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When AI first began gaining traction in education, one rural school district in Wisconsin promptly took action to embed it into classroom instruction. In a district of less than 500 students, AI has become an integral part of how educators are expected to approach their teaching roles. Carter Thompson, an administrator in the district, stresses that the decision was driven by a need to be proactive: “Two years ago… I said we have got to get ahead of the game… so our administrative team met multiple times and we came up with the idea that every teacher had to use AI as a professional goal.”
The district’s push to embrace AI has also been shaped by the context of the community it serves. With a significant English Language Learner (ELL) population and limited financial resources, the district views AI as both a valuable instructional investment and an important equity tool that can help support the needs of its diverse students.
However, district leadership acknowledges that managing AI is a balancing act. As new technology spreads rapidly across schools, there’s a fine line between micromanaging classrooms and taking a laissez-faire approach where teachers are left to figure it out on their own. Overly restrictive rules can prevent educators from adapting AI tools to individual subjects and student needs, but a hands-off approach can lead to inconsistent practices and inequities in how AI is applied in classrooms.
Thompson’s district manages this tension by issuing a high-level mandate while leaving pedagogical execution up to individual teachers. The crux of this strategy is that AI is not optional. “It’s part of educator effectiveness in Wisconsin and part of their teacher evaluation,” Thompson says, explaining how the mandate embeds AI into the very systems used to measure teacher performance. While the district has established AI use as a mandatory professional goal, it doesn’t define a single standardized way for teachers to use AI in classrooms. Instead, district leaders set high-level expectations while trusting educators to determine the best use of AI within their disciplines.
Reclaiming Administrative Control by Stepping Back
The administration’s AI mandate is a form of “structured autonomy,” where leadership establishes top-down guardrails but gives subject matter experts full control over implementation. “I’m not a micromanager. I like to allow our teachers to do their own thing,” Thompson says. “So our math teachers got together, and they decided how they wanted to use AI, and then our English teachers, and so on and so forth.”
This system allows administration to maintain control over AI usage while letting teachers dictate what acceptable use looks like in their unique disciplines, an approach that has proven key to driving uptake in classrooms. When teachers have full command over AI use, they’re empowered to use tools in ways that best fit their subjects and the unique needs of their students.
This teacher-led approach aligns with the broader Wisconsin state policy environment, which is part of a growing majority of U.S. states that have established guidance for AI in education.1 Wisconsin also belongs to a much smaller group of states that treats AI as a form of developmental literacy, requiring a high level of customization that looks different across grade levels.2 Acknowledging that AI use should vary significantly between elementary and high school students, the state provides detailed recommendations to help educators understand and teach AI concepts with age-appropriate scaffolding. Thompson’s district translates this state-level guidance into day-to-day classroom practice through its focus on structured autonomy.
George Walker is a teacher in the district who appreciates this freedom. He explains that AI is heavily used as an equity and inclusion tool, which requires that teachers adapt AI to their specific needs rather than following rigid, one-size-fits-all parameters. For example, teachers often use AI to actively modify lessons for English Language Learners. “When we have English as a second language for a pretty significant portion of our students, they do a lot of translating through AI, which helps quite a bit,” Walker says. He emphasizes how AI supports differentiated learning by “modifying lessons to either make them more challenging for your better students or leveling them down for IEPs [Individualized Education Programs].” AI’s role in supporting learning also extends outside the classroom. Walker explains that AI serves as an alternative source of support for students when they’re learning on their own, such as after school and on weekends: “We set up chatbots for them to have private tutors when they don’t have access to their teachers.” This supports student autonomy and allows them to learn more from educational materials they might not have otherwise encountered.
The same balance between state guidelines and local flexibility also shapes how the district leverages AI beyond student learning. Educational leaders often use AI to extract district-level insights from student performance data, helping them make evidence-based decisions. “Analyzing data, taking our school report card and putting various data points into it, and having AI analyze it and give us a breakdown of where we’re falling short” are key areas in which Thompson says AI is helping identify performance gaps and drive district improvements.
Flexibility in Policy Leads to Variation in Practice
Despite the promise of AI as a valuable instructional and administrative tool, Thompson acknowledges that not all teachers are ready to embrace the district’s vision. This gap between district policy mandates and classroom practice indicates that autonomy does not guarantee implementation consistency. “One of the difficulties or barriers for us is the teachers’ comfortability with technology and AI,” he says. Walker echoes this sentiment, discussing the persistent challenge of keeping pace with rapid change while preserving instructional quality: “It’s really tough to keep up with all that’s coming out, and finding ways to use it, and still keeping your lessons that you need to teach with some integrity.”
Another significant barrier for teachers is time. Walker feels that educators are often overextended and don’t have the bandwidth to explore methods outside of their tried-and-true teaching practices: “I think probably the biggest thing is teachers are so busy… [and] when you get into that comfort zone, it makes it difficult to kind of branch out.” While the district’s mandate ensures AI is used in classrooms, insufficient instructional support for busy teachers or those less familiar with the technology can result in surface-level adoption aimed at checking boxes rather than using AI as a meaningful teaching tool.
