What is this course about?
Supervisory and recordkeeping obligations apply to AI-generated communications exactly as they do to human ones, and most firms have not extended their systems to cover them. This course covers retaining prompts and outputs, off-channel risk introduced by AI tools, advertising rule compliance, and examination readiness.
Who is this course for?
- Chief compliance officers of broker-dealers and RIAs
- Supervisory principals
- Surveillance and communications review staff
- Internal audit covering supervision
What do I need before starting?
- Broker-dealer or RIA compliance experience
- Familiarity with your supervisory system
What will I be able to do afterwards?
- Extend supervisory procedures to AI-generated communications
- Retain prompts, outputs, and model versions as required records
- Manage off-channel risk introduced by AI tools
- Apply advertising and marketing rules to AI-generated material
- Prepare the artifacts an examination will request
What does each module cover?
What supervisory obligations attach to AI output?
45 minExtending supervision to communications a system generated.
Objectives
- Apply supervisory obligations to AI-generated communications
- Update written supervisory procedures
- Assign supervisory responsibility
Topics
Activity. Update your WSPs to cover AI-generated communications.
What has to be retained?
50 minBooks and records applied to prompts, outputs, model versions, and configuration.
Objectives
- Determine what constitutes a required record
- Retain prompts, outputs, and model versions
- Meet format and accessibility requirements
Topics
Activity. Map AI artifacts to your recordkeeping obligations and find the gaps.
How do AI tools create off-channel risk?
45 minPersonal AI tool use as the newest off-channel communications problem.
Objectives
- Identify off-channel risk created by AI tools
- Detect unapproved tool use
- Set and enforce policy
Topics
Activity. Survey actual AI tool use and assess the off-channel exposure.
How do advertising rules apply to generated material?
50 minMarketing rule compliance when the content was drafted by a system.
Objectives
- Apply advertising and marketing rules to AI content
- Handle performance and testimonial content
- Build the review workflow
Topics
Activity. Review AI-generated marketing material against the marketing rule.
What happens when AI informs a recommendation?
50 minSuitability and fiduciary duty when analysis behind a recommendation came from a model.
Objectives
- Apply suitability and fiduciary standards to AI-informed advice
- Document the basis for a recommendation
- Set boundaries on AI's role
Topics
Activity. Document the basis for an AI-informed recommendation to a supervisory standard.
How do you surveil employee AI use?
45 minSurveillance that meets supervisory obligations without becoming disproportionate.
Objectives
- Design surveillance meeting supervisory duties
- Keep surveillance proportionate
- Escalate findings appropriately
Topics
Activity. Design the surveillance approach and its escalation path.
What will an examination request?
45 minPreparing the artifacts examiners are asking for on AI use.
Objectives
- Anticipate examination requests on AI
- Prepare artifacts in advance
- Identify and remediate gaps before examination
Topics
Activity. Complete a mock examination request list and identify what you cannot produce.
Building the supervisory procedure
50 minThe workshop module: a written supervisory procedure for one client-facing AI workflow.
Objectives
- Write the supervisory procedure
- Verify it is operationally executable
- Test it against a real workflow
Topics
Activity. Write the procedure and have a principal execute it against real output.
What is the capstone project?
Supervisory procedure for a client-facing AI workflow
Produce updated written supervisory procedures covering AI-generated communications, a records mapping with gaps remediated, off-channel policy, marketing review workflow, recommendation basis documentation, and an examination readiness assessment.
Deliverable: An executable supervisory procedure with an examination readiness gap list.
How are learners assessed?
- Procedure executed by a principal against real output
- Records mapping tested — can you produce a prompt from six months ago?
- Mock examination request completed with gaps identified
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 financial services.
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.
- Artificial Intelligence
FINRA
FINRA's guidance on AI use by member firms.
- U.S. Securities and Exchange Commission
SEC
Marketing rule, recordkeeping, and examination priorities.
- FFIEC
Federal Financial Institutions Examination Council
Technology risk expectations relevant to supervision systems.
- AI Risk Management Framework
NIST
Governance structure supporting the supervisory design.
Delivery notes
Binding guidance for anyone preparing and delivering this course.
- Module 2's prompt retention is the gap almost every firm has. Test it concretely — ask participants to produce a prompt from six months ago and watch the room.
- Off-channel enforcement has produced very large penalties. Module 3 should reference the enforcement pattern without naming firms gratuitously.
- Examination priorities change annually. Verify current AI-related priorities at each revision rather than citing a specific year's letter.
- Module 8's procedure must be operationally executable. Supervisory procedures that a principal cannot actually perform are a finding in themselves.
- Have a compliance officer with examination experience review the course. Examination expectations are set by practice, not by rule text.
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 AI Supervision Under FINRA and SEC Recordkeeping Rules course cover?
Supervisory and recordkeeping obligations apply to AI-generated communications exactly as they do to human ones, and most firms have not extended their systems to cover them. This course covers retaining prompts and outputs, off-channel risk introduced by AI tools, advertising rule compliance, and examination readiness. It runs 5.5 hours across 8 modules across 8 modules, at intermediate level, and closes with a capstone: Supervisory procedure for a client-facing AI workflow.
Who should take AI Supervision Under FINRA and SEC Recordkeeping Rules?
It is written for Chief compliance officers of broker-dealers and RIAs, Supervisory principals, Surveillance and communications review staff, Internal audit covering supervision. Prerequisites: Broker-dealer or RIA compliance experience; Familiarity with your supervisory system.
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 financial services teams that cannot send work to a public AI tool.
How do we get access to AI Supervision Under FINRA and SEC Recordkeeping Rules?
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 financial services 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.