What Should Leaders Redesign First?

A conversation for educators on Microsoft’s 2026 Work Trend Index report, exploring AI agents, human judgment, leadership, and why school culture matters more than individual tool confidence.

Transcript

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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 Microsoft's 2026 Work Trend Index Annual Report called Agents, Human Agency and the Opportunity for Every Organization, with a foreword by Dr. Karim Lakhani of Harvard Business School. It's a big global workplace report built from a survey of 20,000 AI user knowledge workers across 10 countries, alongside Microsoft 365 Productivity Signals and Expertives, and at first glance it looks like a business story. But I think buried inside it is a really important question for schools, colleges and universities. If AI takes on more of the execution, what exactly becomes the work of the human being in front of the class, in the middle office, or around the leadership table? According to the report, the central argument is not just that AI tools are spreading, it's that work itself is being redesigned. And I think that distinction matters a lot because educators have sat through years of technology conversations that were really software conversations, new platform, new dashboard, new shiny thing. But this report is making a bigger claim. It suggests that once intelligence becomes available on demand, the question is no longer simply what tool are we using? The question becomes how are we designing the work? Who does what? What gets delegated? What still needs judgment? What needs care? What needs taste? What needs trust? And honestly, that is such an education question. One of the most interesting findings in the report is that in Microsoft's analysis of more than one hundred thousand copilot chats, nearly half of all conversations, forty nine percent, supported what it calls cognitive work. So not just typing things up faster, but analysing information, solving problems, evaluating thinking creatively. Now, I want to be careful here. That is workplace telemetry, not school-based research. But the underlying idea is striking. We are moving past the old lazy story that AI is mainly about speed. According to the report, many people are using it as a thinking partner, or at least a thinking scaffold. Now pause there for a second. What does that mean for a teacher? Because in education we often talk as though the valuable work is the delivery, the explanation, the mark in, the planning document, the resources. But what if more and more of the value shifts away from producing the first draft of those things and toward deciding what good looks like, what matters most, what this class needs today, and what should happen next? That is a profound shift. It takes us straight into something I come back to again and again. Outsource the doing, not the thinking. The report says 66% of AI users felt AI allowed them to spend more time on high value work, and 58% said they were producing work they could not have produced a year earlier. That rises to 80% among what the report calls frontier professionals, the most advanced AI users in the study. But what really caught my attention was not just the productivity language, it was the language of judgment. The report says the top human skills people now value more are quality control of AI output and critical thinking. And 86% of users said they treat AI output as a starting point, not a final answer. That to me is the whole game for education, because a lot of the fear around AI in schools comes from a very understandable place. We worry that students will stop thinking. We worry that teachers will become over reliant, we worry that the machine will flatten expertise. And all of those concerns are real enough to take seriously. But what the report suggests is that the more mature users are not the ones surrendering their thinking. They are the ones becoming more deliberate about where their thinking matters most. In other words, the future is not human versus AI. It is human judgment becoming more visible, more valuable and more necessary. So what might that look like in a school? Think about lesson planning. A weak use of AI is asking it to generate a lesson and then teaching it as written. A much stronger use is asking it for five possible ways to teach a difficult concept to a mixed attainment year eight class, then using your professional judgment to decide which approach suits your pupils, your context, and the misconceptions you know are likely to appear. The machine helps hold the complexity. You decide the move or take feedback. AI can help produce a first pass on likely strengths and next steps in a set of essays. But the teacher's real value is not the generic comment. It is the pattern recognition, the relational knowledge, the timing, the intervention, the conversation. The real value is not in what the machine produces, but in how the educator responds. And this is where the report gets even more interesting because it argues that the biggest barrier is not actually the individual. It is the organization. According to Microsoft's analysis, organizational factors like culture, manager support, and talent practices accounted for more than twice the reported AI impact of individual mindset and behavior. That is massive. More than twice. In other words, this is not mainly a story about getting every teacher to write better prompts. It is a story about whether the institution creates the conditions where thoughtful AI use can actually stick. Now tell me that doesn't sound familiar in education. How many schools have enthusiastic teachers doing incredible experimentation at the edges while the wider system is still built for compliance, caution, and old measures of performance? How many middle leaders can see the possibility of redesigning planning, assessment, communication, or intervention, but feel trapped by policy, accountability, or just the sheer weight of the timetable? The report has a phrase for a version of this. It calls it the transformation paradox. Workers are ready, their organizations aren't. And according to the report, only 19% of AI users are in what it calls the frontier zone, where individual capability and organizational readiness reinforce each other. 