What Are AI Acceptable Use Policies for Local Government Employees?
As generative AI tools become more common in government workplaces, many agencies are developing acceptable use policies to establish clear guardrails for employees.
According to guidance collected by MRSC, local governments across the country have adopted policies that address how employees may use AI tools, what information can be entered into those systems and what types of human oversight are required. The policies often focus on issues such as data privacy, records retention, transparency and accountability.
The goal is not necessarily to prevent AI use. Instead, acceptable use policies help agencies create consistent expectations around responsible use.
Many policies prohibit employees from entering confidential, personally identifiable or otherwise sensitive information into public AI tools. Others require staff members to review and verify AI-generated content before it is shared publicly or used in decision-making processes.
MRSC also notes that local governments must consider public records requirements when using AI technologies. Because AI-generated content may become part of government business, agencies need clear policies governing how information is created, stored and retained.
Acceptable use policies establish the rules. AI literacy helps employees understand how to follow them.
READ MORE: Chatbots top the list of government AI use cases.
Why Is AI Literacy the Foundation of Responsible AI in Local Government?
For many agencies, AI literacy has become an essential component of responsible AI adoption.
Local governments continue to face workforce shortages, growing service demands and budget pressures. AI has the potential to help agencies address some of those challenges, but only if employees understand how to use the technology effectively.
“Local leaders always have more challenges to solve than resources to solve them,” Amante says. “AI is not going to be the panacea, but it certainly represents a possible solution to some of these persistent struggles that government has faced.”
That opportunity is one reason the Partnership for Public Service launched its AI Center for Government and developed its AI Government Leadership Program, which focuses on helping government leaders build AI literacy and organizational readiness.
Amante says agencies often focus first on deploying AI tools without spending enough time developing workforce competencies.
“We’re deploying AI, either just generative AI tools like a Copilot or a ChatGPT, without proper training,” she says. “If they don’t understand the fundamentals, then they can’t accurately assess whether it’s working.”
In other words, responsible AI adoption depends on more than technology investments. It also requires employees to understand how AI systems function, how outputs should be evaluated and where human judgment remains necessary.
LEARN MORE: Agentic process automation speeds work for government.
What Do Government Employees Need To Know About AI Literacy?
Government employees do not need to become AI engineers or data scientists. They do, however, need a practical understanding of how AI systems work and how they should be used in a public sector environment.
Prompting AI: Getting Useful Outputs Without Oversharing
One of the most visible AI skills involves learning how to interact effectively with generative AI tools.
Employees need to understand how to create prompts that provide sufficient context while avoiding the disclosure of sensitive information. That means knowing what data can be shared with an AI platform and what information should remain protected.
Amante says foundational knowledge begins with understanding AI concepts and terminology.
Government workers should understand topics such as generative AI, agentic AI and how data influences AI performance. They also need to understand how AI tools are being used across government and where those tools can provide value.
At the same time, agencies must ensure employees understand organizational policies regarding privacy, security and information sharing.
Evaluating AI Outputs: Review, Verify, Push Back
Another core AI literacy skill involves evaluating AI-generated content.
Generative AI systems can produce inaccurate information, incomplete analysis and fabricated details while presenting them with confidence. As a result, employees must be trained to review outputs critically rather than accepting them at face value.
Amante says agencies should evaluate AI based on whether it successfully solves a problem rather than simply measuring usage or adoption.
“Did it solve the problem it was looking to solve? Did it help the public in a greater way?” she says.
That same mindset applies to everyday users. Employees should verify information, review source materials and apply professional judgment before relying on AI-generated recommendations.
Human oversight remains essential regardless of how advanced AI tools become.
Recognizing Bias and Protecting Constituent Data
AI literacy also includes understanding the risks associated with AI systems.
According to MRSC, local governments should evaluate governance, risk management and ethical considerations as they explore AI adoption. Those concerns include protecting sensitive information, ensuring transparency and recognizing the potential for biased outputs.
Employees need to understand that AI systems can reflect biases found in training data and that AI-generated recommendations are not inherently objective.
At the same time, public sector workers routinely handle information involving residents, public safety operations, human services and permitting activities. AI literacy helps employees understand how to protect that information while still benefiting from AI-enabled tools.
Responsible use requires both technical awareness and sound judgment.
DIVE DEEPER: Why AI is a top priority for state and local governments.
How Can Officials Build an Agencywide AI Literacy Program?
For agencies beginning their AI journey, experts recommend focusing on workforce readiness before attempting large-scale deployments.
One of the most common mistakes Amante sees is organizations moving too quickly without addressing foundational issues such as data readiness and employee training.
“AI is built on data,” she says. “If they haven’t thought through their data structures, it’s not going to work well.”
The next step is ensuring that employees receive training on AI fundamentals, common risks and responsible use practices.
Amante says successful adoption also requires strong change management. Employees need to understand how AI can support their work and why the technology is being introduced.
“It’s not just about putting Microsoft Copilot on their computer,” she says. “They need to fully understand what the capabilities are, how it can help them and why they should want to use it.”
The Partnership for Public Service offers its AI Government Leadership Program to help public sector leaders build those competencies. Amante also points to resources from organizations such as InnovateUS and other government-focused training providers that offer educational opportunities for public servants.
Ultimately, AI literacy is less about mastering a particular tool and more about building a workforce that can use AI responsibly, evaluate results critically and make informed decisions.
As local governments continue exploring AI, workforce readiness may become one of the most important factors determining whether those initiatives succeed. Technology can provide new capabilities, but employees still need the knowledge and judgment to use those capabilities effectively.
