Table of contents
Highlights
- Agencies are increasingly prioritizing AI tools that improve employee productivity and service delivery while still fitting into existing governance and procurement processes.
- The most useful government AI tools tend to connect to real workflows (ITSM, HR, identity, knowledge) and integrate with existing tech, rather than being standalone experiments.
- FedRAMP® readiness and clear answers on data handling and model training are practical filters for shortlisting AI vendors in federal and regulated public-sector environments.
- Responsible AI in government often comes down to choosing vendors with operational guardrails: role-based access, audit logs, human review for higher-risk actions, and records retention.
- A 90-day rollout plan that starts with low-risk employee support workflows can help you prove value early, improve adoption, and build momentum for broader modernization.
- Moveworks is designed to serve as the intelligent front door to work for government agency employees — connecting staff to IT, HR, and operations workflows through a single conversational interface, with role-based access controls, audit logging, and FedRAMP-aligned security built into the platform.
Government IT teams are being asked to modernize faster, support more employees, and improve service delivery — often without the staffing or funding to match.
The data backs this: in a 2025 survey on state and local government workforce trends, 44% of respondents reported having fewer qualified IT applicants than available IT positions in the past year — a clear capacity challenge for government IT teams facing rising service demand.
Moreover, despite pressure to modernize and onboard automation, a 2025 State CIO Survey indicates that only 48% received modernization funding and only 38% received innovation funding.
With dwindling talent pools and funding that falls short, artificial intelligence (AI) tools are emerging as a potential way for government IT teams to reduce repetitive requests and speed up support.
Even simple password resets and access requests can clog service queues, while onboarding workflows touch identity systems, Teams or Slack channels, service portals, knowledge bases, and case systems, requiring manual handoff across systems. But AI tools may help reduce these backlogs and speed support across IT and shared services.
Download the Successful AI Implementation guide for a step-by-step change management approach to launch, scale, and drive long-term AI adoption.
Why government agencies are turning to AI tools in 2026
Many government IT teams are already battling growing ticket backlogs. As the IT skills gap widens and agency leaders struggle to fill critical positions, those backlogs will likely only become harder to manage.
Meanwhile, the pressure to deliver faster employee and citizen services intensifies. Increasingly, citizens expect public services to be as fluid and easy to access as commercial digital experiences. Internally, employees have those same expectations.
Modernizing the mission and the back office, then, are two sides of the same coin:
- Mission modernization: Improving citizen-facing programs
- Back-office modernization: Improving internal systems that government employees use to deliver public services
While modernizing citizen services is important, back-office workflows create a drag that teams feel every day. Here, AI has the potential to help employees find answers and complete work more efficiently across disconnected systems.
Because many employee operations workflows are high-volume and low-risk, back-office modernization may also offer clearer, easier-to-measure ROI.
Still, finding the right tools is what makes the difference. To successfully move beyond pilots into real production, federal agencies are prioritizing tools that reduce fragmentation, integrate easily with existing tech, and meet agency-specific security, procurement, and audit requirements.
Public sector workers currently save only 3 hours a week with AI — half that of the private sector. Discover the Public Sector AI Growth Opportunity.
What counts as a government AI tool (and why it matters)
A government AI tool is software that applies AI capabilities to support agency workflows end to end — from data ingestion to control application to logged and auditable outputs.
For example, a document intelligence tool might automatically extract fields from a benefits form and then route that information to the correct queue with a logged rationale.
These tools can vary significantly, both in where they live and what they can do, but they generally fall into one of three categories:
Tool Type | Example |
AI features in existing platforms | Service desk tool that can draft responses |
Standalone point tools that solve one specific task | Transcription tool |
Workflow-connected AI assistants and agents that can search across systems and take multi-step actions | AI agent that intakes requests, routes for approvals, and logs the actions |
Government agencies, especially federal government, have to meet incredibly high standards of security. So no matter how impressive the vendor’s feature list, make sure you prioritize AI tools with clear security, access, integration, and audit controls.
It’s a careful balance: upholding robust security and compliance controls while giving employees quick, fluid service access.
That said, tools do vary by risk level. While all systems require governance controls, some tools (like employee support and summarization) carry lower risks than higher-impact tools (scoring or screening) that demand stricter governance.
