AI tools can present opportunities to promote equity in education when they are implemented with thoughtful safeguards and strong oversight, minimizing associated risks. For instance, real-time translation tools can increase engagement for multilingual learners by breaking down language barriers. At the same time, tools like plagiarism detectors can carry unintended biases that may disproportionately affect the same learners. To ensure equitable outcomes, educators and administrators must critically assess the accuracy and inclusivity of AI tools. The extent to which these technologies advance equity—or deepen existing divides—will depend on the quality of leadership, the robustness of AI literacy, and the strength of guidance in place to govern their use.

Education systems should carefully evaluate students' access to AI tools, rather than take the approach of general bans. Considerations should be given to age restrictions, data privacy, security concerns, and alignment with teaching and learning goals, curriculum, and the overall district technology plan. Attempting to enforce broad bans on AI is a futile effort that widens the digital divide between students with independent access to AI on personal devices and students dependent on school or community resources. Closing the digital divide in an age of AI still begins with internet connectivity, device availability, and digital literacy.

 Consider the following principles as you develop your AI guidance. Each principle includes questions to discuss and consider, a description, and a real-world example. Visit the Sample Guidance section for an illustrative example of a resource based on these principles.

Education leaders should clarify the shared values that will guide the use of AI tools, especially those that were not specifically created for educational contexts. AI tools should be applied to serve organizational goals, such as promoting student and staff well-being, enriching student learning experiences, and enhancing administrative functions. At the same time, new or revised goals may also emerge as workforce needs shift.

• How does our guidance highlight the purposeful use of AI to achieve our shared education vision and goals? 

• How do we reduce the digital divide between students with easy access to AI tools at home and those dependent on school resources?

• How does our guidance ensure inclusivity, catering to diverse learning needs and linguistic and cultural backgrounds?

Discussion Questions

Using AI tools to promote equity in education requires both access and thoughtful implementation. Equity is also addressed in the other principles in this toolkit, such as promoting AI literacy for all students, realizing the benefits of AI, and addressing the risks.

Ethical AI Use

The use of AI to pursue educational goals must be carefully aligned with the core values and ethics of the education system. This means identifying and mitigating the risks of AI in education so that the benefits may be realized (see Principle 4). Furthermore, students should learn about “the impact of AI on our lives, including the ethical issues it raises,” and teachers should be provided training to recognize misinformation.⁵ AI systems should be deployed in ways that support and maintain human decision-making in the process of teaching and learning.

Information Accuracy: Addressing misinformation, disinformation, and malinformation

When false information is used to harm: Deepfakes

Deepfake technology poses a growing threat within educational environments, potentially harming not only students but also administrators, teachers, and other staff members. AI-generated images, videos, and audio can be used to manipulate reality and used to create false accusations, impersonations, or fabricated media that can lead to serious consequences for individuals' emotional well-being, reputations, and even legal standing.  

Students need to learn how to recognize, resist, and report deepfakes, not only to protect themselves but also to understand the ethical implications of their use. In some cases, students may be the ones wielding deepfakes to exert social pressure, spread misinformation, or attempt to undermine adults or peers in subtle but impactful ways.

This issue cannot be addressed solely through bullying policies. Schools should incorporate structured, ongoing professional development for educators and age-appropriate AI literacy education for students. Understanding how these technologies work, their risks, and the broader implications of digital deception is critical to building safe and respectful learning environments.

Governments are beginning to respond to these challenges with targeted policies. In North Carolina, school systems are encouraged to update their bullying and cyberbullying policies to explicitly address deepfake content, including AI-generated explicit images, and to educate students about the risks of sharing personal media that could be misused. The Welsh government provides structured guidance on safeguarding students from the risks of generative AI, integrating responsible AI use into school policies, and offers specific strategies to protect learners online.

The Common Sense Media AI Ratings System provides a framework “designed to assess the safety, transparency, ethical use, and impact of AI products.”. 

• What is the plan to conduct an inventory of systems and software to understand the current state of AI use and ensure adherence to existing security and privacy regulations?  
• Does the education system enforce contracts with software providers, stipulating that any use of AI within their software or third-party providers must be clearly revealed to district staff and first approved by district leadership?

Discussion Questions

Wayne RESA, Michigan, USA, created an artificial Intelligence website and guidance document with ethical, pedagogical, administrative, and policy considerations. “AI systems often need large amounts of data to function effectively. In an educational context, some uses could involve collecting and analyzing sensitive data about students, such as their learning habits, academic performance, and personal information. Therefore, maintaining student privacy is the primary ethical consideration. Even with consent, it is not appropriate to prompt public models with identifiable data because anything shared with a model, even if information is shared in prompt form, may be added to the model for future reference and even shared with other users of the model.”

