AI a job killer? While AI gets partially the blame for headline-grabbing layoffs such as Amazon shedding 14,000 employees, it’s notable that more than five million people still get hired monthly within the United States. The latest figure from the Bureau of Labor Statistics puts the hiring rate at 5,126,000 for the month of August.
Less than two in 10 executives, at most, foresee job cuts as a result of AI in their own organizations, according to the authors of a new study of 800 business leaders out of University of Pennsylvania’s Wharton School and GBK Collective. If anything, 40% expect AI to help boost hiring of entry-level jobs, while another 40% say their hiring patterns will not change. Only 18% foresee AI decreasing entry-level job opportunities. Likewise, 33% of executives expect AI to increase hiring of executives, and another 54% expect no effect on the sizes of their executive staffs.
This is the third year for this particular study, conducted by Wharton’s Human-AI Research (WHAIR) center.
Some parts of the business will see the greater impact from AI than others. IT departments lead the pack, with 47% affected by AI, up from 30% in the 2023 survey. Purchasing and procurement comes in at 39%, up from 14% just two years ago. At least 37% of product development and engineering departments will be reshaped by AI, up from 22% in the 2023 survey.
When it comes to measuring relative success rates with generative AI, the Wharton study paints a generally positive picture. A few weeks back, a lot of eyebrows were being raised about MIT researchers’ estimates that only five percent of generative AI projects are showing tangible results in businesses.
The current Wharton study, on the other hand, finds at least three in four enterprises, 74%, are already seeing positive returns on their genAI investments, the Wharton survey finds. These results are based on solid ROI metrics such as productivity, profitability and throughput.
The successes with AI were self-reported in the Wharton/GBK study, as the co-authors note that they “intentionally asked the question about ROI for gen AI in a fairly broad way to allow leaders to essentially answer according to their own definition.” Are executives compelled to portray a rosier picture of their efforts? Who knows, right?
Perhaps there is greater comfort with AI. Close to half of these executives, 46%, now use gen AI on a daily basis in their work. A majority, 82%, use it weekly.
On average, 82% business leaders expect their AI investments to pay off in just two to three years.
With the technology evolving almost every day, the greatest inhibitor is “skill atrophy” — meaning it takes talent and training, not just technology, to fully succeed with AI. Decision-makers see gen AI as a supplement to human capital (89% agree), more than a replacement (71% agree). Still, 43% agree that gen AI will lead to declines in proficiency.
The higher you go up the corporate hierarchy, the more optimism you find pertaining to gen AI. Leaders at the vice-president level and above are much more optimistic about early ROI for their gen AI investments compared to mid-managers, with 45% reporting significantly positive returns (defined as greater than 20% ROI) versus only 27% of mid-managers. Mid-managers, the survey shows, are more cautious, and are twice as likely to say it is “too early to tell/still in pilot phase” (16% versus 8% of senior leaders).
