AI has already found a useful place in the advisor’s office.
AI-powered tools listen to client meetings, capture conversations, summarize what was discussed and, in some cases, push notes and action items into the CRM. For advisors who have adopted AI notetaking, the productivity gains are real. Less typing, less manual documentation, and with fewer details lost between meetings.
But a bigger opportunity sits right in front of firms.
The next phase of AI adoption in wealth management will focus on AI tools that proactively complete tasks. Instead of simply documenting, AI tools can help advisors prepare for what comes next, identify what needs attention, personalize the client experience and automate the work that follows.
That is where AI starts moving from a productivity tool to a practice-building tool.
“The first use case of AI was the notetakers, being able to summarize calls, keep everything on track, and then being able to follow up with action calls,” says Tim Welsh, president, CEO and founder of Nexus Strategy, a consulting firm for the wealth management industry. “Step two is turning that into workflow automation. That’s when AI agents come into play.”
Turn meeting notes into action
An AI notetaker can tell an advisor that a client is thinking about selling a business, helping a child buy a home or revisiting an estate plan.
The next step is getting AI to do something with that information.
Imagine an advisor finishing a client meeting and having AI automatically identify the follow-up tasks, assign them to the appropriate team member, update the CRM, draft the client email and flag related planning opportunities.
That next step can happen even during a client meeting.
“If a client mentions a child or a grandchild and college planning, an AI agent will recognize that and kick off a workflow order to the account’s custodian, pull a new account form for a 529 plan, and then drop it into the Zoom meeting where the advisor can pre-populate the form with all the necessary information from their CRM,” explains Welsh.
The advisor still reviews and approves the work. But the administrative chain that traditionally follows every meeting becomes much shorter.
The goal isn't simply to create better notes. It is to make those notes the starting point for everything that happens next.
From point solutions to a platform 'systems of action'
While third-party AI tools have delivered quick wins, the broader industry shift requires moving beyond standalone apps toward deeply integrated wealth management platforms.
"Most of the buzz in our industry over the last two years has come from AI-powered point solutions: the notetaker, the lead gen tool and the chatbot," says Rich Cancro, CEO of AdvisorEngine. "The full promise of AI can only be achieved when it is delivered cohesively across workflows and features."
Cancro emphasizes that platforms need to evolve into true "systems of action" that blend structured portfolio metrics with unstructured qualitative client data. By embedding multi-agent AI directly into core operations, ranging from smart form processing to automated document analysis, platforms can trigger end-to-end workflows automatically.
"Having both CRM data and portfolio management in hand allows us to weave the two halves of a client's financial tapestry," Cancro adds. "The narrative side (emails, notes and life events) and the numbers: results, holdings and tax reality."
Give advisors an AI-powered client brief
AI can also be useful before the meeting, not just during it.
Instead of spending 20 minutes digging through a CRM before a client review, an advisor could have AI prepare a concise briefing that brings together the information that matters.
What has changed since the last meeting? What conversations are still unresolved? What planning opportunities were previously discussed? Has the client's portfolio moved significantly? Are there upcoming life events or deadlines? What questions did the client raise last time? The advisor walks into the meeting already prepared.
This could be particularly valuable for larger firms where advisors may manage dozens or hundreds of households. AI can surface information already in the firm's systems but hard to find quickly.
The benefit isn't just saving time. It can make the advisor feel more prepared, and the client feel better known.
That’s been the experience of Kevin Feig, CFP®, founder of Walk You to Wealth. He uses AI platforms to streamline backend analysis and refine client-facing documents. “AI started out primarily as an automated notetaker,” Feig says. “Now, it’s evolving into a useful secondary check that helps advisors review account details and translate complex data into clearer communications for clients.”
“AI is going to make advisors more productive, faster and ultimately give a better end client experience because they can deliver more, better and faster and probably less expensive,” says Joel Bruckenstein, financial services fintech expert and president of T3 Technology Tools for Today, which produces the annual T3 Conference.
