Over the last few months, I have witnessed AI become increasingly prominent in the workplace.

It has become clear to me that AI is rapidly transforming how government operates. With that transformation comes a new and expanded set of responsibilities.

FOIA, records management, and privacy are not just technical functions. They are the foundation of transparency, accountability, and public trust.

AI is changing how each of these programs functions—and raising new questions that agencies must be prepared to answer.

FOIA: New Challenges in Discoverability and Transparency

AI is introducing new types of records and decision-making processes that must be accounted for under FOIA.

AI-Generated Records and Outputs
Algorithmic outputs, automated decisions, and machine-generated content may all be considered records. Agencies must determine how these outputs are captured, stored, and made retrievable.

Discoverability and Traceability
FOIA depends on the ability to locate records. AI systems must be designed so that their outputs are searchable, traceable, and responsive to public requests.

Explainability and Accountability
As AI influences decisions, agencies must be able to explain how those decisions were made. Transparency now extends beyond documents to include algorithms and models.

Records Management: Rethinking the Lifecycle of Information

Traditional records management frameworks were not designed for the complexity and volume of AI-generated data.

Dynamic and Evolving Records
AI systems continuously generate and update data. This challenges traditional definitions of what constitutes a record and when it becomes final.

New Classification and Retention Models
Agencies must develop new strategies for classifying and retaining machine-generated content, including logs, training data, and outputs.

Preservation and Retrieval
Ensuring long-term access to AI-related records requires new approaches to storage, indexing, and retrieval.

Privacy: Expanding the Scope of Data Protection

AI significantly expands how personal data is used and interpreted.

Inference and Profiling Risks
AI systems can infer sensitive information, even from non-sensitive data. This creates new privacy risks that go beyond traditional data collection practices.

Understanding Data Use, Not Just Storage
Privacy is no longer limited to how data is stored. It now requires understanding how algorithms process, analyze, and derive insights from that data.

Strengthening Safeguards
Agencies must implement stronger governance controls to ensure that AI systems use personal data ethically and in compliance with privacy laws.

AI Expands Responsibility, Not Reduces It

AI does not simplify information governance.

It expands it.

It introduces new layers of complexity that require agencies to rethink how they manage transparency, accountability, and data protection.

This means:

• Designing systems that capture and preserve AI-generated records
• Ensuring algorithmic decisions are explainable and auditable
• Embedding privacy protections into AI development and deployment
• Aligning governance frameworks with evolving technologies

Building Governance for the Future

Innovation cannot outpace accountability.

As AI continues to evolve, government must develop governance models that evolve with it.

We need systems that are not only intelligent, but also:

• Ethical
• Transparent
• Accountable
• Citizen-centered

Because at the end of the day, the goal is not just to modernize government operations.

It is to ensure that as technology advances, public trust is not left behind.