Which Public Sector Jobs Should Be Done by Agents?

A detailed look at government jobs that are ready for automation by advanced AI.

Technological progress has always been a double-edged sword for labor. On one side, new tools and machines eliminate the need for humans to perform many routine tasks. On the other side, they create demand for different skills and entirely new jobs. History offers plenty of evidence that while automation can destroy existing jobs, it also opens up many new possibilities. For example, the mechanization of agriculture in the 20th century wiped out millions of farm labor positions, but it spurred growth in manufacturing and service industries. Each time society panics about technology potentially destroying jobs, the overall employment still tends to increase in the long run as productivity gains lead to higher demand and new industries. In short, governments and workers have continually adapted by phasing out roles and tasks made obsolete by innovation and by embracing new kinds of work created in their place.

Today, we are witnessing another such transition. Advanced AI is the latest transformative tool, and it promises to handle not just mechanical or clerical tasks but even cognitive, decision-making tasks. Public sector agencies should see this as part of the natural progression. Just as past generations eliminated the job of elevator operator or the human “computer” who did calculations by hand, our generation can confidently remove certain routine office jobs, while expecting new roles such as AI system supervisors or data ethicists to emerge. Recognizing this cycle makes it easier to approach automation not as a threat, but as an evolution in how government work gets done.

Why Many Government Jobs Are Ripe for Automation

The past few months have highlighted that significant inefficiencies exist in parts of the public sector workforce. In the past year, oversight investigations into federal agencies’ pandemic-era remote work arrangements unearthed some uncomfortable facts. A watchdog report from the Office of Personnel Management’s Inspector General found abuse of telework policies, with 58.1% of sampled employees failing to meet even the minimal in-office work requirements during 2024. In plain terms, a large share of employees were not fully utilized. Some were logging far fewer hours than expected or not coming into the office as needed.

Even more striking, allegations have emerged that some federal employees were effectively working second jobs on the side while still on the government clock. President Donald Trump has repeatedly claimed that many remote federal workers only devote 10 to 20 percent of their time to their official duties, spending the rest of the workday on personal business or another job. While those claims are politically charged and not always proven, the very fact they resonate with the public shows a perception that some government roles have minimal real workload. In other words, if an employee can literally hold a full-time second job while also occupying a government position, it raises a blunt question: is that government job truly necessary, or could its tasks be handled by an automated system? At the very least, these findings suggest a lot of low-value or idle time in certain public roles. This is exactly the kind of scenario where AI-driven automation can step in to either enhance productivity or eliminate waste.

It is not just the federal level. State and local governments have their own pockets of redundant bureaucracy. Layers of clerical approval, data entry backlogs, and routine report writing often tie up staff who could be better used elsewhere. Budget pressures are leading many state governors and city managers to scrutinize whether paying people to perform menial repetitive tasks, or to be present in an office without much work, is a responsible use of taxpayer funds. With modern AI tools available, keeping such positions unchanged is harder to justify. Those minimal tasks are prime candidates to hand off to AI agents, freeing up or downsizing the roles currently devoted to them.

The Rise of AI Agents Capable of Knowledge Work

Why consider AI agents for government jobs now? Simply put, AI technology has advanced by leaps and bounds in its ability to handle complex, multi-step work. Unlike the simple office software of the past, today’s AI agents are increasingly autonomous and capable of decision-making. They build upon the success of generative AI, such as GPT-style language models and robotic process automation, but go further by actively executing tasks across systems. These agents can interface with databases, compose written communications, analyze data, and make rule-based decisions without constant human guidance. In the private industry, companies have already begun deploying AI co-workers for routine operations. For example, Microsoft’s internal use of AI agents led to a 36 percent improvement in IT self-service resolutions, automating helpdesk tasks and boosting sales productivity by automating lead management. If such gains are possible in business, similar efficiency improvements are likely if AI-driven automation is applied in government agencies.

AI is no longer limited to automating rote factory work or straightforward transactions. Generative AI and agentic AI systems can perform cognitive tasks. Those are the kinds of desk jobs and analytical work that fill the public sector. Unlike earlier automation waves that hit mostly assembly line or routine clerical jobs, this wave can affect white-collar and professional roles, including many government office jobs. Think of an AI that can draft a memo, sort through dozens of case files for relevant information, or triage incoming service requests from citizens. These are tasks that mid-level officials and analysts handle today, and they are very much within AI’s capability now.

Some tech leaders predict that AI smarter and more versatile than the average human could arrive within the next five to ten years. As AI systems approach human reasoning in generality, the range of tasks they can take on expands dramatically. Jobs that involve judgment, planning, or complex communication (traditionally considered “safe” from automation) may soon be feasible to offload to an AI agent. In the public sector, that means not just clerical work, but things like preliminary legal reviews, policy analysis, and multi-step approval processes could be handled by sufficiently advanced AI. Governments need to prepare for this future now by identifying which jobs can be turned over to machines. The approaching era of AGI makes this exercise urgent: what can be automated should be automated to capture efficiency and cost benefits for the public.

Public Sector Tasks Ripe for AI Automation

With both current AI and anticipated AGI capabilities in mind, it is possible to identify which jobs and tasks in government are most suitable to be done by AI agents. These tend to be functions that are repetitive, rules-based, data-intensive, or easily standardized. Key categories of public sector work that an AI could handle, either entirely autonomously or with minimal human oversight, include the following:

Administrative and Data Entry Work:

A huge portion of government employment is clerical: entering data, copying information between systems, updating spreadsheets, processing routine forms. These tasks are highly automatable. Modern AI-powered software can already input data, reconcile databases, and file digital paperwork at high speed compared to a human typist. For example, expense report filing, time sheet approvals, and payroll data entry can be done by agent software with near-zero errors. Any job titled “clerk,” “data technician,” or “administrative assistant” that involves shuffling information from one format to another is a strong candidate to be done by an AI agent. By using optical character recognition and natural language processing, an agent can read incoming documents (emails, PDFs, scanned forms) and populate the required fields in a system just as a person would, but faster and without fatigue.

