As technology increases, it becomes easy to automate processes. This is, of course, a good thing. Machines make the things we use daily, and people don’t have to hand-dip candles to provide light.
But what happens when AI steps in and does low-level tasks? It saves people time and allows people to focus their skills on higher-level tasks, which seems like a tremendous economic benefit, but it raises a key question: How do you learn to do higher-level tasks without mastering the entry-level tasks?
Likewise, how do you hire for mid-level roles when people lack entry-level experience?
A Disappearing Funnel
“To be brutally honest, we had a hierarchy of things that technology could do,” Erik Brynjolfsson, a Stanford Institute for Human-Centered AI professor, told The New York Times, “and we felt comfortable saying things like creative work, professional work, emotional intelligence would be hard for machines to ever do. Now that’s all been upended.”
In other words, many people were OK with technology automating blue-collar jobs. But now that it’s white-collar jobs, it’s concerning — not just for the number of jobs but the training required for those roles.
Meanwhile, Alexandra Samuel, co-author of Remote, Inc.: How To Thrive at Work…Wherever You Are, told SHRM that recruiters “are going to face a bottleneck when it comes to mid-career hiring because a lot of companies are going to replace big portions of their junior workforce with generative AI tools.” She went on to point out that AI is “not really a flattening out of the middle as much as it is a cutting off of the bottom.”
Consequently, there becomes the further problem of creating leadership in that you typically have a vast entry-level workforce that whittles down to a few leaders at the top. Without that wide funnel, however, you may not have enough people to excel in leadership positions.
The Training Problem
When Andrea (who needs to remain anonymous because she’s not authorized to speak about her employer’s hiring practices) graduated from nursing school in 2012, she struggled to find a job. Many hospitals told her to get some experience first and then apply.
Andrea wasn’t alone. New grads struggled to find jobs despite a well-documented nursing shortage and fears that the gap would only increase. Companies didn’t wish to invest in the costly training of freshly minted RNs.
Yet when you do away with the entry-level roles, someone has to do the training, or eventually you run out of trained people. This can be done through on-the-job training or increased education, but the difference is in who pays. On-the-job training comes at the company’s expense, while education usually comes at the employee’s expense, with no job guarantee.
Hiring already trained people works until it doesn’t. Raffaella Sadun, the Charles E. Wilson Professor of Business Administration at Harvard Business School, points out in Harvard Business Review that this type of hiring of external talent isn’t enough and suggests being “more focused on internal talent, and not just upskilling internal talent but also re-skilling, which means giving them training that allows the workforce to jump from one occupation to the other.”
AI is forcing a reskilling of sorts, but it’s not the only force that disrupts hiring patterns. Today, a cardiovascular ICU nurse, Andrea said new grads have no trouble finding jobs. Why? A different disrupter: Covid.
Why Disruption Matters for Hiring
“After Covid, there was a mass exodus as nurses retired early, left acute care for something less taxing like Botox clinics, like three of my coworkers did,” Andrea says. “And a lot of nurses just burned out and switched fields. Now 85% of our night shift is staffed by people who have been nurses for less than a year and in ICU for three to six months.”
People saw AI coming, but large language models seem poised to take over entry-level jobs faster, while Covid was unexpected. No one knows the next significant disrupter, but there will be another, and hiring needs to be flexible.
The takeaway is that a lack of training over the years, combined with burnt-out long-term staff, resulted in newly minted nurses providing critical care. And while the percentage of deaths caused by medical errors is in dispute, everyone agrees it is not a small number. Hiring practices combined with an external disruption resulted in less experienced nurses, which has led to worse outcomes. If staffing levels had been higher prior to Covid, nurses would have been less likely to burn out and more likely to be highly skilled when needed.
The Consequences of No Entry-Level Jobs
Skipping entry-level due to AI taking over can sound scary, but the U.S. has already moved the bar on this. In 1960, only 7.7%t of adults had four-year degrees or more. That number has steadily climbed to 37.9% in 2021.
The job market changed substantially during that time as job requirements increased, shifting the burden of training to the individual to receive a college education.
Additionally, today, 21% of college students do internships, and 31% of internships are done by people after graduation. In other words, it’s moving the entry-level line.
This entry-level movement will likely continue to happen as AI becomes more of a force in the workplace. The jobs that Business Insider identified as most likely to be disrupted by AI are all jobs requiring large ranges of skills. If you cut off the funnel, as Samuel said, you have to compensate by training in another way. Prepare for more internships, certificates, and struggles of a mismatched workforce and job openings — at least until another disruption comes along and forces companies to hire the untrained, as happened in the medical field.