Artificial intelligence (AI) has a range of uses in government, from furthering public policy objectives in areas such as emergency services, health, and welfare, to assisting citizens in interacting with public agencies through virtual assistants and chatbots. According to the Harvard Business Review, "Applications of artificial intelligence to the public sector are broad and growing, with early experiments taking place around the world." Hila Mehr from the Ash Center for Democratic Governance and Innovation at Harvard University notes that AI in government is not new, with postal services using machine methods in the late 1990s to recognise handwriting on envelopes to automatically route letters. The use of AI in government offers significant benefits, including efficiencies that result in cost savings and reduced opportunities for corruption, but it also carries risks related to bias, transparency, and accountability.
Uses of AI in government
The potential uses of AI in government are wide and varied, with Deloitte considering that "Cognitive technologies could eventually revolutionize every facet of government operations." Mehr suggests that six types of government problems are appropriate for AI applications: resource allocation, where administrative support is required to complete tasks more quickly; large datasets, which are too large for employees to work efficiently and could be combined to provide greater insights; expert shortage, including where basic questions could be answered and niche issues can be learned; predictable scenarios, where historical data makes the situation predictable; procedural tasks, which are repetitive with binary inputs or outputs; and diverse data, where data takes various forms such as visual and linguistic and needs to be summarized regularly. Mehr states that "While applications of AI in government work have not kept pace with the rapid expansion of AI in the private sector, the potential use cases in the public sector mirror common applications in the private sector." Potential and actual uses can be divided into three broad categories: those that contribute to public policy objectives, those that assist public interactions with the government, and other uses.
Contributing to public policy objectives
AI can contribute to public policy objectives in several ways. For example, it can enable citizens to receive benefits at job loss, retirement, bereavement, and child birth almost immediately, in an automated way, without requiring any actions from citizens at all. It can support social insurance service provision, classify emergency calls based on urgency (as in the system used by the Cincinnati Fire Department in the United States), detect and prevent the spread of diseases, and assist public servants in making welfare payments and immigration decisions. AI can also be used to adjudicate bail hearings, triage health care cases, monitor social media for public feedback on policies, and identify emergency situations. Other applications include identifying fraudulent benefits claims, predicting crime and recommending optimal police presence, predicting traffic congestion and car accidents, anticipating road maintenance requirements, identifying breaches of health regulations, providing personalised education to students, and marking exam papers. AI also assists with defence and national security, as discussed in the broader context of Artificial intelligence applications.
In China, AI has been used to drive both political and economic markets. In 2019, Shanghai's government rolled out 100 billion yuan to assist in funding enterprises that used AI, introducing 22 new policy agendas. Shanghai invested in these enterprises to attract top international talent and set up the Shanghai Municipal Big Data Center. City Brain AI, an urban management platform made by Alibaba Cloud, is used to maintain a significant share of capital investment through public and state owned enterprises. The synergy between public and private sectors is more than capital-driven, with the blend of public and private shareholding shaped by the role of provincial and sub-provincial governments, which hold control over the direction that City Brain AI takes both socially and economically.
Assisting public interactions with government
AI can assist members of the public to interact with government and access services. Examples include answering questions using virtual assistants or chatbots, directing requests to the appropriate area within government, filling out forms, assisting with searching documents (such as IP Australia's trade mark search), and scheduling appointments. Various governments, including those of Australia and Estonia, have implemented virtual assistants to aid citizens in navigating services, with applications ranging from tax inquiries to life-event registrations.
Gerrymandering
Gerrymandering is a method of influencing political process by drawing map boundaries in favor of incumbent parties. Academic researchers Wendy Tam Cho and Bruce Cain have proposed partially automating the map-drawing process with an AI system to reduce partisan gerrymandering. Even with this AI system, the process may still be manipulated to favor partisan interests, so the researchers emphasized the importance of transparency and human involvement.
Other uses
Other uses of AI in government include translation and language interpretation, pioneered by the European Commission's Directorate General for Interpretation and Florika Fink-Hooijer, as well as drafting documents.
Potential benefits
AI offers potential efficiencies and cost savings for government. Deloitte has estimated that automation could save US Government employees between 96.7 million and 1.2 billion hours a year, resulting in potential savings of between $3.3 billion and $41.1 billion a year. The Harvard Business Review has stated that while this may lead a government to reduce employee numbers, "Governments could instead choose to invest in the quality of its services. They can re-employ workers' time towards more rewarding work that requires lateral thinking, empathy, and creativity - all things at which humans continue to outperform even the most sophisticated AI program." These efficiencies can also reduce the opportunities for corruption by automating decision processes that might otherwise be subject to human discretion.
Risks
Risks associated with the use of AI in government include AI becoming susceptible to bias, a lack of transparency in how an AI application may make decisions, and the accountability for any such decisions. For example, a 2026 lawsuit alleged that the U.S. Department of Government Efficiency used ChatGPT to flag and cancel federal humanities grants, including projects on Jewish history and Israeli culture. Such cases highlight the potential for AI systems to produce outcomes that are not fully understood or overseen by human officials, raising questions about due process and the proper scope of automated decision-making in public administration.
Implementation and oversight
The adoption of AI in government often involves partnerships with private technology firms. For instance, OpenAI has provided models like ChatGPT that have been used experimentally in various public sector contexts. Governments may also work with cloud providers such as Amazon Web Services, Microsoft Azure, and Google Cloud to deploy AI at scale. The development of these systems relies on foundational techniques from Machine learning and Deep learning, including large language models and transformers. However, the use of such models in government raises unique challenges, including the need for model pruning to reduce computational costs and the importance of data augmentation to ensure robustness. Oversight mechanisms, such as human-in-the-loop review and algorithmic impact assessments, are increasingly recommended to mitigate risks.
Future directions
As AI technologies continue to evolve, their role in government is likely to expand. Researchers and policymakers are exploring ways to use AI for more proactive and personalised public services, while also developing frameworks for ethical and accountable use. The balance between efficiency gains and the protection of civil liberties remains a central concern. International bodies and national governments are beginning to issue guidelines and regulations, though as of the mid-2020s, comprehensive legal frameworks are still in development. The trajectory of AI in government will depend on ongoing advances in Generative AI and related fields, as well as public trust in these systems.