Local governments see AI as a way to stretch taxpayer dollars further and deliver more responsive, personalized services to their communities. For school boards and community colleges, the potential goes further still: AI could expand educational opportunities, improve administrative efficiency and, ultimately, boost student success.
But the technology brings real risk alongside those gains. A Gallup survey of K-12 educators published in October 2026 found that 59% used AI tools during the 2025-26 school year. A separate Gallup/Walton survey conducted in early 2026 found that only 18% had received any formal guidance from school administrators on how AI tools should be used. For local government, the gap is starker: a September 2026 UserEvidence survey of more than 800 public sector IT professionals found that just 19% of state and local government IT professionals have an active AI oversight framework in place. That gap extends to the boards themselves: a Diligent Institute survey of 230 nonprofit and public sector leaders published in October 2026 found that 52% of boards do not use AI at all in oversight or strategic decision-making, even as 30% name AI modernization their leading investment priority. AI is already in the building. Governance, for most, is still catching up.
Falling behind creates exposure: Fines, reputational damage and lost community trust are all on the table. Boards that stay current have a clearer basis for compliance decisions, stronger stakeholder confidence and more room to think strategically about long-term adoption.
To help publicly elected boards develop strong, up-to-date policies for AI governance, we've rounded up the latest regulatory developments into a guide that covers:
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The emerging framework of AI laws covers a wide and ever-expanding range of areas, from cybersecurity and data protections to usage policies and safety precautions.
When navigating AI governance for your school or municipal organization, we recommend consulting with your legal team and doing in-depth research on specific agencies, laws and issues. This high-level overview of select countries (the agencies involved, what they're focused on, who they're partnering with and specific policies, both enacted and proposed) is a powerful starting point.
Data privacy has long been governed at the federal level by legislation such as FERPA and HIPAA. The situation with AI is more complex.
Two foundational laws from 2020 established the federal AI framework:
The Biden administration added its own layer: an AI Bill of Rights (2022) and Executive Order 14110 on Safe, Secure and Trustworthy AI (October 2023), focused on safety requirements and risk management for federal agencies. President Trump revoked EO 14110 in January 2025 via Executive Order 14179, "Removing Barriers to American Leadership in Artificial Intelligence," shifting federal policy toward a pro-innovation, deregulatory approach and directing the development of a national AI Action Plan.
That plan arrived in July 2025. In December 2025, Executive Order 14365, "Ensuring a National Policy Framework for Artificial Intelligence," went further still: it directs the White House to prepare a legislative recommendation for a uniform federal AI framework that would preempt conflicting state AI laws. The White House published those legislative recommendations in March 2026. As of late October 2026, the first congressional response — the FRONTIER Act — was introduced in the House on October 24, 2026. It would preempt state obligations on AI developers in three narrow areas: catastrophic risk transparency, independent auditing and incident reporting. It leaves child safety laws, state government procurement rules and laws that apply to everyone equally untouched. The bill has not passed. For school boards and local government officials, the important carve-out is that child safety protections are explicitly excluded from any proposed preemption: student data protections, content restrictions and age-appropriate AI safeguards remain on solid ground.
AI regulation has evolved through a patchwork of federal, state and industry frameworks. In July 2025, the Senate struck down proposed legislation that would have blocked state and local governments from regulating AI for a decade. State-level activity has continued regardless, though the tension between federal and state AI policy is now a live issue boards should follow.
For school board members, the key starting point is the Department of Education's July 2025 guidance on AI use, issued in direct response to Executive Order 14277, "Advancing Artificial Intelligence Education for American Youth" (April 23, 2025), which directed federal agencies to prioritize AI literacy and integration in K–12 education. The guidance covers how federal grant funds can support responsible AI integration and sets out five principles: educator-led, ethical, accessible, transparent and data-protective. In April 2026, the Department finalized AI as a formal grantmaking priority for discretionary programs, meaning AI-focused proposals now carry a competitive advantage in federal grant competitions. In August 2026, the Department issued a Dear Colleague Letter on the responsible use of classroom technology, directing schools to evaluate any technology by the specific learning problem it solves, the evidence that it works and the privacy obligations it carries.
