3 days ago
AI May Be Erasing Entry-Level Jobs
Purple ID card holder on black background with text Entry-level worker - refers to starting jobs ... More require little or no professional experience allow first jobbers just graduating to enter workforce
There's a new report out on jobs this month, and it's not reassuring a lot of people who were worried about job displacement, especially for new graduates and less experienced workers.
We know intuitively that that is a hard time to come of age as someone pondering a career. There are a lot of question marks around what AI is going to do to the job market.
However, the wide-ranging report from Signalfire is showing us some early visions of what might come to pass in the years ahead. The scope of the study is impressive: it uses data from 650 million professionals, and 80 million organizations. There are breakout statistics for smaller groups of companies and workers, but the study in general relies on a pretty good survey of market data.
One of the most sobering parts of the report is the idea that there's a generational shift taking place, and that it largely has to do with decreases in entry-level opportunities for new workers.
For somebody just graduating from college, entry-level work is the name of the game. They can smooth the path with an internship or some kind of freelance position, but essentially, new career professionals have always faced that challenge of needing a job to get experience, and needing experience to get the job.
However, what the study suggests is that this struggle has just gotten leaner and meaner – with a rise of 5.8% in unemployment for new college grads, and similar other harbingers of doom for Gen Z as a labor force. Other cited statistics include increases in certain law school admissions, with report writers theorizing that young professionals often put off job searches by attending law school when markets are tight. New graduate hires, the report shows, are down 50% from pre-pandemic levels.
There's also the suggestion that non-technical job roles keep shrinking, and demand for high-tech positions (filled by experienced people) keeps growing, where senior people may be hired to fill junior positions. There's the question of whether college educations are keeping up with the skill sets employers are looking for. Fundamentally, the question that this asks is: if AI can do all of the go-fering, what happens to the go-fer jobs that have springboarded careers for decades?
The study also analyzed where jobs are being created in the tech world.
What they found is in increases in regional hubs like Miami and San Diego, lower hiring rates in parts of Texas, and continue dominance in San Francisco and New York where over 65% of the software engineers are located.
The report explains it in this way, which to me seemed a little obtuse:
'More companies are embracing hub-and-spoke models, and tailoring compensation philosophies to ensure they secure the right talent mix across diverse locations.'
The move toward larger hiring hubs makes sense in co-locating the talent with the infrastructure, and growing the economy of major cities, while emptying American small towns that weren't doing very well anyway. Economists and even public planners would presumably find it pretty easy to imagine how these trends will exacerbate the hollowing out of secondary or tertiary communities, and the building of massive metropolitan areas around hub cities.
In other parts of the study, there's more analysis of how this could affect both workers and companies.
I listen to an explication of the study from Nathaniel Whittemore at AI Daily Brief, where he went over a lot of the cultural aspects in play. He noted study suggestions that there may be other reasons for lower entry-level hiring, like higher interest rates and different company budget realities.
But he also cited cultural business decisions, for example, in consulting and other areas, where some companies may just demand more from workers as a result of higher AI productivity. Whittemore cited engineers working for Amazon, where some of them have said that their job roles start to seem more like working in an Amazon warehouse, with the kinds of tight quotas and productivity mandates that you would associate with the word 'sweatshop'.
'I think that we're experiencing is an example of how challenging transitional periods can be,' he said, unpacking all of the uncertainties around how productivity gains will be handled. 'If you are a regular listener to this show, you'll know that I am net bullish on how all of this shakes out, I think that AI is going to bring massive disruption to the way that we work. ... I think that the market absorbs a huge amount of talent that would have otherwise been absorbed into these big companies in new and interesting ways. But that doesn't mean that it's not going to be extraordinarily painful along the way.'
While companies, he notes, could train people better, they may just raise output goals, and be less forgiving of deadlines. Whittemore quotes a Harvard professor predicting a 'speed-up for knowledge workers,' which would represent the more partisan approach by employers – and unfortunately for new workers, that's not without precedent.
There's a need, Whittemore suggests, for leadership, to determine whether there's a 'dehumanizing' or 're-humanizing' of human workers in the AI age.
For that more targeted content from the report, here's an example, where in a study of the top 15 tech companies from 2019 to 2024, we see that there's almost a night and day difference on the chart lines between those with two or less years of experience, and others with more.
It's scary for people who lack those first few years of career experience.
In conclusion, I wanted to just post the last section of the report verbatim, because I think it speaks for itself:
'What it means for the road ahead:
- For new grads: The training wheels are gone. With fewer entry-level roles, the path forward will rely on bootcamps, open-source, freelancing, and creative projects. It's not enough to just master the latest AI tools; learn to fix their flaws—debugging messy, machine-generated code may be your superpower.
- For employers: AI might reduce the short-term need for junior hires, but skipping them entirely risks breaking the long-term talent pipeline. The industry's future depends on equipping the next generation with skills that grow alongside the evolving technology landscape.'
So basically, doing too much in this area can hurt both the company, and the workers. Will we be able to find a solution that works for everybody?
Anyway, this is a lot to take in for new hires or potential career professionals who are just graduating and entering the workforce. As Whittemore concedes, we are going to have to figure this out, and things could get messy before we end up with a solution for how to integrate AI changes into this aspect of our lives.