Evaluate tools for security, compliance, and governance
The market is crowded with AI tools today, but you generally don’t want to move a tool into production unless you can verify these five functions through vendor docs and security reviews:
- Compliance readiness
- Governance controls
- Integration depth
- Operational readiness
- Use-case coverage
From there, a simple AI tool buyer’s checklist can support a more in-depth review:
- Permissions: Does the tool know who logged in? Or does it give all users the same level of access?
- Fitting in: Can it connect to your agency’s existing security, identity, ITSM, and knowledge tools?
- Proof of security: Does it provide real-time audit reports to prove safety?
When in doubt, many agencies defer to the buyer’s rule: If a vendor can’t explain where your dataset sits, then their tool likely isn’t fit for government environments.
Criteria 1: Keeping government data private
The most important question when evaluating AI tools for government use is: “Are our questions and documents being used to train future AI?” For government use, the answer must be “No.”
Data borders can also be a red flag. Even if a tool is hosted in the cloud, it’s ultimately stored somewhere — and that location must remain within protected, domestic servers.
An easy way to narrow down AI tool choices is to look for FedRAMP authorization, which means the solution has already proven that it meets standardized government approval for security and risk management controls. The experts have already done the rigorous testing, so your agency doesn’t have to start the security review from scratch.
Criteria 2: Securing “AI agents”
Unlike basic chatbots that simply fetch information and respond with pre-defined scripts, an AI agent is designed to perform multi-step tasks, like filing a request, looking up a record in a database, routing an approval, or updating a ticket.
These capabilities can make agents helpful for swamped IT teams, but that doesn’t mean they should have free rein of the agency network.
When evaluating AI tools, check for permission-aware access. AI agents shouldn’t have a “master” key for unfettered access to agency systems. Instead, think of them as extensions of employees — they should only be allowed to do what a specific human user is allowed to do.
Additionally, each agent action needs to be logged and auditable — that goes for every step in the workflow, not just the final one. This way, if something goes wrong, you can trace what the agent did, where it happened, and when logic failed.
Criteria 3: Supporting responsible and safe AI
While AI agents can help move work forward, there’s one role that needs to stay in human hands: final decision-maker.
For example, in workflows that determine who gets a loan, the tool should bring human experts into the loop for final approval. This human oversight should extend throughout implementation on an ongoing basis to regularly test for hallucinations and unfair bias.
Responsible and safe AI is also trackable AI. In government environments, conversations with AI agents are often considered official records and, per the Freedom of Information Act, are required to be saved for archival and future search.
See the top government AI tools at a glance
AI Tool Type | Example | Best-Fit Workflow | Typical Integration | Ideal Controls | Risk Tier |
Employee operations AI assistants | Employee support assistant that helps staff find answers, submits IT or HR requests, routes approvals, logs outcomes | IT, HR, finance | ITSM, HRIS, Teams/Slack | RBAC, approvals, logs | Low/moderate |
Document intelligence for forms and casework | Form extraction tool; case intake classifier; document routing assistant | Forms, casework | Document repositories | Redaction, PII handling | Moderate |
Translation and multilingual content tools | Translation engine; terminology-controlled content localization tool | Public-facing content, internal knowledge | Service portals, knowledge bases | Glossary/terminology controls | Low/moderate |
Transcription and meeting intelligence | Meeting transcription tool; action-item summarizer; searchable meeting notes tool | Project meetings | Teams, Zoom, Google Meet | Storage and retention controls | Low/moderate |
Analytics and anomaly-detection tools | IT anomaly detection tool; fraud signal detection tool; system health monitoring tool | Login spikes, system health | ITSM, identity, ERP | Thresholds, human validation | High |
The 5 government AI tools agencies are prioritizing
The vendor list is diverse and growing, but from a high-level perspective, these are the top five categories of government AI tools leaders may want to evaluate.
Employee operations AI assistants (IT/HR/internal services)
Accessible in web browsers, Teams/Slack, or service portals, AI assistants designed to serve employee operations can help government teams streamline support, particularly for IT, HR, and other internal services.
They can be especially useful for high-volume, lower-risk workflows, such as:
- Password resets
- Access requests
- Software requests
- Policy Q&As
- Onboarding checklists
- Knowledge retrieval, like “Where do I find the remote work policy?”
