Artificial Intelligence (AI) is changing the way we live, work, and learn, and the public education system is adapting to this rapidly changing technology landscape.1 Understanding how these tools can be used responsibly is the first step to teaching how to engage with AI thoughtfully and effectively to enhance learning.
In listening sessions with students and teachers, both groups expressed a desire for AI policies and acknowledged that it is here to stay. The challenge lies in ensuring its ethical use and preventing it from becoming a replacement for authentic work.
AI for Equity, a national nonprofit, has been working with schools across the country to codify best practices and disseminate learnings to drive more equitable outcomes for all students. Their work acknowledges that integrating AI into education is a multi-year, adaptive process that requires schools to continually reassess what and how they teach. As part of this effort, AI for Equity created a best practice framework for school leadership teams that includes eight key components.2 3
This type of guidance is particularly important given current trends. A nationally representative survey showed that as of fall 2024, roughly half of school districts reported that they have provided training to their teachers about generative artificial intelligence tools, double the proportion of districts from the fall. However, disparities remain: 67 percent of low-poverty districts reported having provided training for teachers.4
AI staff surveys from AI for Equity in school year 2023-24 across seven participating networks of schools (including some in D.C.) reported that 38 percent of staff said they are using AI tools on a daily/weekly basis. Staff have also recognized the value of these tools. For example, all respondents stated that generative AI has helped become more efficient and/or productive (48 percent). These types of responses show how AI is beginning to shape educators’ daily work, highlighting the need for continued investment in policies and resources to expand effective and equitable use.
To understand the integration of AI in the District, we asked stakeholders about their perceptions of the strengths and challenges of AI in public schools.
Ashley Jeffrey, Chief Strategy Officer, Washington Leadership Academy PCS
Strong partnerships have been essential to Washington Leadership Academy’s successful AI implementation. As AI continues to shape the future of education, collaborations with organizations like AI for Equity, The Learning Accelerator, and Leading Educators have helped us thoughtfully integrate new tools into our classrooms. These partnerships have enabled us to learn best practices, address challenges, and ensure that both students and teachers use AI effectively and responsibly.
Contrary to WLA’s typical leadership style, our school adopted a top-down approach for our AI implementation. In the first 6 months, Executive leadership incorporated AI into our work and then encouraged staff to utilize AI for any task that didn’t affect student privacy. Most of our students are Black and Brown, so we center conversations on ethics around AI’s impact on the environment and our communities, both here and abroad. To ensure appropriate AI use, our students operate with guardrails, including a rubric that outlines which assignments permit AI use, which do not, and the extent to which AI can be integrated into schoolwork.
This intentional approach requires difficult trade-offs as we balance innovation with responsibility and equity. We openly discuss the racial, environmental, economic, and social implications of AI, encouraging our future coders to maintain an equity mindset as they create and use technology. Ultimately, while AI is here to stay, our goal is to help students engage with it thoughtfully, and to build digital literacy and critical thinking skills that will prepare them for the workforce of tomorrow.
Janie Scanlon, Founding Partner, Elevant Strategies
When thinking about how to use AI to improve workstreams—whether school administrators, teachers, or education policy advocates—it’s essential to begin with a clear understanding of the problem you’re trying to solve. Is the goal to boost operational efficiency, produce adaptive instructional content, or expose students to emerging pathways in STEM? Whatever the purpose, the successful execution of AI should not be taken for granted. Instead, stakeholders at all levels must collaborate to ensure AI initiatives are tied to tangible processes and desirable, realistic outcomes.
It’s shortsighted and potentially dangerous to place the responsibility of understanding and vetting AI tools only on individual educators. Keeping up with rapid technological advancements, data privacy standards, and emerging safety concerns is a full-time job, one that teachers should not be expected to take on in addition to their instructional responsibilities. Moreover, data privacy policies vary among companies and organizations, and the absence of clear best practices or system-level data governance structures can create confusion and risk. Without stronger oversight and consistent policies, the adoption of AI in classrooms, schools, districts, and even corporate spaces may outpace our ability to ensure it is used ethically, safely, and effectively.
Aaron Cuny, Founder & Chief Executive Officer, AI for Equity
AI is already reshaping broad segments of the labor market, and it’s reasonable to expect that today’s students will graduate into workplaces where AI fluency is a baseline expectation. Yet there’s an emerging equity challenge: higher-poverty districts are less likely than their lower-poverty peers to provide structured AI learning opportunities for both staff and students.
District leaders can help close this gap by developing a clear roadmap for AI integration—establishing policies that connect AI use to academic and operational goals, aligning professional learning to those priorities, and forming partnerships that expand local capacity and trust. When districts create coherent frameworks and consistent approaches, educators gain the structured support they need to navigate change, and all students can access meaningful AI learning experiences regardless of their district’s resources.
The AI Innovation Index supports this leadership work by helping systems measure progress against their roadmap actions, benchmark their approaches against peers, and surface insights that guide more equitable, strategic decision-making over time.
Samuel Price, Senior, Washington Leadership Academy
Artificial Intelligence (AI) has become a large part of my time as a student. Our school has integrated a lot of AI platforms into our daily learning – including one created by a teacher, which gives different information on the topics discussed in class which can be helpful with notetaking and conceptualizing difficult concepts. These notes are typically used to help with drafting an essay but not writing the essay itself.
AI is a strength in the classroom because it assists with giving ideas that can be built on, especially when it’s hard to think of an idea for yourself. It gives you a prompt or starting point that can be expanded while still making the work your own. Despite this, AI has incurred challenges. It is relative, meaning that it typically doesn’t have a diverse set of responses. This could mean that what it generates for one student could be similar to what it generates for another.
Another weakness of AI is that it could result in losing the ability to think for yourself. If you use it too much, you become too reliant on it, and you’re not giving yourself an opportunity to think critically. Nevertheless, our school has strict restrictions on what AI can be used for and what it can’t be used for. Typically, AI is only allowed for planning assignments or outlining, and thus far, there have been no assignments that have been given that allow us to utilize AI throughout the assignment.
Endnotes
- Kulesa, A., Kotran, A., Mission, M., & Wells, M. 2025. Building AI Readiness: Actionable K-12 Insights and Investment Pathways. Bellwether. Retrieved from https://bellwether.org/publications/building-ai-readiness/?activeTab=1
- These components include adopting an AI-informed, overarching pedagogical vision that can be applied to any objective within any subject or class, narrating the change management process for teachers, collecting baseline data from staff and students, establishing high-level organizational principles for ”AI, Classroom Instruction, and Academic Integrity”, establishing a student usage policy that can be reasonably enforced, flooding the zone with examples and exemplars, building leader capacity and systematize teacher support and accountability for curriculum revision, and investing in evolving your graduate profile.
- AI For Equity. “AI, Classroom Instruction, and Academic Integrity.” AI for Equity. Retrieved from https://docs.google.com/document/d/1cSOKIOROr423uwKk1SzJ4KvVBENyLoHvAFPx8QpLrZ4/edit?tab=t.0
- Diliberti, M., Lake, R., & Weiner, S. 2025. More Districts Are Training Teachers on Artificial Intelligence. Rand. Retrieved from https://www.rand.org/pubs/research_reports/RRA956-31.html