Updated: June 15, 2026

Freedom of information (FOI) requests are a vital pillar of democratic public administration, giving citizens, journalists, researchers and civil society organizations a formal channel to request government-held information.

But governments worldwide are finding these public records requests increasingly difficult to fulfill. For example, the US government received more than 1.7 million FOIA requests in FY 2025, while backlogs across major federal agencies rose nearly 27% as full-time FOIA staffing fell 16%.

These backlogs strain public resources, frustrate citizens, and weaken a core mechanism of government transparency. This is where AI can help. Processing FOI requests involves interpreting natural-language submissions, searching fragmented systems, classifying documents, identifying sensitive material, and preparing records for release — all tasks where AI can support faster, more consistent workflows.

In particular, AI agents can be used to enhance the agility and responsiveness of FOI systems, helping reduce processing times, enabling record officers to handle more cases, and lowering error rates. Agentic platforms, like North, can be deployed privately and securely, addressing a key concern for agencies adopting AI in public administration.

Governments we work with are actively exploring the use of AI to enhance nearly every aspect of the current FOI process, from triaging requests to assessing their sensitivity and completeness, to retrieving records.

Current FOI bottlenecks in public administration

The basic premise of FOI laws is simple: If you ask to see a government record, the government has to either show it to you or give a legally valid reason for keeping it secret.

Unfortunately, the reality of public access often falls short of this standard. Backlogs and delays are an issue in many jurisdictions that maintain FOI or public records laws, and the slow pace of access blunts their effectiveness as tools for accountability.

There are many reasons for this slow pace, but understaffing and reliance on manual processes are two of the most persistent constraints. Faced with competing demands and limited resources, agencies often struggle to prioritize FOI, leaving requesters waiting longer for access to public information.

How long does it take to process a FOIA request?

In the US, the average processing time for simple-track FOIA requests was 44 days in FY 2024, up from 39.4 days in FY 2023.

Complex requests typically take longer since they often involve larger record volumes, searches across multiple locations, or consultations with other agencies. In FY 2024, only 80.66% of complex requests were processed within 100 days.

How the process currently works (without AI)

Most FOI systems start with a portal where members of the public can submit FOI or public records requests. While some countries have a single portal, others, such as the United States, maintain separate intake systems for each agency, resulting in fragmented intake processes and uneven routing between record offices. Even where systems are unified on the front end, each department typically manages its own records and maintains its own public records officer for handling requests.

From there, each request is assigned to a specific officer who communicates directly with the requester. Often, there are particular notification requirements (e.g., when a request is received or when a certain amount of time has passed), but communication is typically handled manually through email or phone calls. The officer may sometimes propose modifications to the request, narrowing it in ways that result in faster fulfillment or fewer extraneous records; however, these modifications must be approved by the requesting party in advance.

The biggest pain point is redaction. Once relevant documents have been assembled, records officers must review them carefully to remove trade secrets, classified information, or other sensitive material. Since this review is typically performed manually, requests that span hundreds of pages can become highly labor-intensive.

How AI can transform the FOI process

The good news for governments struggling to meet public transparency expectations is that FOI workflows align closely with AI’s strengths.

A significant portion of handling each FOI request involves repetitive, rule-based tasks, such as reviewing emails, memos, and reports to identify relevant documents and verify them against statutory exemptions. But even when the rules are clear, applying them can be difficult because relevant information is rarely stored in one neat, searchable place.

For example, one common FOI request asks for communications involving a specific office holder during a defined period, related to particular keywords or subject matter. While the phrasing of the request may be simple, it could involve collating records from half a dozen different systems over the course of years. It’s the kind of request that can be frustrating, tedious, and time-consuming to perform manually.

AI can help with this early discovery work by translating broad written requests into structured search logic, applying that logic across fragmented systems, and giving records officers a focused set of relevant materials to review. Models can also be trained or tuned on historical requests, agency guidance, and past FOI review decisions. This allows them to better recognize common request patterns and account for jurisdiction-specific redaction and exemption rules.

The result is an AI-supported workflow that keeps records officers in control. The goal of AI in public input processes like FOI is not to automate disclosure decisions end to end, but to give records officers better starting points for review. Once they receive machine-generated results, officers can refine, validate, and approve them before any records are released, preserving the human judgment required for responsible government transparency.

Security controls are just as important. Since FOI workflows can surface sensitive or exempt material before final disclosure decisions are made, AI systems need to operate inside secure, access-controlled environments. Governments can run AI-powered FOI systems through private deployments to ensure the data accessed by the model doesn’t leave the agency’s secure environment. Permission and access controls can also create clear boundaries between departments, roles, and job functions.

Deploying AI agents across FOI workflows

Agentic AI systems can be tailored to specific tasks and existing FOI workflows while ensuring that data and sensitive information remain within the appropriate departments. Together, these agents can support the core workflows of a modern FOI or FOIA request management system.

With human oversight and authentication reviews, AI agents can perform assigned tasks for different stages of a workflow. Consider, for instance, how a records department could use specialized or fine-tuned agents to manage each of the following tasks:

AI agent for department routing and triage: Records requests often require manual routing to the relevant departments for processing. A workflow-embedded agent could automatically identify the appropriate departments and recommend interdepartmental consultations as needed. Over time, it could also help teams adjust the overall routing system to optimize processing time.

AI agent for sensitivity assessment: Records vary significantly in their sensitivity, and much FOI work involves determining which requests or records are sensitive enough to warrant additional oversight. An AI agent could assess sensitivity based on previous decisions and flag potentially sensitive requests in advance, giving departments far greater flexibility in how they handle more delicate records. The same AI agent could also flag records that may be exempt from disclosure, based on the relevant jurisdiction’s laws.

AI agent for clarification and information gathering: Records requests are often ambiguous, requiring labor-intensive clarifications between the requesting party and the records officer. These clarifications typically address the scope of the request, including whether it should be time-gated or otherwise limited. (As veteran requesters know, getting thousands of pages of redacted or unresponsive documents can be worse than getting no response at all.) An embedded agent could be explicitly tailored to assess the completeness of the request and draft or recommend any necessary clarifying questions.

AI agent for record search and retrieval: A more advanced AI agent could be deployed for the search and retrieval of records, automatically converting natural-language requests into structured queries. Instead of starting from scratch, records officers could begin each request with a pre-filled selection of relevant documents, then review, validate, select, and redact documents before release. The same worker could handle many more requests, enabling agencies to make significant progress in reducing their backlogs.

In each case, the agent could be configured, tested, and refined against real FOI workflows to learn the nuances of how they are processed. By being embedded in workflows in this way, the agent can learn not only the unique demands of the task but also the unique practices of each workplace.

This agent-empowered system could produce major productivity gains across the FOI process. We estimate processing times could be cut by 50-75% while records officers would be able to handle 2-3 times more requests than in current systems. Errors in redaction and document discovery could also fall by around 30-50%. These improvements could enable departments to reduce backlogs by an estimated 40-60% within a year of implementation.

See the visual below for the entire workflow.

A gateway to wider government AI

Governments face a unique set of challenges around implementing AI, including the need to win public trust in the technology.

Overwhelmed FOI request systems represent a powerful opportunity to show how AI can deliver tangible improvements to a vital citizen service without undermining privacy, security, or accountability. If implemented successfully, FOI modernization can open the door to broader AI use cases across government by showing that agencies can use AI to improve responsiveness in complex, process-heavy public services.

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Rohit Kurhekar

Solutions Architect at Cohere