As always, it has been a busy few weeks in “Education and AI Land.” Here is a snapshot of what I want to remember, and for you to know!
Top of Mind
In the days following CEC, the follow-up conversations have been just as telling as the hallways chats we had in person. What is emerging is not a single question about AI in education, but a set of very different needs depending on where people sit in the system.
Researchers are asking a sharper question than I expected. Not “Does this tool work?” but “What do we see changing?” There is a growing interest in identifying immediate, observable shifts in teaching and learning rather than waiting for long-term studies tied to specific platforms. That is a meaningful shift in how evidence may be defined in this moment.
Consensus right now is that we have a lot of work to do before we even decide which tool matters most.
Leaders are reaching out with a different kind of request. They are not asking for a list of tools. They want structured ways to engage their teachers in co-design. There is real interest in creating space for educators to name problems of practice and build solutions together. If that is something your organization is exploring, we are actively supporting this work through the AI and Education Studio. You can connect with us here: https://aiandeducationstudio.com/connect
Families are raising questions that are often missing from broader conversations. Several reached out asking how AI might support students managing long-term health conditions. Not as a replacement for care or even having much to do with the health condition itself, but as a support for continuity in learning, organization, and communication. We are actively working on a resource in this area and will be sharing it soon.
Policy leaders are trying to determine what comes next. There is growing attention to state-level activity, including recent legislation in Tennessee requiring AI-related policies in education systems. What we are seeing nationally, however, is a disconnect. State guidance around safe and responsible AI use in education is advancing, but the translation into clear, actionable local policy remains pretty invisible if I am being honest.
The gap between state guidance on AI and education and local policies is becoming one of the most important areas to watch.
Taken together, these conversations point to something important. The field is moving past curiosity. Different stakeholders are now asking what this looks like in practice for them, in their role, with their constraints. That is where the real work begins.
Now… on to what we are paying attention to this week.
Microsoft: AI in Education Resource
This Microsoft resource takes a systems-level view of AI in education, with a strong emphasis on institutional readiness, infrastructure, and responsible deployment. What stands out for me is their attempt at bridging technical capability with leadership decision-making, particularly around governance, security, and scalability. The framing is useful for district and system leaders who are moving beyond experimentation and beginning to think about sustained implementation.
At the same time, this resource reinforces a familiar tension to so many of us. Large-scale platforms are advancing quickly, while many institutions are still developing the internal capacity to use them effectively.
Check out the full resource on Implementing an AI Center of Excellence here.
Joe Pulizzi: A Signal About Why Adoption Fails
This short post offers a useful lens for thinking about AI adoption in education systems. The argument he makes in this post is so simple but so important. Important enough that I wanted to highlight this for you — failure is rarely about effort, and more often about lack of clarity, focus, or alignment.
In education contexts, this shows up when AI initiatives are layered on top of existing work without a clear problem of practice driving them. It is a helpful reminder that successful AI integration is less about motivation and more about disciplined design and prioritization.
Read Joe’s full post here.
Stanford SCALE: Understanding the Evidence Base for AI in K–12
This new piece by SCALE provides a much-needed grounding in the current evidence base for AI in K–12 education. I can’t begin to tell you how many times I get into this conversation with our partners and team — does AI make a difference? The question is actually pretty complicated. Rather than overstating impact, the folks at SCALE carefully examined where evidence exists, where it is still emerging, and where claims are outpacing research.
The most valuable contribution is its emphasis on implementation conditions, highlighting that outcomes are shaped as much by context and instructional design as by the technology itself. For leaders and researchers, this reinforces the importance of pairing innovation with rigorous evaluation.
Read Stanford’s full statement here.
Five Principles for Rethinking Assessment with Generative AI
This isn’t necessarily new, but I found myself thinking about it during meetings this week. In this work Leon offers a clear and practical reframing of assessment in the presence of generative AI. The principles move the conversation away from detection and toward redesign, emphasizing authenticity, process, and higher-order thinking. What is particularly useful in this work is the implicit shift in responsibility, placing assessment design back in the hands of educators rather than relying on technical safeguards.
This is just one example of how AI can prompt deeper reconsideration of long-standing instructional practices — but this is an area where quality, purpose, and values all come to light
Read Leon’s full work here.
Ed3 Global: Between Promise and Practice
This newest research brief from Ed3 Global offers a synthesis of what current research actually tells us about teacher adoption of AI, and where the gaps remain. One of the findings suggest that AI use is still concentrated in teacher-facing tasks like lesson planning, with far less visibility into how it shows up in classroom instruction. What we have referred to as efficiency level work. The thing I appreciated most about this is the focus on what we do not yet know, especially the lack of detailed case studies that capture depth of use in practice. Let me be clear that in every single use of AI I have witnessed and experienced with educators, mindsets matter! At CEC last week I drilled into the difference between thinking in hypertext versus hyper thinking. In hyper-text models we were really thinking about connecting specific things. In hyper thinking we are building the capacity to move across ideas, tools, and perspectives quickly, synthesizing them into informed action.
For education leaders, this is an important reminder that the field is still early in our actual knowledge about AI and the next phase of work must move beyond adoption metrics toward understanding in real contexts.
Check out the full research report here.
AI for Education: Multilingual Pedagogy and AI
From our friends at FabAI, a new report brings important attention to multilingual pedagogy as a central, rather than peripheral, consideration in AI integration. This work highlights how AI systems can both support and complicate language access, depending on how they are designed and implemented. The focus on teacher-facing capabilities is particularly valuable, as it grounds the conversation in classroom realities rather than abstract policy. One of the teachers I spoke with at CEC last week is trying to solve this very issue within the context of a tribal community. The wheels are turning and the opportunity is there — this one is an important read if you are thinking about language and AI.
For global education contexts, this is a critical reminder that language inclusion must be intentionally built into AI strategies from the start.
Read the full report here.
Remember that the future of education is being shaped now. We need informed, thoughtful voices to make meaningful choices. Subscribe to Jody’s newsletter for weekly updates as soon as they’re published at https://jodybritten.medium.com/subscribe
