The people building AI are no longer just selling software. They are selling a vision of an age of abundance. OpenAI CEO Sam Altman predicts “massive prosperity.” Anthropic CEO Dario Amodei argues that people underestimate AI’s “radical upside.” Elon Musk imagines a future of “sustainable abundance” whereby everyone can access whatever goods and services they want.

It is easier to be optimistic about AI’s future when you are among its primary beneficiaries. Still, the possibility does raise an important question: In an age of abundance, who will actually be prepared to participate in it?

The rise of artificial intelligence is changing what work looks like, what skills matter, and how quickly old competencies lose value. As an initial response, some companies are reducing entry-level roles while employees are finding mid-career transitions more difficult to navigate. A growing share of workers are finding themselves excluded from the prosperity AI is supposed to create.

At a time when students and families are increasingly questioning the value of a degree, college and university leaders should ask themselves what education must become in a world where both manual and cognitive work are being transformed. AI is not removing the need for people, but it is raising the price of entry. And if technology is raising the price of entry, education has to lower it.

In many ways, we have been here before. Mechanized agriculture reduced the labor required to grow food. Industrial machinery multiplied factory output while again reducing labor. Computers slashed the cost of storing, processing and transmitting information.

Each shift increased productivity while expanding access and improving living standards. Food became more abundant, goods more affordable and information more accessible. Each also caused jobs to vanish, disrupting communities and sapping older skills of their value.

But over time, lower costs expanded demand and added value. As agriculture became more efficient, labor and investment flowed into industry, logistics and management. As computing spread, value moved into software, systems, design and analysis.

AI will likely follow the same arc. It is a multiplier, not just a replacement.

According to the Federal Reserve, AI adoption has yet to reduce overall job postings, at least in the aggregate. But the path toward stable, upwardly mobile work is narrowing. As that happens, the skills required to enter the workforce will become more demanding. As the number of traditional entry-level roles shrinks and employer expectations rise, workers will now be expected to add an ever-growing amount of value on day one.

Today, the workers most likely to be squeezed out will be those with the least room for error: first-generation students, career changers, adult learners, and anyone trying to move into the middle class. If technology accelerates productivity while narrowing access, the result will be a labor market more rewarding for those already prepared and less forgiving for everyone else.

My grandfather understood this long before artificial intelligence entered the public conversation. He immigrated to the U.S. alone with little to his name beyond determination and the electronics repair skills he had learned in a vocational program. Those skills gave him a foothold in a new country and, over time, the opportunity to rebuild his life.

Years later, he founded an institution designed to do the same for others. In 1966, it began as the Electronic Computer Programming Institute, created to prepare workers for what was then an emerging computer industry.

Career preparation cannot be an afterthought. Return on investment is part of the bargain institutions make with students, their families and taxpayers. 

Programs should align with where the labor market is going, not with where it has been. They should connect to real workforce demand, teach transferable skills and equip graduates for evolving careers. The old sequence of earning a degree, getting hired, and then learning the real work on the job is becoming less reliable. Institutions need tighter feedback loops with employers, faster program updates, and more opportunities for internships, apprenticeships, and project-based work that help students graduate with proof of capability, not just a credential.

The market will increasingly reward so-called “T-shaped” graduates: people with depth in one field and breadth in the human skills that machines still struggle to replicate.

As routine cognitive work becomes cheaper, the premium on skills like judgment, communication, creativity, and ethical reasoning will rise. AI literacy is also quickly becoming a differentiator. As companies learn where these tools create real value, workers who can use them thoughtfully will have an advantage.  

Even as AI disrupts the entry-level pipeline, employers know they cannot abandon it completely. Companies that stop hiring and developing early-career talent may save money in the short term, but they risk starving themselves of future managers, specialists and leaders. It is higher education’s job to sustain that pipeline and to demonstrate to employers that early-career talent still delivers value.   

There may well be an age of abundance ahead. But abundance does not guarantee access or economic mobility. The goal should not be to create a world where a select few hold extraordinary tools, but one where many can use them to shape an extraordinary future. If AI can put more on the table, education must make more seats at it. That is real abundance. 

Sam Dreyfus is executive vice president at ECPI University.

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