Compared to standalone chat tools that just respond to queries, AI assistants that connect to agency systems are built to support full operational workflows.
When deployed to answer employee questions, submit requests, route approvals, and trigger end-to-end workflows, AI assistants have the potential to increase ticket deflection and speed up resolution.
Document intelligence for forms and casework
U.S. government operations often require form-heavy work, like processing applications and triaging casework. Document intelligence AI tools may help by supporting extraction, classification, and routing.
Example workflow:
- Extract key fields
- Validate required information
- Route to correct case system
- Generate a summary for review
They can be a useful fit for stretched-thin government teams managing high-volume intake. With an AI tool that can support validation and routing, teams often see reduced manual re-keying and queue misroutes that slow workflows.
Like all government tools, governance controls play an important role here. For document intelligence specifically, AI tools need capabilities for redaction, PII handling, human review thresholds, and audit trails.
Translation and multilingual content tools
From emergency updates to benefits instructions, government agencies are responsible for creating and maintaining extensive libraries of public-facing content.
To support accessibility and help constituents access public services, agencies need reliable ways to translate public-sector content — and that includes the knowledge articles employees rely on for internal support. Those use cases are where AI-driven translation and multilingual content tools are designed to slot in.
Example workflow:
- Translate outage communications or benefits instructions
- Apply glossary rules
- Publish via an approved content workflow
Governance-wise, agency leaders should look for glossary/terminology control, secure handling of sensitive content, and clear retention policies. For high-stakes messaging that concerns safety, healthcare, legal rights, or other sensitive information, AI-generated or translated content should also include human review before publication.
Transcription and meeting intelligence
Meetings can drain time, focus, and productivity. But when integrated directly into familiar environments (like Teams, Zoom, or Google Meet), AI platforms can serve as meeting assistants, bringing more order and alignment.
These AI solutions are built to help teams with tasks like:
- Summarizing an incident review
- Generating meeting transcripts
- Capturing action items and owners
- Turning discussions into searchable notes
- Linking next steps to a ticket or case record
To protect data privacy, transcription and meeting intelligence tools should support consent and notification policies and provide clear classification for sensitive sessions. Additionally, in accordance with FOIA, agencies need tools that can retain transcripts for future search and review.
Analytics and anomaly-detection tools
The intricate systems that keep government services running require constant attention and upkeep. IT teams use analytics and anomaly-detection tools to help them detect potential issues earlier in areas like system health, usage, or procurement patterns, such as unexpected traffic spikes or spend increases.
These tools may also support fraud detection by flagging unusual patterns for review, like a spike in password resets.
Anomaly detection typically works best paired with human validation. When a pattern crosses a defined threshold, the tool should pass the issue off for human review, validation, and next steps.
Example workflow:
- Detects an unusual spike in password resets
- Routes the alert to a security operations workflow
- Triggers human review for validation before escalation
The higher the workflow’s impact, the greater the risk — and the more governance controls AI models need to review steps and ensure explainability.
Avoid pitfalls and run a 90-day rollout
Selecting AI systems that meet security and workflow requirements is the first step to successful implementation, but it’s not a straight line from procurement to adoption. After selecting tools, agency leaders need to carefully manage rollout and expansion.
A common mistake is focusing heavily on tool selection, then underinvesting in implementation, but that’s ultimately where success happens. The most successful agencies typically focus on:
- Setting up governance intake to review new workflows before they go live
- Prioritizing low-risk workflows that are high volume and measurable
- Instrumenting measurable outcomes to track the tool’s success
- Planning a phased rollout to test and expand based on real-world learnings
Common pitfalls: Shadow AI, legacy integration gaps, and adoption challenges
In a survey of nearly 500 senior government executives, more than half recognized the importance of AI adoption for cost savings (64%) and improved service delivery (63%). Nonetheless, only one quarter (26%) have integrated AI technology across their organization.
Legacy complexity often gets in the way. Agency knowledge is spread across multiple repositories, workflows span four different legacy systems, and approvals have to route to a different platform for every department. AI implementation can also fail when tools add more steps instead of removing them.
Avoiding these and other common challenges ultimately comes down to a combination of change management and the right solution.
