Your briefing this week is thinner on K–12 research related to AI, but there are a few useful items here, especially when you read them through a school leader’s lens.
A report from McKinsey suggests AI could relieve the teacher workload problem that often leads to burnout, and an OECD study shows why that might help retain the best teachers, especially in math and science. Those two sources point to the same two questions:
Who decides if, when, and how AI is employed at school? How do those decisions affect people?
Heads and Boards need to be paying attention to where AI is already shaping decisions at school. Meanwhile, school leaders should be considering how AI’s time savings can be used to make teaching more sustainable and attractive, and ensuring that professional development builds capacity with AI across the whole faculty and not just among a handful of early adopters.
This week I’ve added a Policy Watch section. Policy moves more slowly than research, so this will be an occasional section that looks back further than one week. Laws and publicly available policies are generally written for public districts, but they set the norms that parents will compare independent schools against.
Let’s get to the sources…
1. “Workforce in Motion: Skills and pathways to future jobs in the United States” | McKinsey Global Institute | Ramirez, et. al. | September 29, 2026
The headline numbers are about the whole economy, but there is useful material about teachers, who McKinsey says are in a “low-disruption group” because their work depends heavily on “physical presence, regulation and human interaction.” But teaching is also an overwork case, with teachers working 53 hours weekly vs. 46 for adults in other professions. McKinsey cites a Gallup finding that AI-using teachers save about 6 hours a week.
Takeaway: The near-term question for independent schools is what is done with the time AI frees up for teachers. Teacher workload and burnout are already retention problems, and while recovered hours could go to feedback for students, more time for advisory, or even to increase a teacher’s load of students or sections, it could also be set aside to improve teacher well-being. Leaders need to decide. Note that McKinsey projects office and administrative support roles will be most impacted by AI, replacing 80% of current work hours by 2035. Business offices, admissions, and administrative support are where schools will face real staffing decisions.
Read the report: https://www.mckinsey.com/mgi/our-research/Workforce-in-motion-Skills-and-pathways-to-future-jobs-in-the-United-States
2. “Education at a Glance 2026” | OECD | September 29, 2026
This edition of the OECD’s annual indicators report focuses on teacher shortages. Math and science teachers are the hardest to recruit, and considering that starting salaries for lower secondary teachers average only 61% of what all college graduates earn, let alone what engineers and scientists are paid in industry, the picture for recruiting high quality future STEM teachers looks grim. OECD suggests AI can reduce burdensome parts of the job, and potentially make teaching more attractive, but it is unlikely to make up for shortfalls in available quality teachers.
Takeaway: Independent school leaders need to decide whether to invest in AI as a means to ease teachers’ administrative work, making it a more sustainable and attractive profession. Be cautious of vendor claims that AI can fill your staffing gaps – so far there is little evidence AI can replace the best teachers.
Read the report: https://www.oecd.org/en/publications/education-at-a-glance-2026_b4968bbc-en.html
3. “Teachers report ‘horrendous stress’ after AI used to rate their work” | The Guardian | September 29, 2026
Instructors at a UK apprenticeship and training company told the Guardian that an AI system now evaluates their online lessons and alerts managers if it finds weaknesses. AI give classes scores and assigns each teacher a “risk status.” The company says only humans write performance reviews, but instructors told the Guardian that managers challenged them over AI-flagged “mistakes” in their courses that were actually responses to what learners needed. Instructors described losing sleep, seeking therapy and feeling under continuous scrutiny.
Takeaway: This is the first widely reported case of AI being used at scale to evaluate teaching. Be aware that vendors will attempt to bring the same capability to independent schools: lesson transcription, “instructional quality” scoring, classroom analytics, etc. Just because a human signs off on a final review won’t mean professional judgment has been employed or that the reviews are accurate. And teachers will not respond well. A scoring rubric can’t tell a digression from the lesson plan from a teacher making an expert judgment to pivot for a student’s need. In a true growth-oriented evaluation model, AI may inform teachers’ own reflection but should not become a surveillance tool.
Read the story: https://www.theguardian.com/technology/2026/sep/28/teachers-euan-blair-firm-report-horrendous-stress-ai-used-to-rate-their-work
4. “How private schools can manage AI risks” Q&A | Rochester Business Journal | October 1, 2026
This is an interview with two executives at information security and insurance companies that serve private / independent schools. They highlight the risks of entering student, family, donor or financial information into AI tools. Schools may have vetted and approved software, but staff often use “shadow AI” without approval. They liken AI oversight to cybersecurity risk and recommend that schools should adopt protocols to help staff determine when and how AI can be used.
Takeaway: independent schools currently have AI risk whether or not they’ve decided to “adopt AI” – staff are using chatbots. Boards’ audit and risk committees should be involved in setting and overseeing policy, and Heads should inventory how much AI is already being used in various systems including SIS, LMS, and finance platforms. Require approval and verification of continued AI use.
Read the Q&A: https://rbj.net/2026/10/01/private-schools-manage-ai-risks-rochester/
Policy Watch
A consensus is forming in public opinion and policy that high-stakes decisions, especially discipline, assessment and grading, should mostly be done by humans. Admissions offices and Heads should expect families to ask whether their school meets that standard.
- D.C. AI policy for school staff (Sept. 1): adoption of a stoplight framework – a “red” category prohibits AI for high-stakes decisions requiring human judgment, including student discipline and teacher evaluations. Grading is “yellow,” allowed with safeguards. Lesson planning and communications are “green,” allowed with human review. https://osse.dc.gov/release/osse-releases-ai-model-policy-guide-responsible-staff-use-schools
- Maryland (July 9) now requires an AI coordinator and staff training at schools. Oklahoma prohibits using AI primarily for grading and discipline and lets parents opt their children out of interaction with AI at school without penalty. https://www.k12dive.com/news/4-more-states-require-districts-to-adopt-ai-policies/824749/
- Brookings policy recommendation for student AI councils (Aug. 18): Rebecca Winthrop argues schools should give students real influence over AI decisions, including beta-testing tools, co-designing assignments, shaping policy, etc. https://www.brookings.edu/articles/enhancing-student-agency-through-school-ai-councils/
Mike Gwaltney is a long-time independent school educator and former Head of School. He is Vice President of Consulting and Learning, and a Senior Consultant at Independent School Management (ISM). Mike has been at the forefront of academic technology since the early 2000s and is widely considered the “OG” of blended and online learning in independent schools. He holds a Master’s in Educational Technology, and writes about student agency, teaching and learning, and leadership and governance of AI in independent schools.
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