Local government officials and board members can look to the White House's AI Action Plan, also from 2025, and follow developing conversations about the use of AI in government activities.
Regulation of AI at the state level has been more direct and more active than among federal policymakers. Many of the key considerations apply both to school boards and to local government.
The National Conference of State Legislatures AI Legislation Database of AI-related regulatory developments, tracking the most common areas for AI regulation across states: transparency requirements for automated decision-making tools, guardrails for AI-powered bots and agents, and data privacy protections.
The pace has accelerated. Colorado set an early precedent when it enacted SB 24-205 in May 2024, the first comprehensive state AI law in the US, focused on algorithmic discrimination and high-risk AI systems. However, the law was repealed before it ever took effect. In May 2026, Colorado replaced it with SB 26-189, a narrower Automated Decision-Making Technology (ADMT) disclosure framework that requires notice, explanation and human-review rights for consequential automated decisions. The new law takes effect January 1, 2027.
California has been a forerunner in AI regulation, addressing algorithmic discrimination, business accountability and data use. Signed in September 2026, AB 1159 added a direct protection for students: covered student information may not be used to train generative AI systems, effective January 1, 2027 for K-12 and July 1, 2027 for higher education.
Many states (including Texas and Utah) have also established a state office or center of excellence to sponsor, host and disseminate additional research or guidance.
In 2026 alone, four states enacted K-12-specific AI laws:
Florida went further still: State Board Rule 6A-1.0957, adopted September 2026 and effective October 29, 2026, requires parent opt-in for student-facing AI tools, public approved-tool registries, interaction logs and non-AI alternatives. Districts have until July 1, 2027 to comply.
At the district level, responses have been equally varied. In September 2026, New York City and Los Angeles Unified, the two largest school districts in the country, each implemented moratoriums on student-facing generative AI pending the development of stronger safeguards: NYC's covered nearly 600,000 students from K-2 through 8th grade, and LA Unified blocked generative AI tools on district-issued devices for all students districtwide. Both cited the absence of adequate oversight frameworks as the reason for pausing.
Most states have opted for guidance rather than mandates: AI for Education was tracking official guidance or policies from 35 states and Puerto Rico as of 2026, with the most common focus areas including notifying people when they're interacting with AI or AI-generated content, using algorithms to determine employment, services or housing, offering ways to opt out of data collection and profiling, testing AI systems for discrimination and bias, and monitoring, mitigating and disclosing the potential risk of automated decision tools.
In Tennessee and Ohio, school districts are required to maintain a detailed policy on AI use. In states like Massachusetts, the absence of school-specific regulation is balanced by robust guidelines covering legal, ethical, pedagogical and social issues related to AI.
For local government, the top concern is not targeted regulation but the complexity of multiple, overlapping sources of AI policy and guidance.
At the federal level, Canada's Artificial Intelligence and Data Act (AIDA) was its first attempt at comprehensive AI legislation. AIDA formed Part 3 of Bill C-27, which died when Parliament was prorogued on January 6, 2025. AIDA was never passed into law, and no successor federal AI act has been introduced.
What actually governs AI use in Canada today is a patchwork of privacy law and provincial statutes:
Bill C-36 (tabled June 2026) is a privacy bill that would add automated-decision transparency and human-review rights for significant decisions about individuals. It is at second reading in the House of Commons and is not yet law.
These rules will continue to change. Debates about the use of AI in Canada's schools and local governments remain active, and the absence of a federal AI statute means the compliance picture is assembled from multiple provincial and sectoral sources. Savvy board members will make proactive moves to head off the greatest risks and set up flexible, powerful systems for governance and internal management of AI technologies.
Understanding what the law requires is the starting point. Translating it into policy, process and accountability is where boards earn their compliance.
