The public demand for transparency has never been greater, and agencies are drowning under the strain of unorganized legacy data. This is why FOIA modernization increasingly hinges on in-place data management: governing and accessing unstructured data where it lives, rather than trying to move or copy it.
The Freedom of Information Act remains one of the federal government’s most important transparency mechanisms. Today, the system designed to provide public access to records is under increasing strain. In fiscal year 2024, FOIA requests surpassed 1.5 million, representing a 25% increase from the year prior. Agencies processed nearly as many requests, but that total includes cases carried over from previous years as backlogs persist going into 2026.
At the same time, expectations for transparency continue to rise. Journalists, advocacy groups, and the public increasingly expect faster responses and broader access to records, even as agency staffing declines and budgets tighten. The result is a growing gap between FOIA demand and the government’s ability to deliver.
Why FOIA Backlogs Persist
According to a March 2024 report by the Government Accountability Office (GAO), FOIA backlogs have grown steadily over the past decade. Staffing shortages remain widespread, while the nature of FOIA requests has grown more complex as agencies manage expanding volumes of unstructured data across emails, documents, collaboration tools, and legacy systems. Most modern discovery and analytics tools assume data can be migrated or re-platformed, an assumption that breaks down in federated government environments.
Key contributors to persistent FOIA backlogs include:
- Widespread staffing shortages within FOIA offices
- Increasingly complex, multi-system requests
- Explosive growth of unstructured data
- Outdated and siloed technologies that slow discovery and review
The GAO report explicitly identified outdated and limited systems as a major barrier to FOIA efficiency. Recent governmentwide layoffs have further intensified the challenge. In several major agencies – such as the CDC, NIH, and FDA – entire FOIA teams were eliminated, yet statutory requirements and penalties for non-compliance remain firm, accelerating reliance on technology rather than manual review.
The Modernization Gap
Lawmakers have increasingly acknowledged that FOIA reform cannot be solved through staffing alone. Senators Chuck Grassley and John Cornyn have pointed to the government’s continued reliance on what Cornyn described as “archaic computer systems.” These fragmented tools make it difficult for FOIA offices to collaborate internally and nearly impossible to respond efficiently at scale.
The Department of Health and Human Services has stated that public records offices were siloed and not effectively communicating across the department, reflecting a broader truth: today, FOIA compliance is inseparable from digital capability and data readiness. This challenge is being addressed as part of FY2026 “Mission Critical” priorities, including data, AI, and system consolidation initiatives such as the GSA’s OneGov Strategy, which seeks to standardize IT tool procurement. In-place management supports this vision by allowing agencies to standardize access and oversight without forcing data migration into a single system.
AI in FOIA Processing
Interest in artificial intelligence and automation has grown as agencies search for scalable solutions. “In our digital era, the government must adapt to serve its citizens,” Grassley noted, emphasizing the need for modernization to maintain transparency.
The Chief FOIA Officers Council has explored AI through pilots and working groups focused on improving request triage, search, and review. While still emerging, AI-assisted workflows show promise in several areas:
Potential AI-enabled FOIA benefits include:
- Rapid identification of relevant phrases and keywords across massive document sets
- Improved usability of electronic FOIA reading rooms
- Faster review cycles for complex requests spanning multiple systems
Without in-place access to governed unstructured data, these AI capabilities remain theoretical rather than operational. Advocates argue that AI and automation can significantly reduce the human-intensive nature of FOIA processing, but only if deployed on top of strong data foundations.
In-Place Data Management: Connecting the Pipes
Rather than copying or migrating vast amounts of information into new repositories, in-place management allows agencies to govern and act on unstructured data where it resides, across emails, documents, collaboration tools, and legacy repositories.
In-place works by extracting and indexing the “essence” of every document—metadata and content—without copying or moving the original file. High-value documents, such as contracts, can still be selectively archived, but the majority of data remains in its source location. From a unified platform, agencies can execute governance functions like:
- Records management: classification, retention, and defensible deletion
- Policy enforcement: automated tagging aligned with regulatory requirements
- Risk management: remediation of sensitive information and elimination of redundant, obsolete, trivial (ROT) files
- Flexibility: rapid reclassification and policy updates without re-indexing
This approach reduces storage costs, lowers compliance risks, and ensures agencies can “connect the pipes” between disparate systems to centralize access while preserving data security and compliance. In-place management also enables curated datasets for AI, improving model accuracy, reducing risk, and making institutional knowledge accessible without manual intervention.
Why Automation and IG Must Come First
Agencies cannot successfully apply AI to FOIA if their data remains scattered, unindexed, duplicative, or trapped inside legacy repositories. In these flawed environments, AI tools risk amplifying inefficiencies rather than eliminating them.
In-place, unified information governance—auto-classification, centralized access, and global search—forms the foundation for scalable FOIA operations. The GAO notes that consistent systems across repositories can “streamline coordination and document reviews,” reinforcing the need for unified environments before layering AI on top.
At a minimum, agencies need:
- Centralized visibility across unstructured data
- Automated classification to reduce manual sorting
- Global search across repositories to accelerate discovery
Preparing for AI-Enabled FOIA Workflows
Any AI system intended to support FOIA will require high-quality, well-curated datasets. Agencies exploring fine-tuning or domain-specific models must be able to reliably prepare training data that reflects real-world FOIA scenarios.
That preparation depends on the ability to:
- Locate relevant records across disparate repositories
- De-duplicate, classify, and organize large volumes of data
- Assemble complete, representative datasets for training and validation
Robust global search capabilities and automated classification directly influence model accuracy, auditability, and compliance with FOIA and the Federal Records Act.
Enabling Government Transparency
Legal and compliance experts increasingly view modernization as an efficiency multiplier:
“The kind of ironic thing is, having the best technology is not going to be a financial burden on these agencies. In many ways, it makes employees more efficient. It makes the processes more efficient.”
Daniel Epstein, St. Thomas University College of Law
By investing in modern information governance, agencies can meet both FOIA and Federal Records Act obligations without reactive scrambles for documents. More broadly, unified data platforms and automation help agencies build resilience. They reduce dependence on manual labor, support continuity during staffing disruptions and political transitions, and allow agencies to respond more effectively to request surges.
Recap: Data Governance is the Key to FOIA Success
FOIA transparency is fundamentally a data problem. With request volumes accelerating and resources shrinking, agencies need centralized systems capable of rapid global search, automated classification, and consistent record stewardship. Agencies that invest in unified, in-place information governance gain:
1. A solid data foundation first
- In-place, accessible, governed, and indexed unstructured data
- Automated classification and global search for speed and compliance
- Mitigation of risk from sensitive data spillage
2. Strong AI outcomes in FOIA
- Faster, more accurate identification of relevant records
- Improved usability of electronic reading rooms
- Reduced human-intensive review cycles
3. Broader benefits of unified IG
- Compliance with the Federal Records Act and other obligations
- Resilience to staffing changes, political transitions, and surges in requests
- Foundation for future AI enhancements and broader mission readiness
- Ability to break down silos and safely “connect the pipes” between systems and agencies
Automation and strong information governance address today’s backlogs while preparing agencies for the AI-enabled workflows of tomorrow. Agencies that modernize now will be best positioned to meet rising transparency expectations, improve operational efficiency, and strengthen public trust.
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