Every major upheaval in business or technology sends ripples through the job market. When mergers and acquisitions and junk bonds were hot in the ’80s and ’90s, corporate finance was the sparkly new job to get after college. Consequently, droves of students brushed up on the subject with a class or two.
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Similarly, when the internet boom descended upon us, undergraduates and MBAs pored over case studies of Amazon and eBay with the hope of impressing prospective dot-com employers.
Flash forward to now. Considering the rapid increase in businesses embracing generative AI and large language models, this is indubitably the dawn of the AI era.
There is an emerging consensus that AI will be crucial in core business applications ranging from customer acquisitions and interactions to dynamic or real-time pricing. Sixty-five percent of US executives surveyed by consultancy KPMG in 2024 said AI will have “an extremely high impact” on their organization in the next few years.
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“I think young people need to know that AI is going to touch absolutely everything, and you do need to have some degree of AI competence in almost any field,” Julia Pollack, chief economist at ZipRecruiter, told ZDNET. “Across all sorts of business functions, you’re seeing a greater need for business analytics.”
Still, these are early days filled with a large degree of ambiguity — as is common at the beginning of all transformative epochs — around how exactly to fuse this technology into businesses.
For prospective entrants into the job market, that ambiguity can have bigger repercussions.
Not knowing how companies are reacting to this tectonic shift, especially when it comes to hiring, adds a layer of uncertainty and anxiety on top of the usual worries about landing a job and paying off student loans.
Who needs AI?
Nick Drydakis, a labor economist at Anglia Ruskin University in the UK and director of the Centre for Inclusive Societies and Economies, took a stab at figuring out what kind of background enables a candidate to be successful in landing an interview and then a job in today’s turbulent job market.
For a study published in May in the Oxford Economic Papers, Drydakis conducted a research experiment where he had two groups of students with identical backgrounds apply for the same jobs across 10 industries by submitting cover letters and resumes.
The students — 1,360 men and 1,316 women — were not exactly slouches. They all had achieved a 2:1 (upper second-class) grade in mathematics, statistics, and econometrics, which is a high distinction in the UK.
The only difference between the groups was that half of the students had taken an AI module, which consisted of lectures and computer-based seminars. Topics included AI’s role in strategy and decision-making, AI tools for the economy, machine learning and its role in econometric approaches, challenges and biases in AI tools, and ethical and legal considerations related to AI.
The other half had no AI experience.
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To gauge the level of employer interest in students with AI experience, Drydakis ensured the cohort that took the AI module included a paragraph highlighting the course content in a few lines.
Over the next five months, Drydakis’ research team sent job openings to each participant that matched their course of study and tracked the ensuing correspondence.
Findings on the AI factor
The experiment’s results are an eye-opener on how industry is adapting to this new landscape and a powerful indicator of how college graduates should begin looking at their course content, irrespective of their field of study.
Fifty-four percent of male applicants and 50% of female applicants with AI “capital”– a term that Drydakis coined to reflect “knowledge, skills, and capabilities related to AI technologies which could boost individuals’ productivity, employment, and earnings” — received interview callbacks versus only 28% and 32%, respectively, who did not take the AI module.
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Most stunningly, the research revealed that those with the AI module were 36% more likely to be asked to interview in large firms where more hiring takes place.
Plus, male job aspirants with the AI module listed on their resume were shortlisted for jobs that had a 12% higher starting salary on average than those who didn’t. For women, the corresponding figure was 13%.
Every job sector will be impacted in some fashion.
“The finance industry, leveraging AI for financial modeling, fraud detection, and algorithmic trading, also demands AI expertise,” Drydakis told ZDNET via email. “Marketing and e-commerce businesses utilize AI for customer targeting, personalized marketing, and sales optimization. Additionally, the manufacturing and logistics sectors use AI for automation, predictive maintenance, and supply chain optimization.”
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Students or professionals who aren’t aiming for roles in a data-crunching industry — and therefore don’t believe they need any AI arrows in their quivers — could come to regret it.
“Increasing AI skills among non-experts is considered as important as training AI experts,” Drydakis said. “The former group will most likely use AI or collaborate and coexist with it.”
So, for college students planning their courses of study, learning about AI, regardless of major, could help them gain an edge and land that first job.
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