Generative AI introduces new challenges to copyright and intellectual property, particularly as it becomes harder to determine clear ownership of content used to train or generated by AI systems. Oregon’s guidance acknowledges this complexity and recommends that schools approach these issues with caution. Educators are encouraged to review licensing frameworks such as Creative Commons and stay informed through resources like the U.S. Copyright Office’s Artificial Intelligence Initiative. While not education-specific, this initiative offers valuable insight into how copyright laws may apply to AI-generated content. Given the legal uncertainties in this evolving area, school systems should engage legal counsel to help monitor developments and inform local policies, ensuring that staff understand their rights and responsibilities when using, sharing, or creating instructional materials with AI tools.

Once you have aligned your AI Responsible use guidelines and policies and updated existing privacy, data security, and student protection policies, your procurement and approval policies may also need a refresh. A coalition of seven leading edtech organizations—1EdTech, CAST, CoSN, Digital Promise, InnovateEDU, ISTE, and SETDA—has introduced Five Edtech Quality Indicators to help schools evaluate AI and edtech products efficiently. The coalition is also developing an EdTech Index to display verified edtech product approvals. 

The 2025 SETDA EdTech Quality Indicators Guide applies the Five EdTech Quality Indicators to support education leaders in evaluating and selecting high-quality educational technology tools. The guide includes adaptable questions for procurement leaders, examples of state leadership in edtech evaluation, and third-party validation resources to support informed decision-making. ​

AI literacy refers to the knowledge, skills, and attitudes associated with how artificial intelligence works, including its principles, concepts, and applications, as well as how to use artificial intelligence, such as its limitations, implications, and ethical considerations.

Foundational concepts of AI literacy include elements of computer science, as well as ethics, psychology, data science, engineering, statistics, and other areas beyond STEM. AI literacy equips individuals to engage productively and responsibly with AI technologies in society, the economy, and their personal lives. 

Schools can create opportunities for educators to collaborate and consolidate lessons learned to promote AI literacy across disciplines. In April 2025, the Center for Reinventing Public Education (CRPE) issued “an urgent call” for widespread support of AI literacy for educators and education leaders, arguing that “Adult AI literacy is the foundation to advancing scalable, sustainable AI strategies.”⁷

AI4K12’s Five Big Ideas in AI provide K-12 guidelines for how AI works.

AI literacy has benefits for a wide range of stakeholders and a variety of purposes. For example:

• Policymakers will be better able to assess and mitigate risks, from data privacy threats to overreliance on automation.
• Teachers will be more prepared to lead discussions on AI's ethical and societal impacts, including bias, privacy, and fairness, and promote its responsible use.
• Students will be more likely to critically assess AI-generated content and discern between reliable outputs and potential misinformation.

AI Literacy frameworks are beginning to emerge, and many guidance documents offer significant content shaping these frameworks. The AI Readiness Framework, developed by aiEDU, highlights “What students, educators, and district leaders need to know.” This free resource is offered for students and educators to use as they “develop AI Literacy and build AI Readiness.” For districts, the resource includes a rubric to use as they prepare schools for AI integration.

The Digital Promise AI Literacy Framework is designed to provide educational leaders with a concise and comprehensive understanding of what constitutes AI literacy. The framework centers around three interconnected "Modes of Engagement: Understand, Evaluate, and Use". Underpinning these modes are core values emphasizing human judgment and centering justice. These values are operationalized through "AI Literacy Practices", which are actionable skills that demonstrate understanding and evaluation. The framework also identifies three types of use: interact, create, and problem solve. This interconnected approach highlights that robust AI literacy involves a concurrent and integrated engagement with understanding, evaluating, and using AI, guided by core values and demonstrated through specific practices.

The European Artificial Intelligence Office maintains a Living Repository of AI Literacy Practices: A dynamic collection of real-world AI literacy initiatives from European organizations, compiled to support implementation of Article 4 of the EU AI Act. This repository showcases practices across sectors and organizational sizes, offering concrete examples of how to tailor AI literacy training by role, technical expertise, and contextual use. It’s designed to inspire cross-sector learning, highlight inclusive and risk-aware strategies, and ensure AI tools are used ethically, effectively, and in alignment with regulatory expectations.