10% are in blocked agency, skilled people inside systems that have not caught up. Half are in the messy middle. That is such a powerful picture for education. Because lots of schools right now are not short of curious people. They are short of coherent conditions. This is why leadership matters so much. Not because leaders need to know every feature of every tool, they don't. But because, according to the report, the job of every leader is now to re-architect work. I really like that phrase. Rearchitect work. Not buy more tools, not issue another policy. Re architect work. For a school leader that might mean asking questions like these. Which parts of planning should remain deeply human because they depend on curriculum intent, local knowledge, and professional judgment? Which parts can be accelerated? Where are teachers duplicate an effort every week in ways AI could reduce? How do we make experimentation safe? How do we share what works? How do we stop innovation, live in private chats, and start turning it into collective capability? Because one of the best ideas in the report is this notion that every firm is becoming a learning system. The organizations pulling ahead, it argues, are not just adopting AI. They are absorbing it. They capture what works, what fails, where handoffs break down, where outputs drift, and then they build that learning back into routines and processes. That is such an important distinction. Adoption is getting the tool in people's hands. Absorption is when the organization itself gets smarter. Schools need that desperately. At the moment a lot of AI use in education is still artisanal. One brilliant teacher has figured out a workflow for adapting texts for multilingual learners. Another has found a better way to build retrieval quizzes. Another is using AI to support parent communication. Another is redesign an assessment so students submit product, process, and performance, not just a final answer. But too often that learning stays local. It sits in one classroom, one department, one enthusiastic person's head. And then what happens? That person leaves, or gets too busy, or burns out, and the learning goes with them. What the report is really pointing toward is the need for owned intelligence, shared know-how that compounds over time. In school terms that means documented prompts, agreed quality standards, example workflows, department reflections, assessment redesign principles, staff development that comes from real classroom practice rather than generic training. It means building systems where teachers can say, here is what I tried, here is where AI genuinely helped, here is where it failed, here is what students still needed from me, and here is how we improve the next version together. Now, there is a tension here, and the report names it well. According to the survey, sixty five percent AI users feared falling behind if they did not adapt quickly, but forty five percent said it felt safer to focus on current goals than redesign work with AI. That tension is alive in schools too. Teachers feel the pressure to keep up, but they are also working in environments where the safest move is often to protect the current system, get through the week, hit the deadlines, and avoid risk. So we cannot just tell educators to innovate harder. That is unfair and frankly a bit lazy. The deeper leadership challenge is to create permission, permission to test, permission to share half formed practices, permission to say this worked in year ten but not in year seven, permission to refine, permission to learn publicly. That is where culture beats slogans every single time. And I think there is one more education angle here that is easy to miss. The report says the most effective users are not those who just do more things faster. They are the ones who redefine their value around outcomes, intent, and design. That should make us rethink what we develop in both staff and students. AI literacy is not just using a chatbot well, it is collaborative reasoning. It is knowing how to direct, question, evaluate, revise, and decide. It is knowing when the machine is useful, when it is misleading, and when the human needs to step in. Teaching students not to outsmart machines, but to outthink them. That has major implications for assessment too. If AI can help generate polished outputs, then assessing only the final product becomes weaker. We need richer views of learning. Process, performance, live explanation, reflection, application. Not because we are trying to catch students out, but because we are trying to value what matters. Can they explain why they chose that idea? Can they defend the judgment? Can they adapt it in a new context? Can they show the thinking behind the output? That is where the human stays visible. So where does all of this leave us? For me, the real message of the report is not that schools need to become more like corporations. Absolutely not. It is that educational organizations need to become more intentional about human agency. If AI takes more of the routine execution, then we have a choice. We can let that create cognitive debt, passivity, and shallow compliance, or we can use it to create more room for judgment, creativity, care, and better design. That is the opportunity, not replacement but enhancement. Not blind adoption but purposeful redesign. Not asking how do we use AI everywhere, but asking where does AI free us to do more of the deeply human work that only educators can do? The mentoring, the noticing, the motivating, the sequencing, the questioning, the sense making, the building of confidence. Machines can compute, they cannot wonder, they cannot care. And perhaps that is the part of this report that stayed with me most. As AI expands, the premium on human judgment rises. I think that is true in business, but I think it may be even more true in education, because education has never been only about execution, it has always been about helping people become. So maybe the challenge for schools now is not simply to introduce AI, it is to redesign work, culture, and assessment in ways that protect thinking, amplify agency, and turn isolated experimentation into collective learning. That is a much bigger task, but it is also a far more exciting one, and that's all for today. Thanks for listening.