The Role of Teachers in AI Education

The AI generation has made teaching one of the hardest jobs — and one of the most important jobs — that exist today. We used to worry about giving students too much information — now we worry about getting their attention. Today's students can find answers in seconds — what they need help with is understanding — and putting that information into context — and making good judgments about it. And that is exactly why innovative teaching has become more valuable than ever. Being innovative in teaching does not mean you have to use all of the latest tools. Innovative teaching is about changing how you support your students to think. In the age of artificial intelligence (AI) teachers are no longer simply providers of knowledge. Teachers will act as guides — as filters — and as sense makers. If AI can provide explanations for concepts, then the teachers' role changes to supporting students to develop the skills to ask better questions — to challenge their assumptions — and to apply the ideas in the real world. Innovative teaching will move away from the student memorizing and toward the student interpreting. Away from asking "What is the answer?" and toward asking "Why does this matter?" Away from being passive listeners and toward being active problem solvers. While AI can provide personalized content — teachers can provide personalized meaning. Students should be encouraged to explore, to debate, and to be curious. Students should be allowed to use AI — but students should be taught how to analyze the output of AI, to question the logic of AI, and to understand the limits of AI. That is real digital literacy. As such, innovation is also about embracing creativity. To use real-world examples. To promote collaboration. To allow students to fail while still learning. To create environments that allow students to think aloud — and not just to do things correctly. Most importantly, innovative teaching is uniquely human. Empathy, encouragement, and inspiration cannot be replicated by algorithms. A teacher who develops relationships with students, understands their challenges, and believes in their capabilities — that is an influence that no algorithm can replace. In the AI generation — the best teachers will not compete with technology — instead, the best teachers will teach their students how to think with technology. Because the future does not belong to those who have the most knowledge — the future belongs to those who can continue to learn, adapt, and think critically — over and over again. - Nataraj Sasid

I was on CBS News Chicago yesterday as part of their "Eye on AI" series to talk about what we're seeing in schools right now. Towards the end a Zoom notification made a guest appearance on my face for about ten seconds - proof that you can help people navigate emerging technology everyday and still get taken out by a pop-up. Fortunately, it takes a lot more than that to keep me from talking about AI and education. We covered a lot of ground in a short segment, but three things stood out: 1. It starts with teachers and leaders. The first question was about how we're tackling AI adoption in schools. I shared that before we ever get to students, we work with teachers and leaders to build confidence — not just with the tools, but with the ethica that l adoption of these tools. No one is an expert on AI in education yet. We're all learning together, and that means focusing on limitations just as much as opportunities. 2. The "cheating" narrative needs to go. We talked about one of the biggest misconceptions in education right now: that AI is only for cheating. Students are internalizing that message, and it's leading to two negative outcomes. Some are hiding their use, with no support or training, which can affect not just their schoolwork but their mental health and wellbeing. Others are avoiding AI entirely, even as they head into college and careers where these skills will matter. We need transparency and real discussions, not fear. 3. AI can do more than just save teachers time. Finally, we got into how teachers are actually using AI. In our experience, intentional, AI-literate use doesn't necessarily save teachers a ton of time. But it means teachers are upgrading instructional materials, supporting diverse learners, and getting back to the work they love most — building relationships and helping young people find a love of learning. Overall it was a great segment and thanks to the CBS team who also shared AI for Education's new free student AI literacy course and our guide for parents (links in the comments if you want to check them out). #aiforeducation #ailiteracy #techfail

