Wealth management technology executives are urging advisory firms to look beyond the chatbot era and embrace agentic AI—systems that execute multi-step tasks autonomously, with human oversight. According to leaders at Concurrent, Practifi, and Vanilla, the firms that thrive will be those that embed AI into their operational fabric, not those that simply respond to individual prompts.
Adoption is already widespread. A May 2026 survey by Morning Consult and Edward Jones found that 82% of 201 U.S. advisors use AI in their practices. Large institutions are also investing heavily; in June 2026, Rockefeller Capital Management partnered with Anthropic to develop an AI-enabled wealth management platform. Regulators are taking notice too—FINRA's 2026 Annual Regulatory Oversight Report, released in December 2025, addressed AI agents for the first time, urging firms to define human oversight procedures.
Joe McQuaid, COO of Concurrent, advises firms to start with repeatable, rules-based processes such as meeting follow-ups, portfolio surveillance, account-opening paperwork, and compliance pre-review. "The shift isn't about buying a smarter chatbot," he said. "It's about building the operating layer—connected data, governed access to firm systems, and a library of skills and workflows that run without someone having to type a prompt." McQuaid emphasizes that winning firms will move from reactive prompting to automated workflows that surface the right action to the right person.
Conor Curtis, head of product at Practifi, echoes that sentiment, pointing to recurring workflows like onboarding, annual reviews, and post-meeting follow-up where missed steps create service gaps. He stresses that firms must define triggers, ownership, completion criteria, and approval requirements before automating. "Firms should expand autonomy as they demonstrate reliable execution, rather than treating it as an all-or-nothing decision," Curtis said. He sees the CRM as the natural foundation for AI integration.
Gene Farrell, CEO of Vanilla, draws a distinction between proactive and autonomous AI. While proactive AI—which flags issues for advisor review—is the right direction, autonomous AI that makes decisions without human involvement is problematic for fiduciaries. "Accountability has to sit with someone who has judgment and a relationship with the client," Farrell said. In estate planning, for example, agents might review an advisor's book for red flags like a rental property titled outside a trust, but the advisor decides what to escalate.
All three executives agree that firm-level AI differs from individual productivity tools. Farrell notes that two advisors using the same tool can get vastly different results depending on their prompting skills, while the firm has little visibility into data usage. McQuaid outlines four pillars for firm-level AI: grounding in firm data, connectors to core systems, a governance framework for approving skills, and built-in human supervision. "One advisor's prompt is a personal win, but that same prompt turned into a vetted, governed, firm-wide skill becomes institutional capability that compounds," he said.
Curtis adds that success should be measured by consistent service delivery, not just minutes saved. "The measure of success shifts from minutes saved by one advisor to whether the firm delivers timely, consistent service across its client base," he said. This distinction matters because service levels, not efficiency, are where firms compete.
Regarding accountability, the executives agree that data gathering, reconciliation, document review, and first drafts belong in the back office, while advice and difficult conversations remain human. Farrell cites Edward Jones research showing 59% of advisors want AI to automate administrative work, while 68% believe long-term client trust requires a human touch. He also warns that calculations should run on deterministic engines to ensure accuracy. "AI still makes mistakes, and it's very difficult to hold an agent accountable when it gets something wrong," he said.
Curtis concludes that oversight should match the stakes of each action, and Farrell warns against tool sprawl, noting one firm's advisors use 34 different tools. For more on how firms are scaling AI, see enterprise AI partnerships and AI chatbot limitations.
