AI Won’t Replace Educators. But It is Changing How Students Learn.

Recently, my kindergartner climbed onto the scale and asked me what dinosaurs also weighed 50 pounds. Thanks to Claude, we quickly learned, to my son’s delight, that he is the size of a juvenile velociraptor.

Artificial intelligence helped me with a question I couldn’t have answered on my own. But it didn’t replace me as a parent or my son’s role as a learner. A few weeks later, I had forgotten the answer, but my son didn’t. He was the keeper of knowledge, and I was the conduit.

Something like this is happening in schools and colleges, too. Information is more easily accessible than ever before. Anyone anywhere can ask an AI tool a question and receive an answer that seems reasonable, at least on the surface. It’s not surprising, then, to see predictions of the demise of traditional schools and colleges.

But education has never been only about access to information. Students need much more to become capable members of society. They need the ability to assess the quality of information, recognize strong work, and connect ideas. Students also need to grapple with the reality that not everyone agrees, and that’s ok. This kind of learning requires human relationships that expose students to the friction of life that sycophantic AI models tend to obscure.

The big question is how to know when AI supports real learning and when it leads to the “cognitive surrender" of accepting AI-generated answers with minimal scrutiny. Recent research findings shed some light on that.

Learning by AI Type

First, learning varies significantly based on the type of AI used. The dangers of cognitive surrender are greater when students use the standard, free versions of LLMs. Those models are designed to be helpful and therefore simply provide answers to the questions they are asked. Brain activity and retained learning are lower when students are working with AI in this way.

In contrast, tools that scaffold learning and support in-person instruction can produce outcomes even more impressive than my son’s memory of the size of teenage dinosaurs. One study of an introductory undergraduate physics course found that students using a carefully designed AI tutor had twice the learning gains of those receiving active, in-person instruction.

Learning Process Matters

Second, the role that AI plays in the learning process matters, and it should be off-limits at times. The authors of the physics course study cautioned that structured AI tutoring may not be appropriate for tasks “requiring complex synthesis of multiple concepts and higher-order critical thinking.” In a larger-scale example, Estonia’s education minister—who is overseeing the country’s ambitious partnership with OpenAI to provide a custom AI platform in upper secondary schools—has described a blended model. Students use handwriting to form memories early in the learning process and, later, use digital tools for feedback and AI-assisted learning. Estonia is not introducing AI in earlier grades so that students can build foundational knowledge and skills first.

Support for Educators Needed

Third, because the outcomes are so far apart between good and bad AI use in learning, educators need support to add AI to their teaching toolkit responsibly. In one study from Sierra Leone, secondary school educators completed a one-day training before adding AI tools in the learning process and only then saw math learning gains equivalent to more than a year of additional schooling.

Google, OpenAI, and Anthropic all offer learning modes and other supports built on these ideas. Still, those features are typically opt-in and getting harder to find for non-enterprise users. OpenAI, for example, launched “study mode” in July 2025 but quietly removed it from the standard ChatGPT interface this spring. The feature remains available to schools and systems with enterprise contracts. These contracts are expensive but drive demand for the types of AI that educators actually want, especially when leaders collaborate across systems and make similar asks of tech companies in procurement.

Schools, colleges, and educators should not be alone in navigating these waters. Philanthropy can help, for example, by supporting training that respects teachers’ expertise, conducting independent research on what works, and advancing advocacy work that counterbalances the size of tech firms. They can also help make enterprise contracts more affordable and support the development of procurement standards that protect learning, student data, and educational institutions’ sovereignty over their own systems.

This fits with philanthropy’s history of helping the benefits of new learning approaches reach everyone. For example, as compulsory schooling laws were passed at the turn of the 20th century, communities benefited from Andrew Carnegie’s 2,509 libraries (many of which served as classrooms) and Julius Rosenwald’s 5,000 schools that educated a third of Black children in the rural South.

Looking even further back in time gives me confidence that humans can weather tech-driven transitions and come out in a better place. German apprenticeship programs are strong today in part because, during the Industrial Revolution, German guilds adapted their models to fit an evolving economy rather than resisting change outright.

Today’s overflowing supply of information began with the printing press, which expanded access to texts and eventually reshaped who could claim expertise. I can capture and share these thoughts with you in part because, very long ago, writing transformed curriculum, credentialing, and information exchange.

Humans may not be as cool as velociraptors, but we have incredible agency and potential to evolve to meet the moment. All of us—including tech providers, educators, and philanthropy—can play an active role in shaping what’s next for students.