From Promise to Practice: A Strategic Framework for Counties Embracing Generative AI

Angela Novelli
May 30
4 min read

Bridging policy, ethics, and implementation for local government AI adoption

By Ramit Luthra

overhead view of a town, local government, generative ai

Introduction: The GenAI Inflection Point

Generative AI (GenAI) has emerged as a transformative force, rapidly reshaping industries, redefining workflows, and increasingly influencing public service. While private-sector organizations aggressively prototype and deploy GenAI tools, county governments are faced with a different kind of challenge: how to responsibly harness the power of GenAI while safeguarding trust, equity, and security.

In my decades working within enterprise technology and cybersecurity, I have seen waves of transformation—from the advent of cloud computing to zero trust architectures. GenAI, however, feels fundamentally different. Its reach is broader, its risks are deeper, and its potential, particularly for local governments, is extraordinary.

The Strategic Blind Spot in Local AI Adoption

Many counties are already using GenAI—sometimes without even knowing it. Vendors are embedding GenAI features in software, employees are experimenting with it to automate grant writing or streamline intake forms, and public expectations are shifting toward faster, AI-enhanced service delivery.

But too often, these efforts happen without foundational policies, data governance practices, or ethical frameworks. The result is often a patchwork of isolated initiatives, where enthusiasm outpaces readiness

Four Pillars for Responsible County AI Readiness

The following framework provides four essential dimensions for GenAI readiness, adapted from NACo's "AI County Compass"—but with an added layer of strategic insight for technology and policy leaders.

1. Promote Policy Models

Counties must distinguish between policies (strict and enforceable), standards (moderately prescriptive), and guidelines (flexible best practices). This tiered approach allows for adaptability as GenAI tools evolve.

Pro tip: Tie GenAI policies to existing cybersecurity, remote work, and acceptable use frameworks. Keep policies modular and review them biannually.

Example: A growing concern in state and local governments is the emergence of “shadow AI,” where employees use AI tools without official approval or oversight. This unregulated use poses risks such as data breaches, biased decision-making, and legal non-compliance. The lack of formal policies and training exacerbates these issues, underscoring the need for structured AI governance frameworks.

2. Establish an Ethical Framework

GenAI isn't just about efficiency; it's about public trust. Fairness, transparency, privacy, and accountability must be woven into every implementation.

I view AI hallucinations (when AI generates convincing but factually incorrect information), hidden biases, and opaque decision-making as not just technical issues, but trust liabilities. Counties should:

Maintain human oversight at every stage of GenAI implementation—from prompt design to output review—to prevent errors and reinforce accountability.
Use watermarks and disclosures in public communications.
Implement ethics training tied to real-world GenAI examples.

Example: Baltimore, Maryland has issued a generative AI executive order that places significant restrictions on the use of AI-generated content by city employees. The directive explicitly forbids the utilization of outputs from generative AI tools without a thorough process of fact-checking and refinement. This mandate is particularly critical when the AI-generated content is intended to inform decision-making processes within the city government or when it is slated for public communications.

3. Enable Responsible Applications

Start with low-risk, high-value use cases such as grant proposal drafting, agenda summarization, or language translation.

Classify use cases by sensitivity. A simple 1-2-3 risk scale (low-medium-high) based on data types and public exposure is practical and effective. Ensure robust data governance and apply cybersecurity controls at every layer for maximum security.

Example: King County, Washington successfully implemented a GenAI-powered chatbot to answer resident questions about permit applications, reducing call volume by 35% while maintaining high satisfaction ratings.

4. Prepare the Workforce

Workforce readiness is the cornerstone of implementing GenAI in local government operations. Counties should:

Offer training tailored to job roles.
Hire or designate a Chief AI Officer.
Engage retirees as GenAI mentors.
Promote AI literacy for elected officials and unions.

This is not just about skilling up. It's about reimagining value creation in the public sector.

Example: Following Governor Gavin Newsom's executive order directing state agencies to develop ethical and responsible AI deployment plans, the California Department of Human Resources introduced professional development courses for public employees in 2024. This initiative aimed to equip state workers with the necessary skills as California explores the integration of AI technology into government operations.

Cybersecurity Isn't an Add-On—It's the Foundation

To secure GenAI systems and preserve public trust, counties must treat AI as an extension of their critical infrastructure. As GenAI becomes more prevalent, so do its attack surfaces. Consider the implications of deepfakes in public meetings, synthetic voice impersonation in finance departments, or malicious prompts that exploit chatbot vulnerabilities.

Security strategies must include:

Model vetting and access control.
Fraud detection protocols.
Ongoing monitoring for AI misuse.
Clear incident response for GenAI-related breaches.
Compliance with relevant regulations (HIPAA for health data, CJIS for criminal justice information, etc.).

Recommendations to County Leadership

Start with your data. If your metadata is poor, your AI will mislead.
Pilot transparently. Publicize pilot programs and invite community feedback.
Don't ban GenAI. Create guardrails instead.
Cross-skill your workforce. Don't assume AI expertise will only come from new hires.
Think regional. Small counties can pool resources for shared GenAI capabilities.

5 Questions Every County CIO Should Ask Before Signing an AI Contract

Is the GenAI model closed or open? What happens to the data we input?
Does the vendor use county data to train models available to others?
What are the data retention, access, and deletion policies?
Has the model passed a security and ethics audit?
What is the long-term cost model—including usage-based pricing, support, and compliance overhead?

GenAI's Local Moment

Counties are closest to the residents. They deliver frontline services that impact daily lives. Done right, GenAI can amplify this impact—but only if implementation is responsible, inclusive, and strategic.

Let's lead not with fear, but with foresight. And let's make sure the future we build with AI reflects the values that local governments were created to uphold. By acting now with deliberation and clarity, counties can set the standard for how GenAI responsibly serves the public good.

"Effective performance is preceded by painstaking preparation."

- Brian Tracy

Ramit Luthra is a senior technology executive and advisor with decades of experience in AI, cybersecurity, and digital transformation. He writes at the intersection of cybersecurity and infrastructure, focusing on how emerging technologies—especially AI—are reshaping the future of digital governance.