Pitfall | What happens | The fix |
Shadow AI | Employees use unapproved AI-powered tools, risking sensitive data leakage. | Publish approved-tool guidance. |
Integration gaps | Agencies onboard AI tools, but workflows remain clunky because the tools can’t connect with existing agency systems. | Prioritize tools with secure APIs and plugins. |
Adoption challenges | Adoption stalls because employees don’t understand how AI tools support internal workflows and service delivery. | Provide employees with AI tool training. |
90-day rollout plan: pick low-risk workflows, set an intake process, and instrument logging/feedback
A government AI rollout should start focused and only scale when success is measured and clear. For example:
- Weeks 0–4: Select 2–3 workflows to start with.
- Weeks 5–8: Integrate with existing identity, ITSM, and knowledge systems.
- Weeks 9–12: After reviewing usage and feedback, expand to adjacent workflows.
When expanding AI in government, you generally want to avoid ad hoc rollouts. Consider a controlled intake process to evaluate new workflows before launch: request form, risk tier, owner, test plan, and sign-off.
From the outset, keep a close eye on relevant metrics to help monitor performance and adoption, such as:
- Deflection rate
- Mean time to resolution (MTTR)
- Handoff rate to humans
- Top intents
- Audit completeness
Modernize government agency workflows with Moveworks
Like enterprise organizations, government agencies are facing pressure to modernize, but they often lack the staffing and funding to do so quickly and effectively. AI tools, when appropriately secure and designed for government use, can help move work forward with the right controls in place.
Together, Moveworks AI Assistant and Agent Studio are designed to integrate with legacy ITSM, identity, and knowledge systems to help unify employee search and action across departments.
Rather than adding another disconnected AI tool that may introduce new security risks, Moveworks supports configurable agents that extend workflows by coordinating across systems and using plugins and APIs for action.
For IT teams managing heavy service desk loads, Moveworks is built to help reduce repetitive support work while maintaining oversight, logging, and access controls. Backed by FedRAMP Moderate Authorization, the platform gives government agencies a verified path to secure, governed AI deployment.
Learn more about Moveworks, the FedRAMP Moderate authorized front door to work platform that supports secure, agentic AI for government missions at scale.
Then connect with an expert to learn how Moveworks can help securely modernize services for your sector of government.
Frequently Asked Questions
Agencies often use AI tools for practical workflow support, such as document processing, translation, transcription, analytics, and employee support. In many environments, teams start with lower-risk use cases like summarization and internal knowledge retrieval, then expand as governance matures. The most sustainable deployments typically connect AI to real systems of record so outputs and actions can be logged and reviewed. Over time, agencies may standardize on a small number of approved tools to reduce shadow AI.
State and local teams often focus on high-volume, time-sensitive work like form intake, multilingual communications, meeting documentation, and internal support for staff in the field. Some tools can help route requests to the right queue, reduce manual data entry, or make information easier to find. Many programs also prioritize accessibility and language coverage, which can make translation and content tooling especially relevant. The best-fit use cases usually have clear owners, measurable cycle-time goals, and defined review steps.
Trustworthy AI generally refers to AI that’s used with reliability, oversight, and accountability in mind, especially where outcomes affect people or public services. In practice, that can include human review for higher-risk outputs, audit logs, test plans, and ongoing monitoring. In government IT, it also tends to mean clear data handling rules, role-based access, and the ability to document how the tool was configured and used. The goal is to support modernization while sustaining public trust.
Many teams look to resources and frameworks from organizations like NIST, as well as government guidance hubs such as Digital.gov and GSA, to shape internal policies and evaluation criteria. These frameworks can help you define risk tiers, required testing, monitoring expectations, and documentation practices. They also support consistent vendor questions about data handling, retention, and auditability. In practice, agencies often translate these into procurement checklists and implementation guardrails.
Common risks include sensitive data exposure, unclear accountability for AI-assisted decisions, model errors or bias, and inconsistent records retention. IT can mitigate these risks by standardizing approved tools, enforcing SSO and role-based access, requiring audit logs, and establishing human review for higher-impact workflows. It also helps to establish an intake process that scopes, tests, and monitors new use cases before scaling. A phased rollout can make it easier to demonstrate value while maintaining controls.
