Generative Artificial Intelligence (AI) has quickly moved from tech labs into the public sector mainstream. From federal agencies in Washington to city halls across the country,
generative AI in government is on the rise. In fact, U.S. federal agencies reported a ninefold jump in generative AI use cases from 2023 to 2024 (rising from 32 to 282 use cases). This surge reflects a growing belief that AI capable of producing text, images, and data insights on demand could revolutionize how government operates
transforming everything from internal workflows to public services. But with these opportunities come significant risks and challenges that government technology leaders must carefully navigate. This article explores the potential of generative AI in the public sector, its benefits for federal and local government agencies, and the crucial safeguards needed to use it responsibly.
The Rise of Generative AI in Government
Public-sector interest in AI has never been higher. Developments in tools like large language models (e.g. ChatGPT) and image generators have shown how AI can draft documents, answer questions, create visuals, and more when prompted by a user. Governments are taking notice. A recent U.S. Government Accountability Office (GAO) report found that across 11 federal agencies, the total number of AI use cases nearly doubled between 2023 and 2024. Many of these new projects involve generative AI systems for tasks like content creation and data analysis. The generative AI benefits in government are envisioned to include dramatically increased productivity and streamlined operations. For example, generative AI could help automatically summarize reports, draft responses or briefings, and provide instant insights from large datasets potentially
transforming AI in government services to be faster and more efficient.
Beyond federal agencies,
state and local governments are also experimenting with generative AI. Generative AI in local government is still nascent but growing. According to one global survey, 90% of mayors expressed interest in using generative AI, yet only 2% of cities had actually launched generative AI initiatives as of 2023. This gap between enthusiasm and execution is closing fast as more pilot projects get underway. In the United States, some city officials aren’t waiting for formal programs they’ve begun using AI tools informally to assist their work. For instance, an investigation in Washington state found city staff using ChatGPT to help write emails, draft mayoral letters, generate policy documents and even create social media posts and press releases. These early adopters see
generative AI in local government as a way to do more with less, helping small teams produce polished documents or answers quickly. At the same time, this ad-hoc use raises questions about transparency and security (many of those AI-written letters and posts weren’t labeled as such, potentially blurring authorship). Nonetheless, the trend is clear: from big federal agencies to city halls, governments are dipping their toes into generative AI and discovering both its promise and its pitfalls.
Generative AI Benefits in Government
When implemented thoughtfully, generative AI offers a variety of benefits in government operations and public services. Here are some of the key opportunities this technology provides:
Efficiency and Productivity:
Generative AI can automate routine text- and data-heavy tasks at a scale and speed far beyond human capacity. This means government employees can delegate tedious work (like summarizing lengthy documents or drafting standard replies) to AI and focus on higher-value activities. A McKinsey analysis estimates that generative AI could automate 60–70% of employees’ tasks and add an astounding $2.6 to $4.4 trillion annually to global productivity. Public agencies stand to gain a share of these efficiency improvements. Early pilots already show time saved for example, the U.S. Patent and Trademark Office developed an AI-powered search tool to help examiners sift through millions of patent records faster and more accurately. By embracing modern IT solutions for the government sector that include generative AI, agencies can reduce backlogs and serve constituents faster.
Enhanced Public Services and 24/7 Assistance:
One of the most visible generative AI benefits in government is the improvement of citizen services. AI-powered chatbots and virtual assistants can handle common inquiries anytime, offering 24/7 support that augments limited human staff. Many agencies are exploring these
AI in government services for example, the National Archives’ “Ask US” chatbot uses a generative AI to help the public search millions of records via a conversational interface. City governments, too, see potential in AI helpers. Buenos Aires’s city chatbot “Boti,” launched in 2019 and enhanced with generative AI, handled 11 million conversations in one month and became “a preferred channel for citizens” seeking services. By deploying intelligent assistants on websites or messaging platforms, government offices can be available to help citizens around the clock. This not only improves convenience but also builds public trust when people get quick, accurate answers. Crucially, these AI assistants can operate in multiple languages and personalize responses, expanding access to services. The generative AI in local government context is especially promising here: small municipalities can offer AI-based customer service that was previously out of reach due to staffing limits. With AI in government services like permitting, licensing, or FAQs, residents could get what they need without waiting in line or on hold.
