AI in K-12: From Permission to Purpose

The Shift in How Districts Are Thinking About AI 

Through our annual K–12 Lens survey, we’ve tracked how districts are thinking about AI —across student, teacher, and administrator use. 

In the early days following the release of ChatGPT in late 2022, the conversation was largely cautious. The question was simple: Should we use this? Many districts focused on the risks of student use, with some choosing to block access altogether. 

That question didn’t last long. 

The conversation has shifted. 

Increasingly, districts are asking something more practical and more complex: How do we use AI to improve outcomes? For many, that starts with the day-to-day work of educators and staff. From lesson planning to communication to operational tasks, AI is beginning to show up in the workflows that keep schools running. 

As that shift takes hold, we wanted to better understand: 

• What does adoption actually looks like in practice? 

• How many staff are already using AI for common workflows?  

• How many remain opposed? 

This paper explores those questions, offering a clearer view into how AI is being used across K–12 staff workflows today, and where districts may be headed next.

What’s Changing in AI Adoption Across K-12 

• Support has stabilized. Just over half of districts report supporting AI use, with little change year over year. 

• Support varies by use case. Districts are more supportive of staff-facing applications than student-facing use. 

• Support is rising across most roles – but declining among superintendents. Staff adoption is growing, while leadership caution is increasing. 

• Capacity shapes support. Urban and larger districts report higher levels of support than smaller and rural districts. 

• Interest outpaces use. Districts want to expand AI use, particularly in data analysis, financial workflows, and automation. 

• Adoption is uneven. AI is emerging across workflows, but often in isolated pockets rather than coordinated, systemwide efforts. 

• AI use is associated with outcomes. Districts using AI report stronger hiring conditions, higher financial forecast accuracy, and greater operational confidence – while also appearing more often in high-need environments. 

What the K-12 Lens Reveals 

Support for AI has leveled off. 

Just over half of districts report supporting AI use, a level that has remained largely unchanged from the past year. After an initial increase, support is holding rather than expanding.  

Districts are not rushing into adoption, but they are not stepping back either. Instead, many are taking a more deliberate approach, weighing where AI fits and how it can be used responsibly.  

Interest is high. Confidence is still forming. 

Opposition – after declining in 2025 – has begun to tick up again, and a significant portion of districts remain neutral. Together, these trends suggest that while interest is holding, many districts are still working through how, and whether, to move forward.  

  

Support Is Not Uniform 

How AI is used matters as much as whether it is used. 

Districts are most supportive of AI when it is used by staff, especially teachers and administrators. In these roles, AI is seen as a practical tool to reduce workload, streamline tasks, and improve efficiency.  

Support for student use is more mixed. While many districts see potential, there is still greater caution around how AI should be used directly by students and what it may mean for learning. 

Support Is Growing Across Roles – With One Notable Exception 

Most roles are becoming more supportive. One is stepping back. 

Principals, HR leaders, curriculum teams, and business officials all show rising levels of support compared to last year. As AI becomes more embedded in daily workflows, more staff are seeing its practical value. 

Superintendents, however, show a different pattern. While still the most supportive group overall, the share of superintendents who support AI declined compared to last year – suggesting a shift in sentiment at the leadership level. This likely reflects the broader responsibility of district leadership – balancing potential benefits with concerns around risk, policy, and long-term impact. 

Staff adoption is growing. Leadership caution is increasing.  

Context Matters: Geography and District Size  

Capacity shapes support. 

Support for AI is highest in urban districts, where access to resources and infrastructure may make implementation more feasible. Urban districts also showed increased support in 2026, while suburban and rural districts experienced slight declines. 

District size tells a similar story.  

Larger and medium-sized districts consistently report higher levels of support, while smaller districts lag behind. These patterns have held steady over time, suggesting they reflect longer-term differences. 

Where capacity is stronger, districts are more likely to express support for AI.  

Interest is Outpacing Use 

Districts want to do more than they are currently doing.  

Across nearly every workflow, interest in AI exceeds current adoption. Districts are already using AI in areas like employee document management, communication, and lesson planning – but many want to expand into more complex use cases. 

The largest gaps appear in:  

• Budget and financial analysis 
• Predictive models for student support 
• Workflow automation and operational processes 

Districts are not resisting AI – they’re either waiting for the right tools to become available or they are still figuring out how to implement them safely and effectively. 

The barrier is not interest. It’s execution. 

Where AI Is Showing Up Today 

To capture use cases beyond predefined survey options, we included an open-ended question inviting respondents to describe how their district is currently using, or would like to use, AI. 

AI is not concentrated in a single function. 

Responses point to a wide range of applications, from instructional support and administrative writing to specialized processes like special education documentation.  

At the same time, many respondents pointed to future opportunities in data analysis, internal tools, and workflow automation.  

Adoption is happening – but not always visibly. 

A notable share of respondents indicated they were unsure how AI is being used across their district. This suggests adoption is often occurring in pockets, rather than through coordinated, systemwide efforts. 

The chart below shows how frequently different use cases were mentioned across responses. Each percentage reflects the share of responses that referenced a given theme. Because respondents could describe multiple uses, individual responses may be represented in more than one category. 

The sections below define each theme and provide representative perspectives to illustrate how districts are describing current and future AI use in their own words.

AI Use and District Outcomes 

AI use is consistently linked to differences in outcomes. 

Data from the K-12 Lens also shows that districts using AI in staffing workflows – such as applicant screening, interviewing, and credential tracking – are more likely to report improved hiring conditions. In special education, AI use is associated with reduced time spent on IEP documentation, with more than 70% of districts not using AI reporting five or more hours per IEP. 

In financial planning, the relationship is even stronger. 57% of districts using AI for budget forecasting report high accuracy, compared with fewer than 8% not using AI.  

Operational confidence follows a similar pattern. Districts using AI for inventory management report higher confidence across key tasks, including tracking devices, managing distribution, and supporting users. 

But the relationship is not uniform. 

Districts using AI for student support – such as personalized learning, predictive models, and tutoring – also report higher chronic absenteeism (often above the 18% average) and lower teacher retention. This does not suggest that AI is driving these outcomes. Instead, it reflects where AI is being used – often in districts facing greater strain. 

AI shows up where systems are strong – and where pressure is highest. 

From Exploration to Implementation 

Adoption is selective – and intentional. 

AI is not spreading everywhere at once. It is appearing first in workflows where the need is most immediate and the risk is manageable – documentation, communication, and routine operations.  

These are areas where errors can be reviewed, corrected, and contained. 

That’s where AI adoption is happening first. 

At the same time, use remains uneven. 

Many district leaders report limited visibility into how AI is being used beyond their immediate role. Adoption is often happening in pockets, without a shared view of what’s working or where it matters most.  

The next phase is not expansion – it’s alignment. 

Districts will need to: 

• clarify where AI adds value 
• connect use across teams 
• provide staff with guidance and support 

The shift underway is about integration, not acceleration. 

What comes next will depend less on whether districts use AI, and more on how intentionally they do so.