Artificial intelligence (AI) is a topic of growing interest for California schools and classrooms, spurred by new advances in generative AI, many of which are being led by California-based technology leaders such as OpenAI’s ChatGPT, Google’s Gemini, Anthropic’s Claude. The implications for schools are still uncertain and complicated. Early in our current generative AI era, a vision of the ultimate personalized tutor was promoted, whereby every student could learn with a custom chatbot. Yet the initial uptake and impact of generative AI was modest, there were some prominent cases of failure (LAUSD, Keierleber, 2024), and the research has ultimately been lacking. The conversations around AI in education have pivoted several times from digital tutors to teacher efficiency tools to drivers of student cheating to harmful technologies for students’ mental health and critical thinking capacities to job displacement. Given worldwide engagement and uncertainty around AI and its relationship to K-12 education or its regional equivalents, this conversation will remain cacophonous and fluid.
With that said, we still seek information to guide decision-making, particularly at the policy level, and clarification on what is the current landscape of AI in K-12 education. This technical report provides information, although with recognition that this is a dynamic situation and that existing publicly accessible data - and specifically data that focus on California - is scarce. Even research studies based in the US are scarce as the currently available academic literature is largely contributed from overseas researchers working in very different national contexts. Under the larger umbrella of AI and K-12 education, the following questions are addressed in this report:
- What is the current policy landscape for California with respect to encouraging and supporting AI education?
- To what extent is AI currently being instructionally supported in K-12, both for teachers and students, with respect to school-related educational or instructional activities? How does California compare with what is happening nationally?
- What are emerging areas of need for the California K-12 education system, given the most recent national and international guidance and research related to teaching about AI in schools?
At present, we as a society and the larger scientific enterprise are not able to answer questions about whether AI is a net positive or negative for schools, under what conditions AI will improve student achievement or teacher job satisfaction, and what kinds of efficiencies or cost-savings (or new costs) AI will have on K-12 education. Some initial information is coming (see SCALE report) but these are questions that require more time (e.g., more years and schools integrating AI) and evidence gathering (e.g., more measures of outcomes and variables of interest, many of which may not yet have valid instrumentation).
It is important to also acknowledge that this recent push for AI is taking place in the 2020s. This period of time included an abrupt shift to remote learning during the COVID-19 pandemic, leading to an immediate investment in chromebooks and digital learning platforms that continue to be in use. The return to schools post-COVID had some documented challenges for students. Alarm about cell phone usage in schools, “screen time”, and potential risks associated with both (e.g., Haidt, 2024; Prasanth, 2025; Sved, 2025) has led to new policies about cell phone use, and some of this is surfacing concerns about mental health and student social and emotional development in relation to AI. Again, the latter is still new enough that information is limited even though actions – such as bans or restrictions - are being taken.
