There is a particular kind of inevitability being marketed to educators right now, and it should make us deeply uncomfortable. The pitch goes like this: AI is coming to classrooms. It's already here, really. Resistance is futile. The only question left is whether your school will be an early adopter or left behind.
This framing appears everywhere. Education conferences feature sessions on "preparing students for an AI-integrated future." Vendors promise efficiency gains. Progressive educators tout personalized learning at scale. The conversation has moved past whether AI should be in schools to how to implement it fastest.
But let's pause. This inevitability narrative is not prophecy. It's sales strategy.
The uncomfortable truth is that many technological "inevitabilities" in education have come and gone. Remember when every classroom needed a smartboard? When tablets would revolutionize learning? When MOOCs would upend higher education? These weren't inevitable. They were choices made by administrators, often influenced by vendors with financial interests. Some choices worked. Many didn't. Many wasted resources that could have gone elsewhere.
The AI moment feels different only because the technology is genuinely powerful and the venture capital behind it is genuinely massive. That doesn't make it inevitable. That makes it well-funded.
Here's what genuinely concerns me: we're not having the harder conversations while there's still time to shape how this unfolds. Where will the data go? Who owns it? What happens when an AI system perpetuates the same biases that already exist in education, but now at algorithmic scale? How do we ensure that personalization doesn't mean surveillance? What happens to teachers whose roles are redefined without their input?
These questions deserve answers before implementation, not after.
The global dimension matters here too. Wealthy nations can afford to experiment with AI tools, make mistakes, and adjust course. They can hire specialists to audit algorithms. They can push back against vendors. Developing economies often can't. When educational technology is sold as inevitable, poorer countries get pressured into adopting systems designed elsewhere, with training that's inadequate, support that's nonexistent, and contracts that benefit foreign companies far more than local students.
There's also something troubling about how AI adoption discourse treats the teacher. The pitch often frames AI as a solution to teacher shortages or as a tool to handle the administrative burden so teachers can focus on relationships. Fair enough. But the actual deployment often treats teachers as implementers of predetermined systems rather than professionals with expertise worth consulting. In many proposals I've seen, teachers become monitors of AI outputs rather than designers of learning.
We should be asking: What problems are we actually trying to solve? Are those problems genuinely unsolvable without AI? Who benefits from framing their adoption as inevitable rather than optional?
I'm not arguing against exploring AI in education. Exploration is healthy. Pilots are fine. But pilots are different from inevitability. Pilots are humble. Pilots expect to learn what doesn't work. Inevitability shuts down that questioning.
The strongest education systems in the world succeed because they invest in teachers, small class sizes, time for professional development, and community engagement. These things require sustained funding and political will. They're not glamorous. They don't generate venture capital returns. So it's worth asking whether "inevitable" AI adoption becomes the reason we never properly fund what actually matters.
Technology is a choice. How we deploy it is a choice. Who gets consulted is a choice. The framing of these choices as inevitable is perhaps the most consequential choice of all.
It deserves more skepticism than the current moment allows.