Donald Gainsborough has spent years at the intersection of bureaucratic efficiency and legislative foresight. As the leader of Government Curated, he has become a pivotal voice in translating complex federal mandates into actionable strategies for the modern workforce. Today, we delve into the nuances of the National Archives and Records Administration’s recent stance on artificial intelligence, exploring how the shift toward automated systems is redefining the very definition of a “federal record” and what this means for accountability in 2026 and beyond.
The discussion focuses on the contextual boundaries of record creation as defined by the Aug. 21 memo, the transformative nature of audit trails during official investigations, and the strategic collaboration required between IT and legal stakeholders to govern emerging technologies.
How should federal staff distinguish between casual AI experimentation and materials that officially document a decision?
The distinction lies primarily in the intent and the lifecycle of the information within the agency’s workflow rather than the technology itself. According to the guidance released in the Aug. 21-dated memo, the mere act of using an AI platform does not automatically trigger the Federal Records Act. For example, if a staffer uses a tool for preliminary research on a work-related white paper but ultimately leaves those specific outputs out of the final report, those searches remain outside the scope of official records. However, the moment that material is circulated among others or integrated into an agency system to conduct official business, it crosses the threshold into a formal federal record that must be preserved.
In what ways does the use of internal audit trails within AI systems complicate or clarify the responsibilities of an agency under the Federal Records Act?
It is a common misconception that every digital footprint left on a government device constitutes a permanent record. NARA has clarified that while an agency might maintain an audit trail of every employee action within an AI system, that trail doesn’t become a record simply by existing. The status changes significantly if the agency decides to capture that data to conduct a formal investigation or use it as evidence in official business. This means the transition from a technical log to a federal record is defined by the agency’s active choice to use that data as a tool for governance or oversight.
Given that commercial tools like Gemini and ChatGPT are frequently used for government tasks, how should agencies navigate the risks of these platforms not being inherently classified as federal records?
While the current guidance suggests that uses of commercial AI programs are likely not considered federal records, the burden of determination remains with the individual agency. Each organization must evaluate whether the inputs or outputs from these commercial platforms are being used to conduct official business or if they are merely being utilized for non-essential tasks. Because there is no universal “one size fits all” standard, agencies are encouraged to build specific guardrails that prevent sensitive decision-making data from being lost in a third-party interface. It is essential to remember that even if the platform is commercial, the resulting decision it helps shape is very much an official record.
What role does cross-departmental collaboration play in ensuring that new AI policies reflect the complex requirements of federal records management?
Building a robust AI policy is not a task that a single department can handle in isolation, which is why the guidance emphasizes a collaborative approach. Agencies are advised to bring together legal experts, information technology specialists, and other relevant stakeholders to ensure that recordkeeping isn’t an afterthought in the digital transformation process. By involving these diverse perspectives, an agency can move away from generic models and create a nuanced framework that respects both innovation and archival law. This ensures that as we move forward, the systems we build are legally sound, transparent, and capable of maintaining the integrity of federal functions.
What is your forecast for the future of federal recordkeeping as AI becomes even more integrated into daily operations?
I anticipate a shift where the human intent becomes the primary filter for what constitutes a record, placing a much higher premium on the training of federal employees. As these AI systems become more autonomous, the definition of “creation” will likely expand, forcing agencies to implement even more granular internal policies to stay compliant. We will see a move toward integrated record management requirements where AI outputs are tagged and categorized at the moment of generation to reduce the administrative burden on staff. Ultimately, the focus will remain on the impact and use of the data rather than the specific software used to produce it.
