of The Wall Street Journal Recently, it was reported that a battle has broken out between tech giants for scarce and valuable AI talent, part of a much larger talent shortage looming over the U.S. economy in the coming years as AI becomes a critical business infrastructure.
Since generative AI (GAI) burst onto the scene in late 2022, the technology has been advancing rapidly, driven by public interest and huge investment. Large technology companies such as Google, Meta, and Microsoft have been busy building and improving customer tools to meet the demand. It is expected that GAI will become the new “general purpose technology” that will reshape the US and global economy, increasing efficiency and sparking a new productivity boom. PwC estimates that AI could contribute up to $15.7 trillion to the global economy by 2030.
Given concerns about AI-induced unemployment, it is ironic that workforce is becoming one of AI’s most important bottlenecks. Until last year, GAI research was concentrated in academia and a few “cutting edge” companies like OpenAI, relying on a relatively small number of senior experts for much of the theory and initial design work. Now, a wide range of companies have entered the fray, and the competition for skilled AI engineers is fierce. Salaries for top AI talent regularly reach seven figures, astonishing even in an industry long known for eye-popping compensation. These developments point to an important reality: we need new solutions to scale the AI workforce, rather than simply moving the same workers between companies.
The twists and turns of education, training and skills in the technology sector seem to never end. The Federal Reserve's inflation-fighting measures, a destabilizing banking system and shareholders' demands for higher profits are forcing the tech sector to cut jobs. The layoffs that began a year ago are still ongoing. Labor statistics show that tech companies have cut almost 90,000 jobs since the start of the year. That's more than the 260,000 tech jobs expected to be lost in 2023.
Programmers and engineers haven't been hit as hard as those in HR, marketing, sales, and other support roles, but even a slight drop in demand for computer science (CS) degrees has increased anxiety for CS students and workers. The New York Times Reports suggest that internships leading to jobs at major tech companies are becoming fewer and fewer, and more distant. Computer science degrees have dropped a notch or two in importance in favor of more general “engineering-ready” skills. Finally, students who once hoped to work for top tech companies like Amazon or Google are now turning to jobs in automotive, retail, and logistics. The slowdown in the tech industry is clear.
Importantly, tech workforce trends are representative of the future of an AI-infused workforce more broadly. Access to AI tools like GitHub, Claude, and ChatGPT is democratizing skills and lowering the barrier to entry for workers across sectors. AI is also putting pressure on agile engineering. Higher education institutions are looking for ways to diversify CS education to include broader, more generic skills that help students adapt to changing skill demands. AI is beginning to permeate the “real” economy in production and services, requiring sector-specific AI capabilities and reskilling of incumbent workers who know little about AI but can learn how to use it to smooth workflows and improve productivity. Top-tier AI talent will remain valuable, but “simply good” programmers may need to be retrained as experts in using AI.
In March, a conference hosted by New York University economist Dr. Julia Lane, AEI, and the Stanford Institute for the Digital Economy hosted a workshop of senior economists and labor market intelligence experts to explore strategies for forecasting how AI and other “idea industries” will affect future jobs and skill demand. Job and skill forecasting is a fluid phenomenon, shifting unpredictably in response to shifts in technology and consumer demand. Providing accurate and transparent information to educators, students, and workers may be one of the best ways to equip U.S. businesses and workers with the information they need to make better decisions about education and training.
America's top AI professionals are by far the best on the planet, but they're like the NFL's starting quarterback who keeps throwing the impressive “long bomb.” As the future of AI unfolds, we'll need linebackers, managers and coaches to execute not just the big plays, but the “three yards and dust” advances that will lead to increased productivity and shared prosperity. Now is the time to get to work on that playbook.
