State and Local Government Records Management Evolves with AI
Records management in state and local government has evolved beyond a purely administrative role. It now plays a key role in supporting transparency, compliance, and public trust. As agencies adopt cloud platforms and explore AI, records programs are expected to modernize without adding risk. At the same time, teams are managing increasing volumes of digital records across more systems, often with limited resources, while still needing to remain compliant and defensible.
Key takeaways
- Modern records programs must support transparency, compliance, and operational efficiency — not just retention requirements and schedules.
- AI and cloud technologies can improve records management, but only when governance and auditability are built in.
- Agencies that treat archives as strategic infrastructure are better positioned to meet FOIA, legal, and public accountability demands.
The evolution of records management
If you manage records in state or local government, the role likely looks very different today than it did even a few years ago. What once centered on paper files and storage rooms now involves overseeing digital records of email, text messages, collaboration applications, and social media interactions.
As communication channels expand and public scrutiny increases, records management has become more complex and more visible. Your responsibility extends beyond retention schedules to ensure records are captured automatically, governed consistently, and preserved in a way that stands up to audits, public records requests, and legal review.
The fundamentals of accountability and transparency remain constant. The environment in which you apply them continues to evolve, which is why future-focused public records management software is so important to government recordkeeping and FOIA requirements.
What to know about modern records management
Today’s records programs operate in a far more complex environment than even a few years ago. Volume, velocity, and system sprawl have changed what good looks like.
AI‑assisted classification and metadata
AI tools can scan content, suggest classifications, apply metadata, and route records more consistently than manual processes. For agencies facing backlogs or inconsistent filing, this improves efficiency and defensibility.
Explainability and auditability matter
When AI influences records decisions, agencies need to be able to explain and defend outcomes. Records managers need visibility into how classifications, retention, and exceptions are applied, especially as federal AI guidance continues to evolve.
Cloud‑native records lifecycle management
Moving to the cloud doesn’t eliminate recordkeeping obligations. It simply changes where risk resides. Public records requirements, retention policies, metadata capture, and governance controls still apply, regardless of where data is stored. To avoid audit findings or public records missteps, these controls should be built into systems from day one rather than layered on after issues arise.
AI touches records decisions; agencies must be able to explain and defend the outcomes. With evolving federal guidance and executive actions related to AI use, explainability, auditability, and documentation are now essential. Records managers must be able to demonstrate how AI systems classify records, apply retention schedules, and handle exceptions.
💡 Tip: If AI is involved in records decisions, be able to demonstrate how it classifies records, applies retention schedules or handles exceptions.
Considerations for modern records management
Below are practical advantages and tradeoffs to guide decision-making.
Potential benefits
Automation can significantly reduce the manual burden of classifying, tagging, and retaining records. This allows staff to spend less time on repetitive review tasks and more time on higher-value initiatives that support service delivery and transparency.
Modern platforms can also strengthen public records response processes by centralizing search and preserving defensible audit trails. As cloud adoption expands, these tools improve visibility into where records reside and how retention and governance policies are applied across systems.
Potential challenges
Modernization also introduces new considerations. AI-driven tools require clear governance frameworks. Without intentional configuration, retention and preservation controls can fall short. Successful adoption ultimately depends on training and change management to ensure the technology delivers lasting value.
In addition, records of lifecycle management must begin with system design. If retention and metadata management aren’t built into the system from the start, agencies may struggle with public records requests or audits when those occur.
Discover how state and local governments are managing social and mobile apps and collaboration.
When does modern records management make sense?
Modern approaches make sense for agencies:
- Managing large volumes of digital communications
- Operating across multiple cloud platforms
- At risk of facing increasing FOIA, litigation, and audit pressures
Modern recordkeeping systems are especially valuable when legacy, manual processes can no longer keep pace with growth or public accountability demands.
When modern records management may not be the best option
Highly automated or AI‑driven approaches may not be appropriate where governance frameworks, documentation, or staff oversight are not yet in place. Agencies with unresolved data ownership, retention authority, or regulatory constraints should address those fundamentals first to avoid compounding risk.
💡 Tip: Simply mirroring technology trends won’t fix inefficiencies. It’s important to understand what AI can do, its limitations, and how it would fit into the records management process.
Alternatives to modern state and local records management platforms
Manual or decentralized approaches
Relying on staff‑driven filing and department‑level tools offers familiarity and a low barrier to entry, especially for smaller teams. However, these approaches depend heavily on institutional memory and employee consistency, which opens the agency up to risk when there’s staff turnover. As record volumes and channels grow, manual processes often cause delays, inconsistent metadata, and defensibility gaps that are difficult to correct after the fact.
Point solutions
Single‑purpose tools are great at solving specific needs — such as e‑discovery, redaction, or content management — without requiring a full platform overhaul. However, multiple point solutions can create record silos and governance gaps over time. This increases integration and administrative overhead, and obscure end‑to‑end lifecycle visibility. Without strong coordination, these tools can create silos that complicate retention enforcement, audits, and cross‑system discovery.
Ensure your next technology decision is structured, defensible, and aligned with mission-critical goals with this check list.
What to do next
Modern records management is about sustaining trust in a digital environment, not just storing information. Agencies should evaluate where unmanaged risk exists today, prioritize systems with built‑in lifecycle controls, and pilot automation in controlled, defensible ways.
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Bill is a frequent speaker at legal and information governance industry events and has authored four eBooks including Email Archiving for Dummies, Cloud Archiving for Dummies, The Bartenders Guide to eDiscovery and the Know IT All's Guide to eDiscovery. Bill has also authored 60 plus industry articles and hundreds of blogs as well as hosting 37 podcasts with industry pundits, subject matter experts, state legislators, and attorneys.
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