AI is reshaping the future of learning, not by replacing educators, but by amplifying human potential. I just read Google’s new position paper on 'AI and the Future of Learning', and several points resonate strongly with my own experiences in e-learning, agentic AI, and responsible innovation. Key takeaways for educators, learning designers and AI practitioners:- 1. Human-in-the-loop matters:- AI should empower teachers and learners, not supplant them. Educators remain central in designing, customizing, and supervising AI tools. 2. Personalized, adaptive learning:- AI can meet learners where they are, adapt to their pace, strengths, and needs, especially powerful in large scale or resource-constrained settings. 3. Ethics, fairness, transparency:- Tools must be built responsibly, transparent about data usage, bias, and decisions. Learners, teachers, and their families should understand how AI arrives at suggestions and always have recourse. 4. Skills for the future:- Beyond knowledge recall, education needs to foster curiosity, metacognition, collaboration, and lifelong learning. AI becomes a partner in cultivating how we learn, not just what we learn. As someone who leads e-learning and agentic AI initiatives (and working on courses / frameworks for learning system design), here are some reflections:- 1. Design with pedagogy first:- When building courses or tools, we must anchor in learning science and best practices. Agents or AI modules should align with what we know about how people learn, including cognitive load, scaffolding, and feedback loops. 2. Build with practitioners:- Co-design with educators ensures the AI tools remain grounded in context, and helps avoid misalignment or unintended biases. 3. Measure impact holistically:- Beyond completion or test scores, we should evaluate growth in learner agency and self regulation, especially for adult learners or professionals. 4. Scale responsibly:- The potential for scaling personalized learning is huge, but we must not lose sight of the social, cultural, and equity aspects of learning design. 🧭 In my upcoming course on Augmenting Collective Intelligence via Autonomous Agents + Human Experts, I'll integrate several of these insights:- embedding AI tutors in training, designing feedback loops, and ensuring alignment with ethical & pedagogical frameworks. 💡 Question for my network:- How are you balancing AI tool adoption in education or training environments while preserving educator control, equity, and learner agency? Would love to hear your experience or frameworks that are working. #AI #EdTech #LearningDesign #AgenticAI #LifelongLearning #InstructionalDesign #AIgovernance

AI is revolutionizing education, but can it really replace teachers? Data says no. Studies show that while AI can personalize lessons and automate grading, it lacks the empathy, adaptability, and inspiration that human teachers provide. According to a 2025 World Economic Forum report, teaching remains one of the least automatable professions. Teachers don’t just deliver information-they mentor, motivate, and build real connections with students. AI can be a powerful tool in the classroom, but it can’t replace the human touch that sparks curiosity and growth. The future isn’t about AI replacing teachers, but about AI supporting teachers to help students thrive.

Most research on AI in education are written by people who do not teach. This was conducted by people who asked teachers what they actually need. A national survey of 349 K-12 teachers across Indonesia, submitted to arXiv, reports three concrete barriers to using AI in classrooms: generic outputs that miss local context, infrastructure constraints, and limited alignment with Indonesian educational frameworks. The survey asked teachers which work they actually wanted help with. The answer was instructional preparation: lesson plans, marking, parent communications. The paperwork that takes time away from teaching. The findings are specific. Elementary teachers showed more consistent AI adoption than senior high teachers. Mid-career educators ranked AI tools as more important than younger or more senior peers. Teachers in Eastern Indonesia, where infrastructure constraints are highest, perceived the most value when access was available. The vendor pitch on AI in education has been consistent: AI tutors, personalised learning at scale, the teacher as a facilitator of an AI-led classroom. These teachers are saying something different: help us with the prep, build for our context, solve the connectivity problem first. Build for the teacher who is actually in the room. Stop building for the teacher in the pitch deck. Paper: https://lnkd.in/e5UjFFpC #AI #HigherEducation #EdTech #AIliteracy #SlowAI

In the GenAI era, it’s tempting to treat learning as something that can be automated—summarized, streamlined, and packaged into slides or chatbot replies. But real understanding requires struggle, dialogue, and time—especially for those just starting out. Across many classrooms today, there is a noticeable mismatch between expectations and outcomes. Learners, relying heavily on AI tools and meeting only the minimum level of engagement, are often puzzled when their work falls short of excellence. This is a reflection of a deep misunderstanding: expertise isn’t earned through minimal effort or through the generation of a perfectly polished AI output—it is developed through sustained engagement, iteration, and learning in community. GenAI is a powerful tool. It can accelerate expression, support reflection, and enhance access to knowledge. But it cannot replace the slow, social, and dialogic process by which deep understanding and wisdom take shape. To students: value your teachers not just as providers of content, but as guides in thinking, questioning, and becoming wiser. To teachers: in this era of instant answers, your role in modeling discernment, depth, and human connection is more vital than ever. What you bring—context, interpretation, and judgment—cannot be replicated by machines. And this matters more now, not less. I’d love to hear your thoughts and see how you make sense of this shift.