Data Analysis and Decision Support:
Government agencies deal with massive amounts of data from economic figures to public feedback to intelligence reports. Generative AI systems (such as large language models and other AI agents) are adept at rapidly analyzing and synthesizing information from diverse sources. This capability can greatly
enhance decision-making in the public sector. For example, the Department of Health and Human Services has piloted a generative AI tool that scans scientific publications to identify potential poliovirus outbreaks in formerly polio-free areas. By catching subtle signals across thousands of documents, the AI can flag emerging public health risks much faster than traditional methods. Similarly, city planners are testing AI models to analyze traffic patterns or development proposals, generating insights that inform urban policy. These uses illustrate how generative AI acts as an “insight generator,” uncovering patterns and predictions to guide human leaders. The result is more
data-driven policy whether it’s budgeting, healthcare, transportation, or national security. In one notable state-level initiative, California in 2025 entered into first-of-its-kind agreements to use generative AI for analyzing highway congestion data and improving a state call center’s customer service. These projects aim to turn vast data streams into actionable solutions (like pinpointing traffic bottlenecks or helping call agents respond better), showing AI’s potential to inform smarter strategies in government.
Innovation in Service Delivery:
Generative AI also opens the door to entirely new capabilities in government. It can
create content from drafting an initial policy proposal to generating a visual simulation. Some local governments have leveraged AI tools to innovate public engagement. For instance, planners in Boston used generative AI to produce images visualizing what a more bicycle-friendly city layout could look like, helping residents literally see potential changes and building support for urban initiatives. Internally, officials are discovering creative uses too. In Washington, records showed city staff using ChatGPT to brainstorm ideas, rewrite communications in a warmer tone, and even
research IT solutions by having the AI compare software options. By serving as a tireless brainstorming partner or first-draft writer, generative AI can spark innovation in how policies are developed and communicated. It’s like giving every public servant an on-demand research assistant and editor. When combined with emerging autonomous software agents (often called agentic AI), generative models can even
enhance agentic AI capabilities enabling goal-driven AI programs that take initiative in completing multi-step tasks. This points to a future where complex processes (permit approvals, benefit applications, etc.) could be handled start-to-finish by coordinated AI agents, under human supervision.
Generative AI in Local Government: Early Trials and Lessons
While federal agencies often have more resources for technology,
generative AI in local government is where some of the most relatable use cases are emerging. City and county governments face many repetitive text-based tasks and public inquiries that AI can help with. As mentioned, several Washington state cities have embraced ChatGPT for day-to-day work. Beyond drafting letters or social media posts, staff have used AI to summarize meeting notes, debug code, and even craft responses to citizen emails on sensitive topics. This shows how generative AI can be a force multiplier for small public-sector teams, allowing them to serve their community more quickly. A city employee described asking an AI assistant: “Using the Mayor’s voice, can you rewrite this letter to be a little more collaborative and less aggressive in tone?” a novel way to ensure communications hit the right note.
Local governments are also launching more structured pilots. For example, the Commonwealth of Pennsylvania ran a year-long pilot of ChatGPT Enterprise in 2024-2025 with 175 employees across various agencies to systematically explore where AI could improve daily work. By involving staff in testing the tool for tasks like writing, research, and customer service, Pennsylvania gathered insights on what worked and what didn’t, helping shape responsible-use policies. This kind of government AI pilot is a smart approach for cities and states: start small, document the benefits and problems, and create guidelines before scaling up. Early findings highlight important lessons. On the upside, generative AI can save time and provide creative solutions; on the downside, concerns have arisen around accuracy (AI outputs can be confidently wrong or “hallucinate” facts), privacy (if staff input sensitive data into public AI tools), and accountability (who is responsible if the AI’s content is misleading?). Local officials in Washington noted issues of transparency when AI is used none of the AI-assisted documents they reviewed had disclosures that they were machine-generated. This could erode public trust if not addressed. As a result, some city governments and states are now drafting policies for AI usage, requiring measures like labeling AI-generated content and restricting use of external AI platforms for confidential data. The
human role in AI governance remains critical: no matter how advanced the tool, human officials must review AI outputs, provide oversight, and take responsibility for final decisions or publications. In summary, local government experiments with generative AI show immense promise in boosting efficiency and engagement, but they underscore the need for guidelines, training, and human oversight from the start.
