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Jun 18 2026
Artificial Intelligence

New Guidance Offers a Blueprint for Local Government AI Governance

Washington examples highlight transparency, public records compliance, workforce training and responsible generative technology adoption across agencies.

As local governments move from experimentation to broader deployment of artificial intelligence, new guidance from the Municipal Research and Services Center suggests that governance may be just as important as the technology itself.

The updated resource, published by MRSC in late May, compiles AI policies, governance frameworks and implementation guidance from cities and counties across Washington state. The guidance arrives as local governments nationwide explore generative AI tools for tasks such as research, drafting, meeting summaries and constituent communications.

Among the most common themes in the policies highlighted by MRSC are human oversight, data protection, transparency, employee training and public records compliance.

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Local Governments Need Clear Rules for AI Use

One of the clearest recommendations is that local governments establish formal expectations for employee use of AI tools. While generative AI can help staff work more efficiently, agencies should require employees to review and verify AI-generated content before using it in official business. Human accountability remains essential, even when AI assists with drafting or analysis.

The guidance also emphasizes the need to protect sensitive information. Local governments are encouraged to prohibit employees from entering confidential, protected or personally identifiable information into public AI platforms unless appropriate safeguards are in place. Agencies should likewise evaluate how AI vendors collect, store and use government data before deploying AI-enabled software.

Transparency is another recurring theme in the policies highlighted by MRSC. Among the examples cited is the city of Bellevue’s AI Policy and Guidelines, which establish principles for AI procurement and use while addressing transparency, bias mitigation, data privacy, records management, employee training and public awareness. The policy reflects a growing recognition that AI governance extends beyond the IT department and requires coordination among technology leaders, legal teams, records managers and business stakeholders.

READ MORE: Here is what agencies should know about AI governance.

Public Records Requirements Create New Challenges

Perhaps the most significant consideration for government agencies is records management.

According to MRSC, AI prompts and outputs created as part of official government business may be subject to public records requirements. In a related resource on public records and AI, MRSC notes that generative AI prompts and outputs retained by an agency are likely to be classified as public records and may need to be preserved, searched and disclosed in response to records requests.

That requirement could create new challenges for governments as employees increasingly rely on AI tools to draft documents, summarize meetings and support decision-making.

As agencies evaluate AI platforms, records retention, searchability and disclosure obligations may become just as important as functionality and cost.

LEARN MORE: Government agencies can build AI-ready data foundations.

Governance Is Emerging as the Next Phase of AI Adoption

The guidance also stresses the importance of workforce readiness. Effective AI adoption requires more than simply providing employees with access to new tools. Staff members need training on topics such as prompt creation, information verification, privacy protection and the limitations of AI-generated content.

The examples highlighted by MRSC suggest that local governments are increasingly moving beyond questions about whether employees should use AI. Instead, agencies are focusing on how to govern AI use in ways that protect public data, maintain transparency and comply with existing laws and regulations.

For public sector IT leaders, that shift may represent the next phase of AI adoption. As generative AI use becomes more common across government operations, formal policies and governance frameworks will emerge as essential tools for managing risk while enabling innovation.

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