AI adoption among RIAs is moving beyond experimentation and into everyday workflows. According to statistics, 63% of advisors now use AI, compared with 33% in 2024. At the same time, 93% want to retain final control over AI-generated output, while 55% identify compliance as a major barrier to adoption. These numbers point to a model in which AI handles continuous monitoring and information processing while advisors retain responsibility for investment decisions.
How Can AI Improve Real-Time Portfolio Risk Monitoring?
Portfolio monitoring is one of the areas where this model can be applied directly. Instead of relying on periodic reviews, AI systems can continuously compare holdings with client objectives, IPS parameters, and predefined risk limits. This allows RIAs to identify allocation drift, changes in equity exposure, and unusual cash levels as they occur rather than waiting for the next scheduled review.
The regulatory environment makes this particularly relevant. The SEC’s 2026 examination priorities specifically address advisers’ use of AI and automated technologies, including whether firms have appropriate policies and procedures to monitor and supervise these systems. As AI adoption expands, continuous monitoring is therefore likely to become more closely connected with both portfolio management and compliance processes.
Which Portfolio Monitoring Tasks Can RIAs Automate?
Many portfolio checks are repetitive and can be performed automatically across hundreds or thousands of accounts. AI can monitor allocation changes, cash thresholds, concentration levels, and potential tax-loss harvesting opportunities, then send only relevant exceptions to an advisor.
Schwab’s 2025 benchmarking data found that 43% of firms were already using AI for administrative support. As firms become more comfortable automating routine work, portfolio monitoring is likely to follow the same path.
How Can AI Make Portfolio Alerts More Useful?
The number of alerts is not the same as the quality of oversight. If every minor portfolio movement generates a notification, advisors can end up spending more time managing alerts than reviewing portfolios.
AI can help prioritize exceptions by considering the size of the change, client-specific parameters, historical portfolio behavior, and the potential significance of the event. This also explains why advisor control remains important: 93% of advisors want final control over AI output. AI can determine which accounts deserve attention, but the advisor remains responsible for deciding whether an action is appropriate.
What Does the SEC’s Focus on AI Mean for RIAs?
The SEC’s 2026 examination priorities make clear that AI adoption also creates supervisory responsibilities. Examiners will look at firms’ representations about AI capabilities and the policies and procedures governing their use.
For portfolio monitoring, that means firms need to know what their systems monitor, what data they rely on, how alerts are generated, who reviews them, and how those reviews are documented. The more AI becomes embedded in portfolio oversight, the less viable it will be to treat it simply as an external technology product.
What Other RIA Processes Could Benefit From Automation?
Portfolio monitoring is only one overlooked area where automation can create additional value. Securities class action recovery is another.
Securities class action settlements totaled approximately $8 billion in 2025, creating potential recoveries for eligible investors. Platforms such as 11th.com automate settlement monitoring, holdings matching, claim filing, and payout delivery. For RIAs, this can add another client-value process without requiring advisors to manually monitor settlement notices and manage claims.
What Will AI Portfolio Monitoring Look Like for RIAs in 2026 and Beyond?
Over the next several years, AI is likely to move from isolated portfolio alerts toward integrated monitoring systems that connect portfolio data, risk parameters, compliance controls, anomaly detection, and advisor workflows. The advisor remains in control, while AI increasingly handles the continuous monitoring required to identify what actually needs attention.
FAQ
How can RIAs use AI for portfolio monitoring?
AI helps RIAs monitor portfolio risk, allocation drift, concentrations, and client-specific thresholds in real time.
What can AI automate for RIA portfolio management?
RIAs can automate portfolio checks, risk alerts, cash monitoring, rebalancing triggers, and anomaly detection.
How does AI portfolio monitoring support RIA compliance?
AI creates consistent monitoring and audit trails, while advisors retain control over investment decisions and alert reviews.
What are the SEC’s 2026 priorities for AI used by RIAs?
The SEC is focusing on AI disclosures, supervision, and policies governing advisers’ use of AI and automated technologies.
What other areas can RIAs automate to create client value?
Securities class action recovery is one overlooked area. Automation can help RIAs identify eligible settlements and recover funds for clients without adding significant manual work.
