What is this course about?
Public records law was not written with conversational AI in mind, and agencies are creating records they have not classified. This course covers when an AI interaction becomes a record, what has to be retained, how to respond to a request that reaches an AI system, and litigation hold across an agent's memory and logs.
Who is this course for?
- Records management officers
- FOIA and public records officers
- Agency counsel
- IT staff supporting records systems
What do I need before starting?
- Familiarity with your agency's records schedule
- No technical background required
What will I be able to do afterwards?
- Determine when an AI interaction constitutes a public record
- Classify prompts, outputs, and logs against your records schedule
- Respond to a records request that reaches an AI system
- Apply exemptions correctly in an AI context
- Execute a litigation hold across an agent's memory and logs
What does each module cover?
When does an AI interaction become a record?
40 minApplying the records definition to prompts, outputs, and the conversation between them.
Objectives
- Apply the records definition to AI interactions
- Distinguish records from transitory material
- Identify the interactions your agency is not capturing
Topics
Activity. Classify twenty AI interactions from your agency against the records definition.
What has to be retained, and for how long?
45 minMapping AI-generated material onto an existing records schedule.
Objectives
- Map AI material to schedule items
- Identify where the schedule has no applicable item
- Propose schedule amendments
Topics
Activity. Map AI material to your schedule and identify the gaps.
How do you retain a conversation?
45 minThe practical problem of retaining conversational records in a searchable, producible form.
Objectives
- Design conversational record capture
- Ensure records are searchable and producible
- Handle attachments and retrieved context
Topics
Activity. Capture a conversation as a record and verify you can search and produce it.
How do you respond to a request that touches AI?
50 minSearch, review, and production when responsive material lives in an agent's history.
Objectives
- Search AI systems for responsive records
- Review AI-generated material for exemptions
- Produce in a usable format
Topics
Activity. Run a mock request end to end against an AI system's history.
How do exemptions apply to AI-generated material?
45 minDeliberative process and other exemptions when the deliberation involved a machine.
Objectives
- Apply deliberative process to AI drafts
- Handle personal information in prompts
- Document exemption reasoning
Topics
Activity. Apply exemptions to a set of AI-generated drafts and document the reasoning.
How do you execute a litigation hold on an agent?
45 minPreservation across model context, memory, logs, and retrieval indexes.
Objectives
- Identify everything requiring preservation
- Suspend automated deletion across all stores
- Document the hold defensibly
Topics
Activity. Execute a mock hold and verify deletion is suspended in every store including indexes.
Should a document say an AI helped write it?
40 minDisclosure of AI involvement in public-facing documents, and where policy is unsettled.
Objectives
- Determine when disclosure is required or advisable
- Draft disclosure language
- Handle the unsettled areas honestly
Topics
Activity. Draft your agency's AI disclosure policy for public-facing documents.
Building the retention and request workflow
50 minThe workshop module: a complete records workflow for one AI system.
Objectives
- Build the retention workflow end to end
- Test the request response path
- Document for records officer handover
Topics
Activity. Build the workflow and run a full mock request through it.
What is the capstone project?
AI records management workflow
Produce a complete records workflow for one AI system: classification against the schedule with identified gaps, conversational capture that is searchable and producible, a tested request response path, exemption guidance, and a verified litigation hold procedure.
Deliverable: A records workflow with a successfully executed mock request and hold.
How are learners assessed?
- Mock request executed end to end with an adequate search demonstrated
- Litigation hold verified — deletion suspended in every store including indexes
- Schedule gaps identified with proposed amendments
What ships with the course?
Facilitator guide
Session-by-session running order, discussion prompts, and the questions that reliably derail a room.
Learner workbook
Exercises, checklists, and the templates each module's activity produces.
Hands-on lab environment
A sandboxed ibl.ai deployment so exercises run against real agents, not screenshots.
Assessment bank
Scenario questions and rubric criteria mapped to each stated learning outcome.
Source bibliography
Every primary regulation and standard cited on this page, linked and dated.
Which AI agents does this course use?
The hands-on modules run against agents already deployable on the ibl.ai platform for government.
Where does the course material come from?
Every module is grounded in primary sources — the regulation, standard, or research itself, not a summary of it. Each was resolved at authoring time.
- AI Guide for Government
GSA Centers of Excellence
Federal guidance on AI recordkeeping practice.
- NIST SP 800-53 Rev. 5
NIST
Audit and accountability controls supporting records capture.
- Artificial Intelligence
CISA
Federal AI governance guidance touching recordkeeping.
- Office of Management and Budget
OMB
Executive branch policy direction on AI use and documentation.
Delivery notes
Binding guidance for anyone preparing and delivering this course.
- Module 6's index preservation is the technical detail records officers miss. Deleting a document while its embedding remains in a vector index defeats both retention and deletion, and the verification must cover it.
- Module 7 must acknowledge that disclosure policy is genuinely unsettled. Presenting a confident rule where none exists sets agencies up to be wrong publicly.
- State public records law varies significantly. Localize for non-federal cohorts rather than teaching FOIA as universal.
- Module 2 will find schedule gaps in every agency. Treat producing the amendment proposal as the deliverable rather than an afterthought.
- Have agency counsel review the exemption material. Exemption application is legally consequential and a course should frame the analysis, not decide it.
Why run AI training on a platform you own?
You own the course, not a licence to it
Course content, learner data, and the platform run inside your perimeter — you own all the code and the data.
Model-agnostic delivery
Run the course's AI components on any LLM — Claude, GPT, Llama, Gemini, Command — and switch anytime.
No per-seat training licences
Usage-based or self-hosted, so cost tracks actual use rather than headcount.
Deploy anywhere
Cloud, private VPC, on-premise, or fully air-gapped — including for cohorts that cannot use public AI tools.
Frequently asked questions
What does the Records, FOIA, and AI: Retention When an Agent Writes course cover?
Public records law was not written with conversational AI in mind, and agencies are creating records they have not classified. This course covers when an AI interaction becomes a record, what has to be retained, how to respond to a request that reaches an AI system, and litigation hold across an agent's memory and logs. It runs 5 hours across 8 modules across 8 modules, at intermediate level, and closes with a capstone: AI records management workflow.
Who should take Records, FOIA, and AI: Retention When an Agent Writes?
It is written for Records management officers, FOIA and public records officers, Agency counsel, IT staff supporting records systems. Prerequisites: Familiarity with your agency's records schedule; No technical background required.
Can we run this course on our own infrastructure?
Yes. ibl.ai is model-agnostic and deploy-anywhere — cloud, private VPC, on-premise, or fully air-gapped — and you own all the code and the data. Cohort data, submissions, and any material learners upload stay inside your perimeter, which matters for government teams that cannot send work to a public AI tool.
How do we get access to Records, FOIA, and AI: Retention When an Agent Writes?
Request access and we will set it up for your cohort — hosted by ibl.ai, or running against your own deployment. Tell us the group size and timing you need, and whether it should run inside your own perimeter.
How much does AI training for government cost on ibl.ai?
There is no per-seat pricing — you pay for usage or self-host and pay only for the infrastructure, so a 5,000-person rollout does not cost 5,000 licences. 1.6M+ users across 400+ organizations run the platform this way, including NVIDIA, MIT, and Syracuse University.