Risks and Challenges of Generative AI in Government
Alongside its opportunities, generative AI brings a spectrum of risks that public-sector leaders must manage. One immediate challenge is accuracy and misinformation. Generative models can produce incorrect or biased information just as confidently as accurate content. GAO warns that generative AI can spread misinformation and even create deceptive outputs that might mislead decision-makers or the public. An AI might, for example, draft a report with subtle factual errors or produce a fake yet realistic-looking image. If unchecked, such mistakes could erode trust in government communications. There are also
national security and cybersecurity risks an AI system with access to sensitive data could be manipulated or could inadvertently reveal confidential information. Federal officials have voiced concerns that these tools, if not properly secured, could become attack vectors or violate data privacy policies. Indeed, 10 out of 12 agencies GAO interviewed said existing privacy and data protection rules pose obstacles to deploying generative AI widely. Agencies must ensure that using AI doesn’t mean uploading citizens’ data to external servers or violating regulations.
Another significant risk area is bias and fairness. Generative AI systems learn from vast datasets that often contain historical biases. Without careful tuning, an AI used in government could inadvertently produce outputs that discriminate or reflect unfair assumptions (for instance, in drafting policy language or answering public queries on sensitive topics). Closely tied to this is the challenge of
public trust and transparency. If constituents suspect that faceless algorithms rather than accountable humans are making decisions or crafting messages, they may lose confidence in those services. The Washington local government case, where AI was used extensively without disclosure, highlights the transparency issue. Government must be open about when AI is involved and have clear lines of accountability. This is where the debate of
Agentic AI vs Traditional AI approaches comes into play. Traditional AI (and software in general) acts as a tool, firmly under human control with predetermined functions. Agentic AI (autonomous AI agents) can make context-based decisions and take actions with less direct human input. While agentic AI can dramatically increase automation, it also raises the stakes for oversight an autonomous AI agent gone awry could make unsanctioned choices. Striking the right balance between leveraging AI’s autonomy and maintaining human governance is a new frontier for public-sector risk management. In practice, this means setting ethical guidelines (e.g. forbidding AI from certain decisions), instituting review checkpoints, and being ready to pull the plug if an AI system behaves unexpectedly. Technical challenges are also non-trivial: many agencies have outdated IT infrastructure and limited AI expertise.
In a 2024 survey, 60% of public-sector IT professionals said a lack of AI skills in their organization was a top implementation hurdle. Without training staff or hiring specialists, agencies risk misusing the tools or failing to extract value from them. Finally, there’s the issue of regulatory compliance governments must navigate evolving laws and policies on AI. Executive orders (like those in the U.S. and other countries) and frameworks (such as data protection laws or emerging AI oversight bodies) will shape what is permissible. Adhering to these rules while innovating is a delicate dance; for example, an agency might be excited to deploy a generative AI chatbot but must ensure it complies with privacy, accessibility, and security standards from day one.
Balancing Innovation with Responsibility
How can government decision-makers harness generative AI’s potential while mitigating its risks? The key is a balanced, strategic approach that treats AI as an aid to humans not a replacement and embeds oversight and ethics into every step. Governance and planning are essential. Many experts advise starting with limited-scope
government AI pilot projects in low-risk areas, then scaling up once lessons are learned. This lets agencies develop internal guidelines and trust the technology gradually. For instance, agencies can pilot a generative AI to handle a narrow task (like answering frequently asked questions or summarizing public comments) and closely monitor its performance for accuracy and bias before expanding its use. Early collaboration and
cross-agency knowledge sharing can also accelerate learning; federal agencies have begun forming working groups to exchange best practices as they all experiment with generative AI.
