AI has moved quickly from experimentation to daily use inside financial firms. Employees are using AI-enabled tools to draft policies, summarize meetings, review documents, write communications, analyze data, support supervision and improve productivity. Some of these tools are intentionally adopted by the firm. Others enter through ordinary software upgrades, vendor platforms, browser extensions, personal subscriptions or employee workarounds.
For RIAs and broker-dealers, this creates a difficult operating reality. AI can improve efficiency, but it also introduces risk across privacy, recordkeeping, supervision, cybersecurity, vendor oversight, accuracy, bias and regulatory accountability. The problem is not simply whether a firm uses AI. The more pressing issue is whether the firm knows where AI is being used, what data is being exposed, who is reviewing the output and how the firm would defend its controls during an examination.
The regulatory environment remains fragmented, but that does not mean expectations are unclear. Regulators may not have a single AI rulebook, but they already have well established rules and principles for supervision, privacy, books and records, fiduciary duty, cybersecurity, vendor oversight and investor protection. AI will be evaluated through those existing frameworks. A firm cannot avoid accountability by saying the technology made the decision, drafted the document, created the error or exposed the data.
The Practical Path Forward: Use AI, But Make It Defensible
AI will become more embedded in financial advisory firms and that will inevitably cause complications for wealth management firms. Avoiding AI entirely may not be practical or a smart competitive growth strategy. But adopting AI without governance creates exposure that can accumulate quickly and quietly.
The responsible path is not fear. It is structure.
The responsible path is not fear. It is structure. Firms should embrace AI for the benefits it provides, but should not do so blindly. They should keep experts in the loop, train their workforce and implement active controls to test, monitor and certify results. Examiners are likely to ask not only whether AI is being used, but how the firm governs, supervises and documents that use.
A defensible AI program should include seven foundational elements:
1. Inventory. The firm should identify all AI tools currently in use, including standalone platforms, vendor-embedded AI, personal accounts, browser extensions, note-taking tools and internal automations. Inventory should include who uses each tool, what data it accesses, what business purpose it serves and whether it is approved.
2. Policy. The firm should define permitted, restricted and prohibited AI uses. The policy should address data entry, client information, personal accounts, vendor tools, recordkeeping, human review, escalation and sanctions for circumvention.
3. Training. Employees need practical training on what AI tools can and cannot be used for, what information cannot be entered into unapproved systems, what human review is required and why violations create risk for clients, the firm and the individual.
4. Qualified Human Review. The firm should require qualified review for AI output used in compliance, supervision, client communications, investment analysis, policies, regulatory responses or other high-risk workflows. The review should be documented.
5. Vendor Oversight. AI vendor due diligence should be risk-based and ongoing. Contracts should address data use, model training, retention, logs, security, liability, incident notification and the firm’s ability to supervise and preserve records.
6. Testing and Monitoring. The firm should not rely solely on attestations. It should test whether AI policies are being followed, monitor for shadow AI where feasible, review metadata and system activity where appropriate, and periodically evaluate whether approved tools remain accurate, current and fit for purpose.
7. Documentation. The firm should document its AI governance decisions, approvals, training, certifications, testing, exceptions, vendor reviews, incidents and remediation. Documentation is what allows the firm to show reasonable effort, reasonable supervision and reasonable due diligence.
AI may save time, allow firms to shift resources to more growth-focused initiatives and help advisors provide more personalized services to clients. But without governance, today’s efficiency can become tomorrow’s examination issue. The firms that benefit most from AI will not be the ones that adopt it casually. They will be the ones that adopt it deliberately, align it with regulatory obligations, preserve human account ability and build controls that can withstand scrutiny.
Defensible AI is not a technology purchase. It is a compliance operating discipline.
Defensible AI is not a technology purchase. It is a compliance operating discipline. And for RIAs, that discipline should begin now.
AI adoption is no longer theoretical. Governance cannot be either.
Sid Yenamandra is the Founder and CEO of SurgeONE.ai, a compliance, cybersecurity and data services platform for wealth management that unifies the offerings of RegVerse, Kovair, Security Snapshot and MGL Consulting.
