AI adoption among RIAs has more than doubled since 2023, reaching 63% of firms by late 2025. Most firms still use AI for administrative tasks, but more advisors are beginning to apply it to investment research, data analysis, and idea generation.

AI can speed up research and help process large volumes of information, but it also adds risk. Outputs may be inaccurate, outdated, or unsupported by real sources.

For RIAs, the value of AI depends on whether the firm has clear verification, human review, and compliance controls before AI-assisted research is used in investment decisions or client communications.

What AI Risks Should RIAs Consider in Investment Research? 

Generative AI tools can produce confident answers that are not correct. In financial and investment-related tasks, hallucination and error rates can reach 15–25% without safeguards, which makes unverified outputs risky for company analysis and portfolio decisions.

This risk is different from a simple drafting mistake. If an AI tool invents a figure, misreads a filing, or uses outdated information, the error can move directly into research notes or client recommendations. That is why RIAs should treat every AI-generated research summary as unverified until it is checked against reliable source material.

How Should RIAs Verify AI-Generated Investment Research? 

Source verification should be the starting point for any AI-assisted research. AI can help summarize SEC filings, company reports, and market data, but advisors still need to check the original source before using the output.

That discipline matters because many firms are still behind on governance. Only 15% of RIA firms have formal AI usage policies, more than 44% of firms using AI have no formal validation process, and only about 10% have fully integrated AI into their business strategy.

For RIAs, the process should be straightforward: require primary sources, confirm the data is current, and document the review before using AI-supported research.

What Compliance Controls Do RIAs Need for AI Use? 

Compliance controls should follow the same structure as the research process. RIAs need to define which AI tools are approved, what use cases are allowed, and when outputs or review records must be retained. 

This is becoming more important as the SEC’s 2026 examination priorities focus on how registrants use AI across portfolio management, including whether firms have adequate policies and procedures to supervise that use.

How Can AI Improve Overlooked Investment Workflows?

AI can also support investment-related workflows that have historically been difficult to manage manually. Securities class action recovery is one example. Historically, this area was difficult to manage manually because there are roughly 1,000 active cases each year. In 2025, settlements totaled about $8B, but many firms still had to track eligible cases, match holdings, file claims, and reconcile payouts manually.

That has started to change with the development of AI, which platforms such as 11th.com use to automate the recovery process. Its AI infrastructure covers class action settlements, SEC Fair Funds, and other government and private recovery programs across assets and jurisdictions. For RIAs, this is a practical AI use case: recovered funds can add value to client portfolios, while clear records help support compliance without replacing advisor judgment.

What Should RIAs Prioritize When Using AI in 2026? 

In 2026, RIAs using AI for investment research should focus on practical use cases with clear controls. Research summaries, data analysis, source review, and recovery-related workflows can improve efficiency when supported by verification and human oversight.

FAQ:

How can RIAs use AI for investment research?

RIAs can use AI to summarize filings, review company reports, analyze market data, and support idea generation.

What risks should RIAs consider when using AI?

AI outputs can be inaccurate, outdated, or unsupported by real sources, so research should be verified before use.

Why is source verification important for AI research?

Source verification helps confirm that the data is real, current, and accurate before it influences research or portfolio decisions.

What compliance controls do RIAs need for AI?

RIAs should define approved tools, allowed use cases, review steps, and record retention rules for AI-supported research.

How can AI support overlooked investment workflows?

AI can help with workflows like securities class action recovery by identifying eligible cases, matching holdings, and supporting recoveries with clear records.