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Key points:
- Career durability depends on fundamentally human skills that give students the flexibility and adaptability to adjust to changes
- Leading with AI and technology in the age of personalized learning
- How districts can build a shared AI structure
- For more news on schools and AI pathways, visit eSN’s Digital Learning hub
America’s schools are moving quickly to respond to the rise of artificial intelligence, with parents, teachers, administrators, and lawmakers working to wrap their arms around what this means for student education.
But regulation that comes ahead of a clear definition of preparedness may set students back in the AI race. For the future of America’s students — and economy — leaders need to first define what the future of career preparedness looks like.
The speed at which education leaders have moved to respond to AI has been nothing short of remarkable. Just a few years ago, there were no states with formal guidance on AI in K-12 education. Today, 34 states and Puerto Rico have issued some sort of AI guidance for schools. More than 70 bills about AI in the classroom have been introduced across 27 states this year alone, as policymakers debate every aspect of AI, from classroom restrictions and student privacy, to graduation requirements and teacher training.
Yet as schools debate every part of AI policy, including who is and isn’t allowed to use it, how they’re allowed to use it, and when they’re allowed to use it, they’re skipping over a more fundamental issue. What do students actually need to learn in order to be successful for the rest of their lives post-graduation?
It’s a question that should fundamentally drive most education policy decisions, especially when it comes to students in the final years of high school and in college. Before schools can determine what students should avoid, they need to first understand what needs to be encouraged based on the demands of employers and the changing business landscape.
This isn’t about letting businesses dictate education policy. We’ve seen industry lead students astray before. The bootcamps and computer science degrees students not long ago were told would lead to higher paying jobs have now fizzled out — a short-term need now rendered obsolete by the advancement of AI.
The mistake we made then was over-indexing on short-term signals. Several years ago, there was high demand for computer engineers, so education leaders gave students one set of skills needed for one defined future.
Then things changed.
The future isn’t set in stone, especially when it comes to dealing with new and emerging technologies like AI. For example: One-third of entry-level jobs now reference AI-related skills, yet students report wildly uneven access to AI guidance and little clarity on which skills will actually matter.
Young people today are expected to change career paths more times than any other generation before them. Instead of looking at education as providing students with the skills they need to go from Point A to Point B, education needs to provide the skills that will take students from Point A to Point E back to Point B, all the way to some point that has yet to be defined.
Training students in things like vibe-coding, prompt-engineering, or model training may answer the business needs of today, but fall short of actual lasting career preparedness.
This isn’t a responsibility that should rest solely on educators to figure out. The best education systems are those that respond to clearly articulated employer demand in a collaborative way that sets students up for long term success.
What we’re seeing in the age of AI is that career durability depends on fundamentally human skills that give students the flexibility and adaptability to adjust alongside technological and workplace demands. Students equipped with skills like judgment and ethical reasoning, problem framing and solving, and critical thinking — in addition to tool fluency and domain knowledge — will be the ones who find success long-term.
How these lessons play out in the final years of high school and across postsecondary education is a task that schools can work collaboratively with employers to figure out. Rather than asking schools to guess what employers want, employers can play an active role in helping them to define it. Community colleges, universities, and workforce training providers are already asking employers these exact questions. The federal government through the National Science Foundation has set up a program designed to help bring business leaders together with education leaders to bring these conversations to life. Similar state programs are taking shape as well.
The goal is not to predict the future. The goal is to define a new standard of preparation that allows students, parents, and educational providers to make the decisions that work best for them.
If the US needs students with new and different skills, it owes students more than warnings. It owes them a clearer picture of what success looks like.
The challenge before the American education system is not simply understanding what technology can do. It is defining what human excellence looks like in a world where technology can do more than ever before. Until that question is answered, policymakers will continue writing rules without first agreeing on the destination.
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