AI engagement in the district is further constrained by generational adoption gaps among veteran staff. This is a common trend across the U.S., as recent research shows that despite overall positive attitudes toward AI and similar levels of training, younger educators generally feel more comfortable with the technology than those in older age groups.3 In the Wisconsin district specifically, younger teachers are seen as more likely to use AI or seek out AI training, with Thompson noting “a direct correlation to age and professional development.” He’s optimistic that incoming hires can help shift the culture: “As we hire teachers… one of the things that we look for is somebody who’s tech savvy and is interested in branching out and looking for new ways to use AI for instruction.” These tech-confident teachers can act as AI champions to support colleagues who are less comfortable with the mandate by modeling the practical use of AI in classrooms.
At the same time, the administration is pushing back against the fear that AI will make teachers obsolete. District leaders feel strongly that teachers remain essential guides despite the technological advancements upending the education industry. Thompson likens this to the early days of the internet: “I don’t see it any different than when the internet first came out, right? Everybody thought that was the end of education and that kids had all this information at their fingertips, so we didn’t need teachers anymore.” Like the internet, he explains, AI is just another means of accessing information: “You still need somebody to guide you and teach you. And AI to us is just another tool on how to do that.” He feels that students will always require human guidance, regardless of the technology at their disposal.
Shifting the Focus from Policing AI to Career Preparation
Many teachers are willing to use AI, but only if it guides students through learning and explains the process instead of providing easy answers: In a survey from the EdSignals Studio, nearly one in three teachers said that this process-based approach best reflects their vision of ideal AI use.4 At the same time, some teachers are strongly opposed to AI because they worry about misuse. Walker describes a “fairly vocal group of people that don’t want it because they think the kids are just going to use it to cheat, and they can’t get past that viewpoint.” The solution, he says, is reframing AI “kind of like a calculator, the internet, or any of those tools… At first, they were looked at like ‘this is cheating,’ and now people can’t live without it.”
While some teachers are hesitant to use AI for learning, students in this district have largely embraced it. “A lot of the kids expose themselves to this stuff before we even get here, and so [they’re] ahead of some of our staff members,” Walker says, stressing that students are outpacing staff on AI use. Restricting student access to AI may reflect teacher’s efforts to preserve academic integrity, but it also limits opportunities to introduce AI to students in a structured, supervised environment. By mandating AI use as a component of instruction, the district seeks to shape how students engage with the tools they’re already using.
As the district works to catch up with students, it’s shifting from a focus on academic policing to viewing AI as a tool to prepare students for careers where AI proficiency is expected. Wisconsin state policy supports this direction, stressing that AI should be integrated into all subjects so that students can learn how it supports creativity, collaboration, critical thinking, research, and other professional skills.1 District leaders like Thompson agree that tying AI use to future job expectations is key to encouraging engagement in classrooms. Thompson adds that this application of AI “allows our kids to be exposed to career pathways and use AI not just for exposure but [to consider] what AI means in that pathway.”
The challenge isn’t just about getting teachers on board, but also about driving meaningful use that advances student learning. Teachers intuitively understand that students get the most out of AI when it supports process-based learning instead of offering shortcuts. In our survey, over 50% of teachers reported that they have students who use AI to help them understand assignments, check homework problems, or brainstorm writing assignments.4 However, many schools lack clear guidance to help teachers employ AI tools while preserving the productive struggle that is core to learning.
Closing the gap will require clearer evaluation frameworks that measure how AI is being used in the classroom, but also how individual tools incorporate process-based learning. For example, measuring the extent to which a tool employs the Socratic method—whether it guides students through their own thinking or simply does the thinking for them—could become a standard benchmark for evaluating new AI materials. Without formal evaluation processes in place, vetting is left to individual teachers. In this Wisconsin district, Walker has taken on this role, acting as a one-man grassroots support hub by helping his colleagues identify tools that support active learning.
Building a Culture of AI Readiness in Education
As AI becomes increasingly embedded in the education system, many districts are struggling to balance the need to provide direction against the risk of excessive oversight. The Wisconsin district’s experience offers a snapshot of what AI integration can look like when leadership is willing to mandate AI use while trusting educators to use it how they best see fit. At the same time, it shows us that this form of structured autonomy cannot resolve adoption barriers rooted in teacher time constraints, discomfort with unfamiliar technology, or fears that AI may be used as a student shortcut rather than a genuine learning aid.
These are not problems any single district can solve alone. Closing gaps between district mandates and consistent classroom use of AI will require clear state policies, evaluation frameworks that help educators identify high-quality AI materials, and practical guidance on how teachers can ensure active learning with these tools. The Wisconsin district is still working through these challenges, but it’s built a strong foundation of expectation and autonomy that will make the path forward easier to navigate as AI policy in the country continues to evolve.
Names in this article have been changed to preserve anonymity.
Sources
- Bires, A. & Albrecht, A. (June 2024). Empowering Lifelong Learning: AI Guidance for Enhancing K-12 and Library Education. Wisconsin Department of Public Instruction. https://dpi.wi.gov/sites/default/files/imce/imt/pdf/AI_Guidance_6-5-24.pdf
- AI for Education. (2025, October 28). State AI Guidance for K12 Schools. https://www.aiforeducation.io/ai-resources/state-ai-guidance
- Taheri, R., Nazemi, N., Pennington, S. E., Clark, J. A., & Dadgostari, F. (2025). Factors influencing educators’ AI adoption: A grounded meta-analysis review. Computers and Education: Artificial Intelligence, 9, 100464. https://doi.org/10.1016/j.caeai.2025.100464
- EdSignals Studio, Ecosystem Study #2, 2026.