I know I'm a little late to the game on this article, but the algorithm reshared it on my feed and I feel a need to comment. As a teacher who has spent almost two decades in a classroom (and as an author writing about AI in education) I can’t help but push back. We all know AI can generate lesson ideas, provide tutoring support, and widen access. I use it almost daily to make learning more accessible and to save time so I can focus on what matters most. But here’s the thing: teaching is not just about delivering “great tutoring.” It’s about trust, relationships, creativity, and seeing the whole human sitting in front of you. My 9th grade students don’t just need information. They need someone who notices when they’re shutting down, celebrates when they take a risk, and reminds them that their voice matters. No chatbot can replace that. So while I believe AI has a profound place in education, it’s not the replacement for teachers. It’s a tool, and like every tool, it’s only as powerful as the humans who wield it. I'd love to hear your thoughts on this: Is Gates underestimating the human side of teaching, or am I overestimating it? Link to original article: https://lnkd.in/em6D9dwW

If teaching is the backbone of a nation, why do our brightest minds avoid it? Ask a topper about their dream career—how often do you hear “teacher”? We speak passionately about innovation, AI, startups, and becoming a developed nation. Yet one critical question remains unanswered: Who is choosing to teach the next generation? Globally, only a small fraction of high-performing students see teaching as their first career aspiration. Teaching is widely acknowledged as meaningful—but rarely seen as aspirational. This gap should concern every education leader and policymaker. So why does teaching still struggle to attract top talent? The challenge is not lack of purpose. It lies in how the profession is structured and perceived: • Teaching is often evaluated by hours, compliance, and paperwork, not intellectual contribution • Pay, growth, and recognition rarely match the depth of qualification required, including a PhD • Administrative overload overshadows research, mentoring, and innovation • Social prestige has not kept pace with the profession’s societal impact Now, a new dimension is entering classrooms: Artificial Intelligence. AI has the potential to transform teaching dramatically—by automating routine tasks, enabling personalized learning, supporting assessment, and freeing teachers to focus on mentorship, creativity, and higher-order thinking. If used wisely, AI can shift teaching from content delivery to knowledge facilitation and leadership. This raises an important possibility: Could AI make teaching more intellectually rewarding and attractive for future aspirants? But this will only happen if educators are empowered—not replaced. AI should elevate the role of teachers as designers of learning, critical thinkers, and mentors, not reduce them to supervisors of machines. Which brings us to the larger national question: How can a country aspire to be developed if many of its brightest minds opt out of teaching and knowledge creation? The real corrections must be structural: • Redefine teachers as knowledge creators and learning leaders • Create clear academic, research, and leadership pathways • Restore professional autonomy and trust • Measure impact, not just attendance or working hours Who is responsible? Policy makers, institutions, regulators, and education leaders—all of us. Passion alone cannot compensate for systemic neglect. If we truly want innovation, leadership, and sustainable national progress, the question is not only how we teach students—but why the best minds should want to become teachers in the first place. Teaching is not a 9–5 job. It is a lifelong engagement with knowledge, youth, and the future. AI can amplify this mission—but only if we redesign the profession with respect, vision, and trust. Would you encourage your brightest student to choose teaching today? #FutureOfEducation #TeachingProfession #EducationReform #AIinEducation #NationBuilding #LeadershipMatters #HigherEducation

Schools need to focus on AI life skills in teaching and learning. Teaching artificial intelligence in education largely centers around making sure students and teachers know about AI—what it is, how it works, which tools to use, and how to fact-check responses. These AI-literacy skills are important, but if we only teach about AI we miss a critical opportunity to practice enhancing our human abilities with AI. In addition to just knowing about AI, students need to practice using AI to think deeper, create better, and solve problems more efficiently than they could on their own. Many schools have created portraits of a graduate - frameworks that articulate the durable skills students should have by the time they graduate (beyond the subject-area knowledge about math, science, history, etc). Adopting that approach, I’ve created a "Profile of an AI-Ready Graduate,” which was shared at the recent #ISTELive and #ASCDAnnual conference. It identifies six core roles students should be comfortable taking on–with AI–to maximize their human potential. ✴️ Learner Students know how to use AI to set learning goals, create plans for learning new skills, identify strategies to get unstuck, and seek targeted feedback to improve performance and understanding. ✴️ Researcher Students know how to use AI to investigate and analyze topics, evaluate claims, and compare sources of information. ✴️ Synthesizer Students know how to use AI to synthesize, remix, and refine information into formats and levels of complexity that best meet their unique needs and capabilities. ✴️ Ideator Students know how to use AI as a brainstorming partner to generate new ideas and explore a wide range of possibilities. ✴️ Connector Students know how to use AI to increase human collaboration, including overcoming language barriers, and finding common ground among divergent perspectives. ✴️ Storyteller Students know how to use AI to present and communicate complex ideas through text, image, audio, video, and other media. The Profile of an AI-Ready Graduate provides a roadmap for helping students learn to use AI to enhance and build on their uniquely human capabilities. By modeling and teaching the key roles students will be expected to take on, we can better prepare them for a world in which AI will be increasingly integrated into their lives. There is no question that students need to learn about AI. But to thrive (and survive) in a AI-powered world, they also need to know how to work with AI creatively, thoughtfully, and strategically. We must shift the conversation from one of basic theoretical understanding to one of in-depth practical and creative applicability. Anything less would be limiting their future success. ISTE ASCD Anthony Rebora Joseph South