Equally important is investing in human oversight and training. AI should augment, not replace, the human role in government services. Agencies should establish review workflows where human officials approve AI-generated content, especially anything public-facing or policy-related. Training programs can help staff learn how to use AI tools effectively and detect errors (Pennsylvania’s employee AI training initiative is a good example). Upskilling the workforce will empower employees to leverage AI’s strengths and apply sound judgment to its outputs. On the technical side, governments need to modernize their IT environments to safely integrate AI. That means ensuring data security (perhaps using on-premises or sovereign cloud solutions for sensitive data), implementing access controls, and monitoring AI systems continuously for anomalies.
Some governments are exploring
agentic AI carefully by first developing strong governance frameworks for example, creating an AI ethics board or an oversight committee that reviews all new AI use cases. This helps set boundaries on autonomous AI behavior and address the Agentic AI vs Traditional AI dilemma with intentional policy decisions. Gartner analysts recommend that public leaders incorporate AI agents into strategic plans by identifying high-value use cases and then running targeted pilots to address concerns before full deployment. In fact, Gartner predicts that by 2029,
60% of government agencies worldwide will be using AI agents to automate over half of citizen interactions, up from less than 10% in 2025. Reaching that future in a positive way will require clear roadmaps and proactive stakeholder engagement. Citizens need to be informed about how AI is used and assured that ethical guardrails are in place. Initiatives like the World Economic Forum’s AI Governance Alliance are bringing government, industry, and civil society together to develop such guardrails globally, which will aid local efforts.
Finally, governments should partner with experts to implement generative AI responsibly. Working with academia, civic tech groups, and vetted private-sector experts can provide valuable guidance on the latest tools and risk mitigation techniques. For example, some agencies collaborate with technology vendors in sandbox environments to test AI solutions on anonymized data before using them live. A
government technology solutions provider with experience in AI deployments can help navigate technical complexity and ensure compliance with standards. By bringing in outside expertise, public-sector leaders can more quickly adopt best practices and avoid pitfalls that early adopters elsewhere have encountered.
Conclusion: Embracing Generative AI with Care
Generative AI is poised to become a cornerstone of modern governance a powerful tool to enhance productivity, deliver more responsive services, and drive innovation in the public sector. The opportunities for generative AI in government are vast: imagine consistently clear communications, data-informed policies crafted in hours instead of weeks, and AI assistants handling routine tasks so public servants can tackle strategic problems. These benefits, however, will only be realized if governments embrace the technology carefully and ethically. By acknowledging the risks from misinformation to bias to security and proactively managing them through strong oversight, transparency, and incremental adoption, agencies can build public trust in AI-driven initiatives. The path forward should combine the agentic capabilities of advanced AI with the irreplaceable judgment of human officials. In doing so, government leaders can unlock the best of both worlds: AI systems that accelerate and enhance human agency rather than undermine it.
As we move into this new era, the mandate for public-sector decision-makers is clear. It’s time to educate your teams, update your policies, and experiment deliberately with generative AI solutions that align with your mission. The governments that succeed will be those that innovate with accountability leveraging AI for efficiency and insights, while keeping citizens’ rights and needs front and center. Generative AI is not a silver bullet for every problem, but used wisely, it can be a transformative tool in the government toolkit.
Call to Action: Is your agency prepared to navigate the AI revolution? Don’t let the potential of generative AI pass you by. Consider launching a small pilot program or consulting with experts to identify high-impact use cases in your department. As a forward-thinking public leader, you have the chance to modernize services and improve outcomes with AI all while setting the standards for responsibility and ethics. To get started,
partner with a trusted government technology solutions provider who understands the unique needs of the government sector. With the right guidance, you can confidently adopt generative AI technologies that drive efficiency, enhance public services, and uphold the public’s trust. Embrace the opportunity to lead your government organization into the future of AI-powered innovation, and ensure that this exciting technology serves as a force for good in your community.
