Predictions on how AI will transform K-12 education

From 2 hour learning to AI tutors, here's how school might never be the same

Historically, K-12 schools have lagged behind consumer tech adoption by a significant margin of 10 or more years. Case in point: home computers were prevalent in the 1990s, but widespread adoption of 1:1 computers in schools didn’t occur until the early to mid 2010s.

Will we see this same lag happen with AI? While adoption of AI-based tools will move slower than consumers (factor in cost + licensing + approvals + teacher training) adoption cycles are moving faster than ever before especially with momentum from the pandemic and lower barrier of entry to access consumer tech like AI.

In his article “Make America Smart Again,” Andy Kessler highlights how AI is already reshaping K-12 education:

Actually, AI is already being deployed with great success. One example: The Alpha School, launched in Austin, Texas, has a goal of completely reimagining education. Alpha co-founder MacKenzie Price says, “Students get AI-powered, self-paced learning plans and spend only two hours a day on academics. They learn twice as much in half the time. The rest of the school day is devoted to learning life skills like public speaking, financial literacy, socialization and teamwork.” To do this, teachers become guides, she explains, “doing what humans do best: emotional support, motivation and developing a personal connection to students.” It works. How do we scale this nationwide and then globally?

It's clear AI is already changing the landscape of education, so what comes next?

Here are some of my broad predictions for education in an AI-driven world:

• hyper-personalized learning driven by AI tutors will dramatically accelerate learning. Unlike direct instruction where lessons accommodate the average and weakest students, AI can create individualized lessons with feedback loops at a pace virtually impossible for teachers. I predict we’ll start to see more AI tutors designed to target core subjects, like Synthesis Tutor for math, but also entire school models designed with AI in mind. The 2 Hour Learning model piloted by The Alpha School and implemented in schools across the US is built on the promise that “students learn 2x in just 2 hours a day” and can free up 4 hours of their day to develop life skills and personal interests. AI systems that interoperate will be crucial for creating holistic student profiles rather than fragmented insights from disconnected tools.

• human connection through social and IRL experiences will become essential. If kids only need two hours for core subjects, families and educators will seek human-centered, community-oriented experiences. Similar to the increasing demand for co-working spaces and IRL meetups with the virtualization of work, we’ll see more emphasis on soft skills through outdoor learning, co-learning spaces like Moonrise, makerspaces and entrepreneurial programs, and expanded extracurriculars. Families will naturally cultivate human experiences that AI cannot replicate. We could even see digital detoxes mandated by schools to preserve interpersonal skills.

• public speaking will be used as a key differentiator and indicator of deep understanding. While good writing instruction shouldn't be offloaded to AI, the ability to verbally communicate ideas spontaneously will increasingly qualify deep understanding. Increasingly TED Talks and public speaking courses are part of curriculums for children as young as 6. The Socratic discussion model is becoming a core tenet of schools like Acton Academy, and edtech tools like Parlay are facilitating meaningful, measurable class discussions. Rather than the traditional five-paragraph essay (where AI might do too much heavy lifting), debate clubs and YouTube presentations could become the new gold standard.

• greater access to hands-on and entrepreneurial opportunities, even for younger grades. Seemingly overnight, AI tools have already democratized the ability to build apps, games, and other cool things through “vibe coding” even for those who are non-technical. We’ll start to see more young people embrace building software similar to how they’ve embraced social media and content creation. There will be increased sense of urgency and access to building real things that actually matter and schools will need to adapt to this. More opportunities to participate in incubator programs and prototype a business idea (similar to micro-economy in Montessori), as well as more access to a variety of internships, partnerships with local businesses, and mentorships earlier on in K-12.

• private and elite schools will invest heavily in advanced AI models as a competitive advantage. While traditional private schools may have the best access to funding and incentive to adopt AI as a value prop, they will also face substantial inertia due to reputational expectations and internal red tape. Ironically, this inertia will likely slow their adoption compared to more innovative, nimble schools. As a result, we're likely to see newer, more agile private schools, especially those built from the ground up with AI, training the most advanced AI models to deliver personalized learning experiences. This has the potential to create further educational inequities in the short to medium term, and will likely lead to an arms race as demand for proprietary models skyrocket.

• parents and families will become more integral to a kid’s education (again). Increased access to real-time feedback from AI dashboards will give parents more frequent and tangible insight into their progress. The modular approach to AI platforms = more choice = more à la carte unbundling of educational services. While we may have not cracked the nut on child care just yet, AI’s increased transparency and personalization will allow families to more actively engage by selecting specific courses and enrichment activities, possibly through hybrid approaches or varied learning environments.

So, where does this all lead?

It’s clear that AI is already here in some capacity and that schools across the globe are experimenting with it at varying degrees. This ranges from basic approaches like district-level licensing of Microsoft Co-Pilot and addressing the growing concerns about AI and cheating, to innovative schools that have built entire curriculums around AI. There are lots of questions and concerns around how we use AI effectively and for the most part we’ve hardly begun to predict AI's long-term impact on education.

Will we use AI to help fix some of the large education issues we face today or will the arms race for advanced models widen the gap further? Another big issue to focus on: implementing AI intentionally so platforms communicate with each other to provide holistic rather than fragmented perspectives on student progress. This interoperability is essential before personalized learning can reach its full potential.

At SXSW EDU 2025, Sinead Bovell outlines 3 core pillars we should consider with AI adoption in education:

1. Safe adoption: Teaching students how to use AI safely and responsibly AKA “AI isn’t your friend.”

2. Curriculum adjustments: Knowing that students are using AI at home, prioritizing higher order thinking in the classroom.

3. System redesign: A complete redesign of the system with AI in mind where it can truly be used effectively and intentionally.

“What seems to be happening in this moment is we are kind of merging all of those pillars in a sense of urgency,” Bovell cautioned. “This leads us to deploy AI in schools for the sake of feeling like we need to meet the moment by bringing AI into the classroom. And there are a lot of technologies that aren’t ready.”

As we navigate this critical transition period, thoughtful implementation will be key.

These are just a few of my predictions on how K-12 will change over time, of which I’ll expand on and add to over time. I’d love to hear your perspective on where you see things headed. 🦢