The California Department of Education offers information regarding the role of AI in California K12 education. “Knowing how AI processes data and generates outputs enables students to think critically about the results AI systems provide. They can question and evaluate the information they receive and make informed decisions. This is of particular significance as students utilize AI in the classroom, to maintain academic integrity and promote ethical use of AI.” In addition, California’s legislature passed Assembly Bill No. 2876 in 2024 which requires “... the commission to consider incorporating Artificial Intelligence (AI) literacy content into the mathematics, science, and history-social science curriculum frameworks when those frameworks are next revised after January 1, 2025, and would require the commission to consider including AI literacy in its criteria for evaluating instructional materials when the state board next adopts mathematics, science, and history-social science instructional materials, as provided.”

• Does our guidance describe and support opportunities associated with using AI and proactively mitigate the risks?

Discussion Question

One resource that wrestles with what a balanced approach to AI in the classroom entails is How to Address Artificial Intelligence in the Classroom (School of Education at the University of San Andrés in Argentina). The guide (available in Spanish and English) provides educators, policymakers, and school leaders with insights and practical strategies for integrating AI into classrooms responsibly, including using AI-generated texts for analysis, incorporating AI literacy into lessons, and adapting assessments to ensure genuine student learning. 

The tables below outline areas of opportunity, related risks, and strategies to mitigate these risks in student learning, teacher support, and management and operations.

Tables: Opportunities, Risks, and Guardrails for Balanced AI Integration in Education 

The Code of Student Conduct of the Madison City Schools, Alabama, USA, integrates an Artificial Intelligence Acceptable Use Policy into section 4.8.14 of the “Acceptable Use Of Computer Technology And Related Resource” and recognizes specific risks of AI use:

• “Students should acknowledge that AI is not always factually accurate, nor seen as a credible source, and should be able to provide evidence to support its claims.”
• “All users must also be aware of the potential for bias and discrimination in AI tools and applications.“

Looking ahead: As new research emerges on the applications of AI in educational settings, schools should rely on evidence-based methods to guide initiatives (see also Principle 7: Evaluation).

• Does our guidance sufficiently cover academic integrity, plagiarism, and proper attribution when using AI technologies? 
• Do we offer professional development for educators to use commonly available AI technologies to support the modification of assignments and assessments?
• Do students have clear guidance for citing AI usage, using it properly to bolster learning, and understanding the importance of their voice and perspective in creating original work?

Discussion Questions

Existing academic integrity policies should be evaluated and updated to include issues specific to generative AI. Students should be truthful in giving credit to sources and tools and honest in presenting work that is genuinely their own for evaluation and feedback. Students should be instructed about properly citing any instances where generative AI tools were used. 

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Use one of the following resources:  

• MLA Style - Generative AI 
• APA Style - ChatGPT
• Chicago Style - Generative AI

Emerging guidance documents also recommend “rethinking” academic integrity in the context of AI. These approaches double down on the importance of maintaining standards of academic integrity, while acknowledging that we will not fully know the extent of AI use within the work that we see. Because of that perpetual uncertainty introduced by generative AI, maintaining academic integrity will require clarity about what academic integrity means. Proactively articulating the values of academic integrity and doing the work of defining those principles and operationalizing them in the context of AI is critical to prevent this potential erosion of integrity in our schools. 

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Colorado: “Be open to rethinking academic integrity; include clear definitions of plagiarism and academic dishonesty while emphasizing how students can responsibly use AI as a tool, eliminating the need for a separate AI plagiarism policy. Additionally, providing basic AI literacy education is essential, linking it to data literacy and career readiness. It is also crucial to teach students how to verify AI-generated information for truthfulness, ensuring they can critically assess the accuracy of such information” (p. 19).

Oklahoma: The Oklahoma State Department of Education guidance emphasizes the need to rethink traditional notions of plagiarism in the age of AI and adapt teaching methods and expectations:“As AI becomes an integral part of writing, from scholarly articles to news updates and emails, it is imperative to reconsider our traditional notions of plagiarism and academic integrity. As AI continues to shape education, labeling all AI-assisted work as “cheating” is shortsighted. Instead, educators must adapt their teaching methods and expectations to accommodate this new reality” (p.7).​

Teachers should be transparent about their own uses of AI and clear about how and when students are expected to use or not use AI. For example, a teacher might allow the limited use of generative AI on specific assignments or parts of assignments and articulate why they do not allow its use in other assignments. 

