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If this episode makes you think, please let us know in the comments and support us by subscribing and leaving a review. Thank you. Today we are exploring a special report titled AI in Education by Jamie John, published in USA Today via Reuters on July 24, 2026, which looks at how AI labs are starting to really muscle in on the education market. Now, what really jumped out at me right away in this piece is the sheer scale of the opportunity these companies are eyeing. According to a report by Morgan Stanley that the article cites, the global education market was valued at a staggering $6 trillion in 2022. That's a massive number, isn't it? It just underscores why the world's biggest AI builders are now so keen to get involved with schools and universities. It really feels like we've seen an evolution, not a revolution. It's in how schools have responded to AI. The piece makes the point that from the moment OpenAI's chat GPT burst onto the scene in 2022, many schools and universities were playing catch up. I remember it well, don't you? There was that initial instinct for many educators to ban AI tools outright. And I get it. There was a fear of the unknown, a concern about academic integrity, and and quite frankly, a lack of understanding about what these large language models actually were and could do. But as the article highlights, educators quickly realized that these tools had become a fact of life. You can't put the genie back in the bottle, and honestly, why would you want to? So now we're grappling with how to genuinely prepare students for a world that's being transformed by this technology. That's our job, isn't it? Not to outsmart the machines, but to teach students to outthink them. Now here's where it gets really interesting. The article points out that the world's top AI builders are no longer just letting us educators figure it out for ourselves. They are actively getting in on the action. And this is the shodden first imp thing I think teachers should know about this report. There's a significant push from major AI labs to provide specific AI tools for educators. For example, Anthropic has just launched Claude for Teachers. This is a free tool aimed at K12 teachers in the US and its whole purpose is to help with lesson planning, creating assignments, and even providing automated reports on students. Similarly, OpenAI has ChatGPT for teachers, which is also a free self serve offering for verified K12 teachers and staff in the US. They also have ChatGPT.edu, a discounted enterprise subscription for universities and of course, Google, a long standing partner for many schools, has its own suite of tools built around its Gemini models, targeting both teachers and students. What this tells me is that these companies are not just throwing generic AI at us anymore, they're starting to understand the specific needs of the classroom. When I hear about tools designed for Jackbo AI lesson planning or generating reports, what immediately comes to mind is that core philosophy of outsource your doing, not your thinking. These are exactly the kinds of repetitive, time consuming tasks that AI can handle, freeing up teachers to do what machines cannot, wonder, care, judge, build relationships and spark imagination. Imagine a year nine science teacher who can now draft three differentiated lesson plans for the same complex topic in a fraction of the time simply by leveraging CLAUDE for teachers. That's not replacing the teacher, that's augmenting their capacity for creativity and care. It's about giving teachers back their time, their focus, their energy to genuinely connect with students. The Laxcom second significant takeaway from this report is how these major AI labs are framing their involvement. While Simon Buckingham Shum, a professor of learning informatics at University of Technology, Sydney, rightly points out that AI is absolutely a marketplace for these companies and we shouldn't be naive about that. Leah Belsky, OpenAI's vice president of education, says there's an imperative for them to help shape how students use the technology. This is why OpenAI has its education for Countries program already working with Estonia, Greece, Jordan, Kazakhstan and others to bring customized versions of its chatbot into classrooms tailored to local pedagogical styles. The goal, according to Belsky, is to personalize learning and prepare students for the workforce. This brings us directly to a key concern that the article touches on, and one that I know is on the minds of many educators. The fear that this technology, with its instantaneous responses, could reduce the productive struggle that helps students learn. This is a very valid concern. If a student can just get an immediate answer, what happens to the process? What happens to the critical thinking? This is where our human in the loop principle comes in and where we need to teach students not just to use the tools, but to think with them. The report notes that both OpenAI and anthropic espouse a Socratic approach to learning, turning chatbots into tutors that guide critical thinking rather than just spitting out answers. For instance, Anthropic's Claude for Education, intended for university students, includes a learning mode that asks, how would you approach this problem instead of just providing solutions? This is precisely the kind of IOI in Education report COG Insight we need to lean into. It's about design and learning that cannot be faked because it demands depth, care and imagination where the real value isn't in what the machine produces, but in how the student responds, evaluates and transforms that output. We need to foster AI literacy not as a technical skill, but as a collaborative reasoning ability, managing AI conversations with precision, understanding its limitations, and developing reflective awareness. If you're finding these insights helpful, remember to hit that follow button so you don't miss future episodes on AI in education. The uotherdoc thing I want to highlight from Jamie John's article is the broader picture for school leaders and the current state of institutional adoption. Microsoft and Google are integrating their AI tools, Co Pilot and Gemini, respectively, into their existing education offerings, building on those long standing relationships with universities and schools. This could be a threat to incumbent edtech companies, but for the most part the article suggests they're choosing to partner with the frontier AI labs. Michael Feldstein from the education consortium SAMO EdTech notes that EdTechs are nervous and afraid that the labs are going to make them obsolete, but they also have valuable data on patterns of usage that the AI labs don't. It's a fascinating dance of collaboration and competition, but despite all this effort, the report finds that adoption of AI at the institutional level has been surprisingly slow. A recent study by the Digital Education Council found that over 40% of students in higher education said AI hadn't been integrated into any of their courses. And for those whose courses did use AI, 42% said it was only somewhat helpful, with 24% reporting limited learning benefit. This tells us something crucial about change leadership in schools. Teachers are often labeled resistant, but often they just need time and space anchored to existing, successful practices, not novelty. We need to empower teachers as change agents, build from strengths and ensure we're measuring student outcomes and teacher well being, not just tool adoption rates. It's a classic know like trust progression, building awareness, then credibility, then confidence. You can't skip stages. There's also an open question about the commercial viability in the long term. Feldstein asks whether schools will want to pay for top chatbots when adequate models might run on their devices for free. Referring to open weight AI models, this point speaks to the aligned step in the 7 Lessons for AI Adoption framework. Customizing for your institutional context. Some universities, like the University of Technology, Sydney, Australia, are already taking matters into their own hands, with instructors building their own AI products and an internal quality assurance process. This is the kind of empowering approach I love to see giving design tools into the hands of educators. It's about focusing on purpose over technology, asking what learning goal we're trying to achieve, and then thoughtfully considering the best tool for the job, whether it's bout chatgpt for teachers, anthropics claude for teachers, or something homegrown. Ultimately, this report paints a picture of a rapidly evolving landscape with powerful external forces. The big AI labs enter in the education space with specific AI tools for educators, but it also reminds us that the real value, the real transformation will come not from the tools themselves, but from how educators thoughtfully, critically and purposefully integrate them to enhance human capability, protect human thinking and deepen learning experiences for every student, especially for that often invisible middle 80%. We need to empower educators to experiment, to question and to design learning that leverages AI to hold the complexity so we all have capacity for creativity. That's all for today. Thanks for listening.