Routine Record-Keeping and Compliance Checks:

Government agencies run on records such as permits, licenses, applications, case files, compliance reports, and more. Reviewing these for completeness or compliance with guidelines is often tedious work for staff. AI can take over many of these checks. For instance, an AI agent could scan building permit applications to ensure all required documents are attached and flag any missing information. It could cross-reference business license renewals against a database of fees paid, automatically approving those that meet criteria and flagging those that do not. Such rule-based decision trees are exactly what AI excels at. In fields like accounting and auditing, AI tools are already extracting data from documents and verifying it against regulations, as some finance-sector AI does for SEC compliance. Similar technology can be applied for governmental compliance tasks. By automating record audits and validation, agencies would need fewer human inspectors for the mundane box-checking, freeing them for higher-level investigation of the truly complex or suspicious cases.

Customer Service and Public Inquiries:

Public-facing offices, from the DMV to Social Security call centers, handle huge volumes of repetitive inquiries. “Where do I find this form? How do I update my address? What is the status of my application?” These are questions an AI chatbot or voice agent can answer instantly by pulling from internal knowledge bases. AI agents acting as virtual customer service reps can handle tier-1 inquiries around the clock without wait times, escalating only unusual or sensitive cases to human staff. Many municipalities have already introduced chatbot assistants on their websites for answering common citizen questions. As AI language models become more capable, these agents can handle even nuanced conversations. For example, guiding someone step-by-step through a tax form or troubleshooting an issue with their public benefits. The result is that jobs like call center operator, information desk clerk, or public inquiry email responder could be largely done by AI. This not only improves response times to the public but also reduces staffing costs. A human workforce might be retained only to handle complex cases or interventions when the AI encounters something it cannot resolve.

Scheduling, Logistics, and Coordination:

Government operations involve countless meetings, appointments, and resource scheduling, such as inspectors scheduling site visits or city maintenance crews allocating work orders. AI agents are well suited to handle these coordination tasks. An AI can manage calendars for a whole department, find optimal meeting times, send reminders, and even arrange travel—tasks often assigned to secretaries or administrative officers. In a more specialized example, consider a city that needs to schedule hundreds of sanitation pickups or building inspections per week: an AI system can dynamically route and schedule these better than a human dispatcher, accounting for location, urgency, and staff availability.

Early versions of this can be seen in routing software and smart scheduling tools. A fully empowered AI agent could replace roles like scheduling clerks, dispatch coordinators, or executive assistants whose primary duty is managing the logistics of people and tasks. By entrusting scheduling and coordination to AI, governments ensure nothing is missed, and humans are not spending time on what is essentially a puzzle an algorithm can solve.

Monitoring and Surveillance Duties:

Certain public sector jobs involve watching for safety or rule violations, for example, security camera monitoring, road traffic monitoring, or reviewing compliance logs. AI vision and pattern recognition systems are increasingly adept at these tasks. An AI agent watching a network of CCTV feeds can detect unusual activities, such as someone climbing a fence at a closed facility or an object left unattended, and alert human security only when needed. This means one AI system can do the first-line monitoring that might take dozens of human security staff to accomplish in shifts. Similarly, AI can monitor network logs in cybersecurity roles, flagging anomalies in real time without a human staring at screens. Traffic enforcement cameras equipped with AI can identify violations, such as speeding or running red lights, and issue tickets automatically, reducing the need for traffic police presence in certain spots. While not every surveillance task should be fully automated, due to privacy and judgment concerns, a large portion of watchkeeping and detection work can be offloaded to tireless AI agents. Roles like toll booth operator, already largely phased out by electronic systems, and security monitor are clear examples where agents can take over.

It is important to note that for many of these areas, the technology exists now or will very shortly. Governments often lag behind the private sector in adoption, but the potential is proven. The above list is not exhaustive, but it covers many of the core tasks across federal, state, and local agencies. Any government job that consists mostly of following a set procedure or handling information in a predictable way should be evaluated for automation by AI. As AGI-level systems arrive, even more complex jobs, such as planning budgets, drafting legislation, or adjudicating routine legal cases, could be within reach of automation, but the low-hanging fruit today are the routine tasks outlined above.

Embracing an AI-Augmented Public Sector

It may sound severe to discuss shifting public sector jobs to automated systems. But the evidence shows this is both pragmatic and necessary. A portion of government employees are underutilized, as recent oversight of telework arrangements demonstrates. Current AI already performs many routine tasks better than people, and more advanced systems are on the horizon. Ignoring these facts does not serve taxpayers or the future workforce. Instead, public leaders should allow AI agents to handle what they do best—consistent, fast, error-free execution of defined tasks—and refocus human talent where it is most valuable, in roles requiring complex judgment, interpersonal interaction, or strategic thinking.

In practical terms, jobs that consist mainly of repetitive processing, checking boxes, or retrieving information are better done by agents, not people. This may mean eliminating certain job titles or reducing the number of staff in those roles. However, this follows a historical pattern: staff whose jobs are automated are not left irrelevant, but instead can be retrained and moved into roles that AI cannot do. For example, if AI handles all the data entry in a social services department, clerks might become case managers who interact directly with clients, providing the human touch that improves service quality. The long-term goal is not a future without public sector workers, but a redeployment of staff into positions where human capabilities truly add value.

To make this transition, government agencies should begin by auditing every role and task for AI suitability. Leadership should be transparent about which jobs and outputs could be performed by an algorithm. AccelNode continues to study federal jobs and the tasks they encompass.