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An AI Assessment Scale is a tool that can help communicate clearly to students the specific uses of AI allowed on different assessments ranging from no AI to Full AI use.¹⁴ The authors recently updated the AI Assessment Scale. The new scale maintains the five categories of AI use, extending to creative uses of AI in exploration.

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Teachers should not use technologies that purport to identify the use of generative AI to detect cheating and plagiarism. The accuracy of these technologies is questionable, leading to the risk of false positives and negatives. Their use can promote a culture of policing assignments to maintain the status quo rather than preparing students for a future where AI usage is ubiquitous.¹⁵

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• Combating Academic Dishonesty from the University of Chicago
• Promoting Academic Integrity in your Course from Cornell University
• Strategies for Teaching Well When Students Have Access to Artificial Intelligence (AI) Generation Tools from George Mason University

Peninsula School District, Washington, USA. AI Principles and Beliefs Statement: “The promise of Artificial Intelligence (AI) in the Peninsula School District is substantial, not in substituting human instructors but by augmenting and streamlining their endeavors. Our perspective on AI in education is comparable to using a GPS: it serves as a supportive guide while still leaving ultimate control with the user, whether the educator or the student.”

Early concepts of “humans in the loop” appear in many guidance documents. That same work is beginning to conceptualize the human role as more than a mere participant and to check on the information generated by AI tools. Human agency conceives of AI as a tool that humans use to accomplish their goal and meet their needs. This perspective better aligns with the purpose of education systems in the first place: to build the knowledge, skills, and dispositions that students need to play rewarding and productive roles in their communities.

The European Commission resource, Ethical guidelines on the use of artificial intelligence (AI) and data in teaching and learning for Educators defines human agency as “the capability to become a competent member of society,” and the ability to “determine their life choices and be responsible for their actions. Agency underpins widely used concepts such as autonomy, self-determination, and responsibility” (p. 18). 

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Looking  ahead: In the future, AI policies should expect increased transparency from AI providers on how tools work and include statements like, “Our school system aims to work with AI tools that are transparent in how they operate, that provide explanations for outputs, and that enable human oversight and override. We will require all providers to make it clear when a user is interacting with an AI versus a human.”

​The EU AI Act, Article 4,  mandates that providers and deployers of AI systems ensure a sufficient level of AI literacy among their staff and others involved in operating AI systems, considering their technical knowledge, experience, education, and the context in which the AI systems are used. This requirement became effective on February 2, 2025.

Article 26 of Argentina’s Framework for the Regulation of the Development and Use of AI states that “AI training and education will be promoted for professionals, researchers and students, in order to develop the skills and competencies necessary to understand, use and develop AI systems in an ethical and responsible manner.”

One of the major benefits of learning about AI is developing computational thinking, a way of solving problems and designing systems that draw on concepts fundamental to computer science and are applicable to various disciplines. Learning how AI works is an opportunity for learning computational thinking skills, such as:

• Decomposition: AI often tackles complex problems. Understanding these problems requires breaking them down into smaller, more manageable parts.
• Pattern Recognition: Machine learning relies on recognizing patterns in data. By understanding machine learning, students practice and develop skills in identifying patterns and trends.
• Algorithmic Thinking: Learning about AI exposes students to algorithms, step-by-step solutions to a problem, from simple decision trees to more complex processes.
• Reflection: As with any computational task, AI models can sometimes produce unexpected or incorrect results. Understanding and rectifying, or debugging, these issues are central to both AI and computational thinking.
• Evaluation: AI often requires assessing different solutions to determine the best approach. This mirrors a key aspect of computational thinking, where solutions are tested and refined based on outcomes.

As an example of a discipline engaging deeply in how AI might influence curriculum and instruction, refer to TeachAI and CSTA’s Guidance on the Future of Computer Science Education in an Age of AI. 

Suggested Citation:  TeachAI (2025). AI Guidance for Schools Toolkit. Retrieved from teachai.org/toolkit. [date]. 

The United States White House issued an executive order in April 2025, Advancing Artificial Intelligence Education for American Youth, that underscores the importance of AI literacy.

Gwinnett County Schools in Georgia, USA, created an office dedicated to computer science and AI.  “The Office of Artificial Intelligence and Computer Science provides supports for the district’s K-12 Computer Science for All (CS4All) program as well as K-12 competition robotics. The office also supports the AI and Future-Readiness initiative in collaboration with other departments. Future-Readiness emphasizes the learning needed for students to be ready for their futures. As advanced technologies continue to impact the workplace and society, GCPS students will be future-ready as informed users and developers of those technologies.”