AI Governance Framework for RIAs: A Practical Build

Every RIA touching AI needs a governance framework. Most don't have one, and the ones that do tend to either overengineer it into a consultant-grade binder no one reads, or underengineer it into a one-page policy that doesn't withstand a regulator's question.

This is the operator-grade build: lean enough to actually use, rigorous enough to defend, written for a firm that has decided AI is permanent infrastructure.

What an AI governance framework actually needs

Five components:

• Scope and inventory — What AI tools the firm uses, who uses them, what data they touch
• Roles and accountability — Who owns AI decisions, who approves deployments, who audits
• Use-case policies — What AI can do, what it can't, where human approval is required
• Data handling rules — Where client data can and can't go, retention, redaction
• Audit and review process — How AI activity is logged, reviewed, escalated

Each of these can be a paragraph or a page. The firm decides based on size and complexity.

Scope and inventory

Start with a one-page inventory:

• Tool name
• Vendor
• Primary use case
• Data the tool processes (transcripts, emails, portfolio data, prospect data)
• Compliance retention configured (yes/no, period)
• SOC 2 / equivalent (yes/no)
• Date deployed
• Tool owner (the person responsible)

Update quarterly. Most firms discover during this exercise that they have 8-15 AI tools live across the firm, only 3-5 of which leadership knows about. The exercise pays for itself.

Roles and accountability

Three roles at minimum:

• AI Sponsor — A principal-level owner who has decision rights on AI strategy. Usually managing partner or COO.
• AI Operator — The person running the AI tools day-to-day. Often the COO, operations lead, or technology officer.
• AI Compliance Reviewer — The CCO or compliance lead who reviews AI policies, AI-generated communications, and AI activity logs.

At firms under 10 advisors, one person may wear two of these hats. That's fine if the roles are explicit.

Use-case policies

The clearest framing we've seen: three tiers of AI use.

Tier 1 — Permitted without approval:

• Internal-only AI use: drafting internal memos, summarizing internal docs, querying public data
• Personal productivity tools at the user level (e.g., Outlook Copilot for drafting)
• AI-assisted research that doesn't produce client communications

Tier 2 — Permitted with documented review:

• AI-generated client communications (emails, letters, decks) — reviewed by advisor and supervised
• AI-generated marketing materials — reviewed under FINRA Rule 2210 / SEC Marketing Rule
• AI meeting capture — supervised under firm's recording and retention policy
• AI prospect outreach — supervised as marketing communication

Tier 3 — Prohibited without firm-specific exception:

• AI generating investment recommendations to clients (fiduciary territory)
• AI making trading decisions
• AI-driven client risk profiling without human review
• Consumer-grade AI tools (free ChatGPT, free Claude) processing client data
• AI tools without SOC 2 or equivalent posture

Each firm tunes the tiers. The structure stays the same.

Data handling rules

Four rules to encode:

• Client data goes to approved tools only. Approved tools have SOC 2, proper retention, and firm-administered access controls.
• PII redaction is mandatory before any AI processing where the tool doesn't redact natively. SSNs, account numbers, credit cards — strip before processing.
• Retention follows the firm's books-and-records policy. AI outputs that constitute records (client communications, meeting transcripts) get retained per firm policy, not per vendor default.
• Cross-border data transfers require explicit approval. Some AI vendors process in regions that conflict with state privacy law or client residency. Document.

Audit and review process

The lightweight model that works for firms 3-50 advisors:

• Weekly: Compliance lead samples 5-10 AI-generated client communications, reviews for fitness
• Monthly: AI Operator reviews tool usage data — who used what, exceptions, any policy violations
• Quarterly: Full inventory review — new tools added, tools deprecated, policy updates
• Annually: AI policy review, regulatory landscape review, training refresh for all staff

Larger firms add daily compliance sampling and continuous-audit tooling. Smaller firms can compress monthly + quarterly into a single check.

Training and acknowledgment

Every staff member who touches AI tools acknowledges the policy annually. The acknowledgment includes:

• Tools they're approved to use
• Tiers they're authorized for
• What constitutes a policy violation
• How to report uncertainty

This isn't theater. SEC and FINRA examiners ask "how do staff know the policy?" An annual acknowledgment with documented training answers cleanly.

What examiners look for

Based on recent SEC and FINRA exam priorities, the AI governance questions to expect:

• Do you have a written AI policy?
• What AI tools are in use at the firm?
• How are AI-generated communications supervised?
• How is client data handled in AI tools?
• What training have staff received?
• Have you identified AI use as a risk in your annual risk assessment?

If your policy answers these questions cleanly and your audit trail backs the answers, you're in good shape. If your policy is silent on AI or contradicts what's actually happening at the firm, you have a problem.

Common mistakes

Three patterns we see:

• Policy without enforcement. Beautiful binder, nothing happens day to day. Examiners notice.
• Enforcement without policy. Firm is doing AI well in practice but has nothing written. Regulator sees no framework.
• Policy that contradicts reality. Written policy says X, advisors do Y, no one updated the doc. The contradiction is the violation.

What to ship

For a firm under 10 advisors, the minimum viable AI governance is:

• A 4-6 page written policy covering the five components above
• A one-page tool inventory updated quarterly
• A one-paragraph staff acknowledgment signed annually
• A monthly compliance review of 10 AI-generated communications
• Annual training (90 minutes, recorded)

That's it. Anything beyond is firm-specific. Anything less is exposed.

Bottom line

AI governance at an RIA isn't a binder. It's a small set of explicit decisions about who can use what AI for which use cases, with audit trail to back it up. Build it once at the right level of rigor, update it quarterly, and it will serve the firm for years.

The firms that get this right today will have meaningful compliance defensibility in three years. The firms that punt will be retrofitting governance under exam pressure.