Building Careers with AI Skills – Explore Interactive Data
As technology evolves, broader accessibility to AI knowledge has made certain skills less unique. Universities are rapidly integrating AI into undergraduate and postgraduate programs with emerging AI-specialized colleges and intensive training, contributing to a larger pool of AI-skilled graduates. Stanford University’s 2022 AI Index report highlights a significant rise in the number of AI PhDs awarded over the past decade, with most graduates moving into industry roles rather than academia or government.
Additionally, platforms like Coursera, Udemy, and edX provide courses on AI, machine learning, and related fields, often taught by top universities or industry experts. This accessibility has enabled millions to acquire skills that were previously limited to specialized academic programs or elite institutions.
With the rapid integration of AI courses both in higher education as well as outside of it, let’s take a look at how degree requirements play a role in the job market.
The top skills to have when looking for a job in AI are Data Modeling (11%) and Machine Learning (9%). Out of all AI job postings from 2010-2023, the top 10 most frequent skills are listed in 63% of postings, indicating high company preference for these skills.
In 2010, job applicants were required to have some form of higher education (Bachelor’s, Master’s, PhD) when applying for jobs listing machine learning as a required skill. In 2023, all degree types, and no degree, were listed for postings requiring machine learning
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This dual trend suggests a more inclusive job market where skills, experience, and continuous learning are gaining equal footing with formal education.
Higher education levels, particularly Master’s Degrees and Ph.D. or Professional Degrees, are associated with higher salaries, suggesting companies are willing to pay more for individuals with advanced degrees.
The graph suggests though, there are exceptions, especially for roles in technical fields or those requiring specialized skills – machine learning for example. The salary data points to a trend where higher education typically leads to higher-paying opportunities, but companies are also willing to hire individuals without advanced degrees, particularly when skills and experience can compensate for the lack of formal education. As industries evolve, we may continue to see a greater emphasis on upskilling and experience in hiring practices, on top of educational background.