Microsoft Education has just released its 2025 Artificial Intelligence in Education report - a global snapshot of how AI is shaping learning, leadership, and future-ready skills across K–12 and higher education. A few key insights resonate with me, with the final one surely essential: * 𝐀𝐈 𝐢𝐬 𝐢𝐧 𝐜𝐥𝐚𝐬𝐬𝐫𝐨𝐨𝐦𝐬, 𝐛𝐮𝐭 𝐜𝐨𝐧𝐟𝐢𝐝𝐞𝐧𝐜𝐞 𝐢𝐬 𝐥𝐚𝐠𝐠𝐢𝐧𝐠. While 86% of institutions report using generative AI, fewer than half of educators and students feel confident navigating it. AI fluency is quickly becoming as essential as digital literacy once was. * 𝐒𝐭𝐮𝐝𝐞𝐧𝐭𝐬 𝐚𝐫𝐞 𝐭𝐡𝐢𝐧𝐤𝐢𝐧𝐠 𝐛𝐢𝐠𝐠𝐞𝐫 𝐰𝐢𝐭𝐡 𝐀𝐈. Tools like Copilot empower learners to brainstorm, reflect, and expand ideas - especially when combined with peer collaboration and thoughtful instructional design. * 𝐀𝐈 𝐚𝐦𝐩𝐥𝐢𝐟𝐢𝐞𝐬, 𝐧𝐨𝐭 𝐫𝐞𝐩𝐥𝐚𝐜𝐞𝐬, 𝐭𝐫𝐚𝐝𝐢𝐭𝐢𝐨𝐧𝐚𝐥 𝐥𝐞𝐚𝐫𝐧𝐢𝐧𝐠. From reading comprehension to writing, AI is most effective as an assistant that supports deep learning rather than a substitute for it. * 𝐄𝐝𝐮𝐜𝐚𝐭𝐨𝐫𝐬 𝐚𝐫𝐞 𝐞𝐦𝐛𝐫𝐚𝐜𝐢𝐧𝐠 𝐀𝐈 𝐭𝐨 𝐫𝐞𝐜𝐥𝐚𝐢𝐦 𝐭𝐢𝐦𝐞. By reducing lesson prep, supporting differentiated instruction, and streamlining administrative tasks, AI helps teachers focus on what matters most: relationships and pedagogy. * 𝐄𝐪𝐮𝐢𝐭𝐲 𝐦𝐮𝐬𝐭 𝐠𝐮𝐢𝐝𝐞 ��𝐈 𝐚𝐝𝐨𝐩𝐭𝐢𝐨𝐧, 𝐧𝐨𝐭 𝐡𝐲𝐩𝐞. Early data suggests AI isn’t widening socioeconomic gaps, but inclusive access, scaffolding, and diverse representation in tool development remain critical. * 𝐀𝐈 𝐬𝐤𝐢𝐥𝐥𝐬 𝐚𝐫𝐞 𝐛𝐞𝐜𝐨𝐦𝐢𝐧𝐠 𝐜𝐚𝐫𝐞𝐞𝐫 𝐜𝐮𝐫𝐫𝐞𝐧𝐜𝐲. With 66% of employers unwilling to hire without AI literacy, students must learn to lead with AI, not just use it. * 𝐓𝐞𝐚𝐜𝐡𝐞𝐫𝐬 𝐰𝐚𝐧𝐭 𝐭𝐫𝐚𝐢𝐧𝐢𝐧𝐠 - 𝐚𝐧𝐝 𝐭𝐡𝐞𝐲 𝐦𝐞𝐚𝐧 𝐢𝐭. High-quality, contextual, job-embedded professional development is non-negotiable. This can’t be another “figure it out as you go” initiative. * 𝐒𝐭𝐮𝐝𝐞𝐧𝐭 𝐯𝐨𝐢𝐜𝐞 𝐢𝐬 𝐞𝐬𝐬𝐞𝐧𝐭𝐢𝐚𝐥. Young people want to shape how AI is integrated into their learning. Let’s co-design the future with them, not just for them. This report is a timely reminder: AI can be more than a time-saver. Done right, it can spark creativity, enhance equity, and help us reimagine learning cultures grounded in agency, curiosity, and care. (Full report can be found in comments)