI arrow in their quiver may be in for some regret.
“Improving the AI skills of non-experts is seen as just as important as developing AI experts,” Drydakis said. “The former group is more likely to use AI or to work with and coexist with it.”
So for college students planning their studies, learning about AI, regardless of their major, could help them get a leg up and land their first job.
