While it’s risky business for anyone to foretell the impact of ChatGPT, this hasn’t stopped hundreds of commentators from jabbering on about how it’ll change how we live, work, and learn (including how it could be a plague upon education or result in a “nuclear-level catastrophe”). But what about AI’s impact on employers, and the workers they’re having so much trouble finding?
As AI begins to reshape the world of work, it will be increasingly important to distinguish between its impact on the skills gap and the experience gap. The skills gap reflects discrete abilities employers expect of (but often aren’t seeing in) candidates, primarily digital or platform skills along with soft skills employers love to complain about. The experience gap is, essentially, the mortar around these skill bricks. Do candidates have enough experience to know what to do with their skills, how to apply them in a specific job function and industry? For most employers, the only way to assess that is demonstrated experience.
The good news is that AI appears likely to help close some skill gaps. Digital platforms will soon be equipped with functionality so users can explain in natural language what they want systems to do. Think about the tens of thousands of new college graduates who toil away in investment banks building presentations to sell clients on one transaction or another. AI will save much of this time, allowing new analysts to perform higher order, higher value work like developing real sector expertise, networking, and business development. Professionals who have already begun leveraging ChatGPT for their work report it’s incredibly useful and satisfying; MIT researchers found that by relieving employees of many mundane duties, ChatGPT significantly improves job satisfaction.
Good entry-level jobs in peril
But the troubling news is that these automatable tasks constitute much of what we now know as good entry-level jobs across many industries. As AI makes skills more accessible, employers will place a higher premium on knowing what to do with skills. From digital marketing to accounting, AI-inflected entry-level jobs will start to look a lot like today’s mid-level jobs, which demand years of experience. As a result, years of experience—or the equivalent in demonstrable skills and certifications—is what employers are likely to add to “entry-level” job descriptions. In short, employers might reasonably expect entry-level workers to be conversant with AI and something like 50% more productive. And this means while the skills gap may narrow, the experience gap could become a chasm.
Related: Will you lose your job to AI?
We’ve already seen this play out in cybersecurity, a sector already worked-over by AI. It’s not uncommon to see position descriptions for entry-level security operations center (SOC) analyst positions demanding “at least four years of experience, including time doing penetration testing, digital forensics and vulnerability assessments; and professional certificates.” As one college senior posted on LinkedIn, “I’ve lost count of the number of ‘junior’ cybersecurity role advertisements I’ve seen that want 1-3 years of experience and a CISSP. Anyone who knows anything about the CISSP knows you need minimum five years of full-time experience.”
One way to think about cybersecurity: Tier I detection and response has been largely automated, so junior jobs are tier II and above. Olivia Rose, former chief information security officer at Mailchimp, wrote “it breaks my heart to see all these young, driven, hard-working young people trying so very hard to get their first job, but . . . we cannot just get our %^)-(#% together and give them a chance.”
Overcoming the growing ‘experience gap’
The problem is that, while career launchers can theoretically solve a skills gap via last-mile training, an experience gap is a tougher nut to crack. As a result, the bar for good entry-level jobs will be higher, meaning fewer jobs that look entry level, and rendering career launch even more difficult. Digital transformation made employers more selective and gun-shy about entry-level hiring, but generative AI will take it to a new level. More than ever, employers will only want to onboard entry-level workers who’ve already proven they can do the job.
The problem will become even more acute with the emergence of industry-specific large language models. Bloomberg has already developed BloombergGPT, “a 50 billion parameter language model that is trained on a wide range of financial data.” It’s generative AI for the finance industry that will only be useful to workers with some experience. We’ll see similar specialized AI emerge for every major industry: insurance, healthcare, logistics, cybersecurity, etc. After this comes function-specific AI for sales, marketing, product management, purchasing, customer support, HR, and IT. The upshot is an experience gap paradox: Without requisite domain knowledge, entry-level workers won’t know what to ask AI for. And no one is suggesting that some new form of AI will help them figure out what to ask AI.
If this is the future that awaits us, what should we do to prepare for it? In the ChatGPT era, the future of career launch and socioeconomic mobility will depend on scaling pathways that not only teach, but also provide relevant work experience. Schools will need to scramble. Career and technical education and youth apprenticeships will become priorities for every high school.
In higher education, it will mean reforming Federal Work-Study to prioritize meaningful off-campus work over menial on-campus work, integrating real work projects into coursework via experiential learning marketplaces like Riipen, and doing much more to provide every student with multiple (paid) internships. Even more important, it means a complete rethinking about the importance of “earn and learn” models like apprenticeships: how apprenticeship jobs are actually created, and how governments fund and support them. As generative AI transforms entry-level jobs and puts a premium on experience, these earn-and-learn models are likely to be the best bet for helping millions of young people launch careers.
The alternative is a cataclysm, or more aptly, a “chataclysm”: an AI-induced decline in good jobs that are truly entry-level, high youth unemployment and underemployment, even higher inequality and political instability. States and nations that fail to prepare for the impact of generative AI on entry-level jobs might find themselves in as bad shape as young career launchers themselves.
Ryan Craig is the author of College Disrupted and A New U: Faster + Cheaper Alternatives to College. He is managing director at Achieve Partners, which is investing in the future of learning and earning.
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