A Diligent survey of public sector board leaders published in January 2026 found that 73% had no AI policy or weren't sure whether one existed, and 80% had received no AI-specific training for board members. Diligent Institute research published in October 2026, based on a survey of 230 nonprofit and public sector leaders including K-12 school boards and local government bodies, found that when boards were asked what would most improve risk oversight, only 15% chose enhanced AI-powered tools. Boards prioritize more structured risk discussions (38%), clearer links between risk and strategy (28%) and clearer governance role definitions (24%) first.
"Boards do want AI support, but they appear to view it as useful only inside a stronger governance operating model. In other words, technology is not a substitute for disciplined agenda design, role clarity, effective reporting and board education. AI is more likely to create value when those fundamentals are already in place." — Dottie Schindlinger, Executive Director, Diligent Institute
One place to start is with an AI governance framework. Such a framework sets guardrails, guidelines and expectations, as well as outlining what's acceptable and what's prohibited for those using AI tools.
A municipal or school district board can make the process of developing an AI framework more manageable with these seven steps:
"While AI will assist in streamlining workflows and so many other things, the human insight provided by members of public-facing boards will not and should not ever be replaced. Boards will actually be able to offload work that can be determined by algorithms and, in its place, focus on important discussions and collaborations with those whom they represent." — Andrea Messina, CEO, Florida School Boards Association
AI policy (guidelines and rules for AI use) is a complementary next step and brings up many more questions. A public education board might consider:
"If it's going to help [board members] do their jobs, phenomenal. If it's going to do their jobs for them, that's really problematic." — Jay Worona, Partner at Jaspan Schlesinger and Narendran, and former Deputy Executive Director and General Counsel, New York State School Boards Association
For practical next steps, Diligent's 90-day AI action plan for public sector governance provides a structured implementation timeline, from establishing ownership to active oversight. The AI governance checklist for public education, AI governance checklist for local government and guide to creating a safe and transparent AI governance framework each translate those steps into concrete board-level decisions.
Maintaining AI policy, tracking regulatory changes and keeping board members informed across multiple compliance fronts is where governance technology pays its way. Diligent Community gives school boards and local governments a single secure platform for:
Throughout, this cloud-based board management software uses FIPS-validated AES-256 encryption to ensure privacy and security for the most sensitive school or municipal data.
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Given the pace of AI regulation, a useful starting point is the public sector regulations outlook, which covers the full range of mandates and trends shaping the year ahead with practical steps boards can act on.
For the cybersecurity side of the same regulatory picture, cybersecurity regulations: what public facing boards need to know covers federal and state data protection requirements for school boards and local government.
For boards that need a practical starting point before diving into the longer guides, Diligent's AI oversight starter kit for public governance provides a ready-to-use SWOT template, board discussion guide and structured meeting agenda for AI governance deliberations.
Guide to AI risk and governance for public boards goes deeper on the structures, principles and implementation steps boards use to adopt AI responsibly, with specific guidance for school districts, community colleges and local government.
AI governance guide for public sector leaders takes the wider strategic view, covering how school districts and local government bodies can build sustainable, audit-ready AI governance programs across their GRC functions.
The Diligent Institute's Governance Outlook 2027 draws on a survey of 230 nonprofit and public sector leaders, including K-12 school boards and local government bodies, to document what boards are prioritizing, where the governance gaps are and what the most effective boards are doing differently. The AI findings are particularly sharp: 52% of boards do not use AI at all in oversight or decision-making, yet AI modernization is the leading investment priority.
For K-12 board members, 2026 in focus: top trends for school boards covers AI governance alongside cybersecurity, curriculum debates and enrollment shifts, helping boards see the regulatory picture in context.
The Leading with Purpose podcast episode with John Thomsen, Director of Engagement and Policy at NEOLA, covers how K-12 boards can navigate fast-moving regulation while staying anchored in mission and student success. Jay Worona, quoted above, also joins a companion episode on AI, equity and school governance with the New York State School Boards Association, which goes deeper on responsible adoption and the oversight questions boards should be asking.
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