AI for RIAs: A Practical Guide to What Works Today (Not Just Hype)

68% of RIAs say they use AI tools in their practice.

44% of them have zero formal testing or governance around those tools.

That gap — between adoption and accountability — is where most AI conversations in the RIA space get stuck. The industry is past "should we use AI?" and deep into "what are we actually doing with it?" without a clear answer.

This guide covers what's working right now, which tools are worth the attention, and a framework for building AI into your practice in a way that holds up to scrutiny.

The Problem Isn't AI Adoption — It's AI Governance

The nContracts 2025 AI in Financial Services survey found that while nearly seven in ten RIAs report using AI in some capacity, less than half have documented policies governing that use. That creates a specific compliance risk: if your staff is using ChatGPT to draft client emails or summarize meeting notes, and you have no policy describing that use, you have a supervision gap.

This isn't an argument against AI. It's an argument for intentionality. The firms getting value from AI aren't necessarily the most technically sophisticated — they're the ones who decided what problem they were solving before they started.

What Actually Works Today: Tool-by-Tool Breakdown

Before getting to the framework, here's what's producing real results across RIA operations in 2026.

Meeting Transcription and Follow-up

Otter.ai — Solid for basic transcription. Integrates with Zoom, produces summaries, exports to notes. The free tier is usable; the Business tier adds speaker identification. Limitation: summaries are generic and require editing for client-specific context.

Fireflies.ai — Better for multi-speaker meetings with action item extraction. Native integrations with HubSpot and Salesforce; Redtail and Wealthbox require Zapier bridges. The "AskFred" feature lets you query your meeting history — useful for "what did I tell this client about their estate plan last quarter?"

Fathom — Free tier is unusually generous. Particularly well-suited for solo advisors or small teams not ready to pay for meeting AI. Highlight and clip features make it easy to extract specific client statements for compliance documentation.

CRM AI Features: Native vs. Bolt-On

Redtail CRM — Currently limited native AI. The platform's workflow automation rules are powerful for task routing and creation, but AI features remain early-stage. Best paired with external tools.

Wealthbox — Similar story. Solid CRM with workflow automation, but AI features are largely surface-level (email drafting assistance, task suggestions). The API is more open than Redtail's, which makes it easier to connect to external AI services.

Salesforce Financial Services Cloud — The most mature AI integration via Einstein, but the cost and implementation complexity are inappropriate for most RIAs below $500M AUM.

Document Drafting and Review

ChatGPT (GPT-4o) — The most common tool in the wild. Used to draft client communications, summarize prospectuses, and generate first-pass investment policy statements. Important compliance note: client data should never enter the public model. Use the API with a data processing agreement or ChatGPT Enterprise.

Harvey — Purpose-built for legal and compliance-adjacent work. Outperforms general LLMs on regulatory analysis, ADV review, and compliance language. Pricing is enterprise-oriented and better suited to larger firms or those with heavy legal workloads.

eMoney Copilot — Launched in 2025, embedded directly in the planning workflow. It summarizes a client's financial plan, flags gaps, and generates agenda talking points from data already in the system — no copy-paste required. Genuinely useful because it removes the context-switching.

The RIA AI Readiness Stack: A Four-Tier Framework

Not every RIA is in the same place. This framework maps where firms typically are and what the next step looks like.

Tier 1 — Unstructured Use Staff uses AI tools personally or informally. No approved list. No documented policy. Results are inconsistent across advisors. Risk: supervision gaps, data leakage, inconsistent client experience.

Next step: Document what's currently being used. Create a one-page AI use policy. Identify which tools touch client data and which don't.

Tier 2 — Policy Without Process The firm has a written policy and an approved tool list. But there's no consistent workflow — individual advisors operate within loose guardrails.

Next step: Pick one workflow to standardize. Meeting transcription is the easiest first move — it's low-risk, high-frequency, and immediately measurable.

Tier 3 — Standardized Workflows AI is embedded in specific, repeatable workflows. Meeting notes flow through the same tool every time. Client email templates are generated the same way. The ops team has consistent inputs and predictable outputs.

Next step: Connect AI outputs to existing systems. If Fireflies generates a meeting summary, it should land in Redtail automatically — not wait in an inbox to be copy-pasted.

Tier 4 — Connected Intelligence AI tools are integrated with the firm's tech stack. Data flows between systems automatically. The advisor reviews and approves; the system handles routing, summarizing, and queuing.

Next step: Build a continuous improvement loop. Track which AI-generated content gets edited heavily (signal the tool isn't calibrated) versus sent as-is (signal it's working).

The Compliance Piece You Can't Skip

Three things every RIA needs before expanding AI use:

An approved tools list — Explicitly document which AI tools staff may use and for what purposes. Distinguish between tools that process client data (require DPA review) and those that don't.
A data handling policy — Define what client information may and may not be entered into external AI services. "No client names, account numbers, or identifying information in public models" is a reasonable and enforceable starting point.
A supervision workflow — AI-generated client communications need a human review step. This isn't about distrusting the tool — it's about maintaining the advisor's responsibility for what goes out under their name.

The SEC had not issued definitive AI guidance as of early 2026, but existing principles around supervision, recordkeeping, and advertising apply. Treat AI-generated content the way you'd treat any staff-produced communication.

Where to Start

The firms making the most progress on AI aren't the ones with the biggest budgets. They're the ones who picked a single, high-frequency problem — meeting follow-up, agenda creation, document routing — and built one consistent workflow around it.

If your team completes 15 client meetings a week and spends 20 minutes each on follow-up, that's five hours of weekly output that could be systematized. A meeting transcription tool with a consistent summarization workflow changes the math. That's where you start.

Start with transcription. Build the policy around it. Connect the output to your CRM. Then move to the next workflow.

Frequently Asked Questions

Is AI use in RIA practices compliant with SEC regulations?

The SEC had not issued AI-specific guidance as of early 2026, but existing rules on supervision, advertising, and recordkeeping apply. RIAs should document their AI tool usage, ensure client data is handled appropriately under a data processing agreement, and treat AI-generated communications as supervised correspondence.

What AI tools are safe for RIAs to use with client data?

Tools with enterprise privacy agreements, dedicated tenants, or API access with signed data processing agreements are generally safer than public consumer tools. ChatGPT Enterprise, Fireflies Business, and tools built into existing platforms (like eMoney Copilot) offer stronger data handling protections. Always review vendor terms before inputting client data.

How do I get my team to consistently use AI tools?

Adoption requires workflow design, not just tool procurement. Pick one high-frequency task, standardize the tool and the process, and make the manual alternative clearly more effortful. Start small, measure output quality, and expand from there. Mandating a tool without a defined workflow produces inconsistent results.

Key Takeaways

68% of RIAs report using AI; 44% have no formal testing or governance in place (nContracts, 2025)
Meeting transcription tools (Otter.ai, Fireflies, Fathom) and embedded tools (eMoney Copilot) produce the most immediate operational value
Native CRM AI features in Redtail and Wealthbox are early-stage; external tools currently outperform them for most use cases
The RIA AI Readiness Stack identifies four tiers: Unstructured Use → Policy Without Process → Standardized Workflows → Connected Intelligence
Compliance requires three things before expanding AI use: an approved tools list, a data handling policy, and a supervision workflow

Ready to build your first AI-connected workflow? Book a discovery call with the Systemaic team.