Personalize client communication at scale
One of AI's biggest opportunities in wealth management is personalization.
Most firms already communicate with clients regularly. The problem is that much of that communication still relies on templates.
AI can help advisors move beyond generic messages by using a client's history, goals and recent conversations to create more relevant communications.
A market update could be tailored to the issues that matter to a particular household. A retirement planning reminder could reference the client's specific timeline. A follow-up email could reflect the actual conversation the advisor just had.
The advisor remains the editor and final decision-maker. AI simply makes it possible to deliver a more personalized experience without requiring advisors to write every message from scratch.
“Client communications, meeting preparation and documentation have been the primary use cases,” according to a recent report on the State of Wealth Management AI Adoption from Cerulli Associates in partnership with Vista Equity Partners.
Make AI a research assistant
Advisors also spend considerable time gathering and synthesizing information.
AI can help with that work by summarizing research, comparing information, identifying relevant data and surfacing questions that deserve further investigation.
And the research doesn't have to be limited to investments.
Think tax planning, estate planning, retirement strategies, Social Security, insurance, legislation and other issues that influence a client's financial life.
“AI is moving into middle-and front-office workflows that sit closest to advice itself, where the work is analytical, client-specific and central to what firms provide to clients,” notes the Cerulli/Vista Equity report. Most of those applications, however, are still being piloted and are not fully deployed, according to the report.
The key is to use AI as a research assistant, not an autonomous source of advice. Financial decisions still require professional judgment, verification and oversight.
Find opportunities hiding in the book
Perhaps one of the most interesting applications has little to do with generating content.
AI can analyze a firm's existing client data and identify patterns that humans may miss.
Which clients may be approaching a major planning event? Which households have assets held away? Which clients haven't had a particular planning conversation in several years? Which relationships might benefit from a deeper estate planning discussion?
Instead of asking advisors to remember every potential opportunity across hundreds of relationships, AI can help them prioritize where to spend their time.
That could turn AI into a business development and client retention tool, not just an administrative one.
Give clients an AI-powered front door
Another opportunity firms should watch is the client-facing AI assistant.
Clients increasingly expect immediate answers to straightforward questions. Where is my document? When is my next meeting? What did we discuss? Can you explain this term? What does this report mean?
An AI assistant could handle many of those lower-level questions while escalating more complicated issues to a human advisor.
That doesn't mean creating an AI financial advisor and walking away.
In fact, the opposite may be more valuable. Let AI handle the simple questions so advisors can spend more time on the complicated ones.
The distinction matters because trust remains critical. People may be comfortable using AI to find information, but when the stakes are high, many still want a human who understands their situation and can help them decide.
The opportunity isn't to replace the advisor. It is to make the advisor more available when the client actually needs one.
"Our goal is to create more capacity for our people, improve the client experience and continue growing without sacrificing the personal relationships that define wealth management,” says Marty Bicknell, CEO and president of Mariner, the RIA leader in AI adoption. The Overland, Kansas, firm has partnered with Humanity Labs to embed an AI workforce, equivalent to more than 700 full-time workers, in its operations.
Start experimenting with AI agents
The longer-term opportunity may be the most interesting.
Today's AI largely waits for someone to give it a prompt. The next generation of AI will increasingly be able to take a goal, determine the steps required and execute portions of the workflow.
For an advisory firm, that could eventually mean an AI agent monitoring a workflow and recognizing that a client's estate planning needs attention. It could flag the issue, update the CRM, send the appropriate questionnaire, notify the advisor and add the topic to the next meeting agenda.
Instead of the advisor telling the technology what to do at every step, the technology begins helping manage the process.
That is a much bigger shift than AI-generated meeting notes.
It also introduces more risk. As AI becomes more autonomous, firms will need stronger controls around permissions, data, recordkeeping, supervision and human approval.
“You need an acceptable use policy for AI which people can attest to regularly,” says Bruckenstein. “It's not a one-and-done thing. You need to constantly remind people of what the rules are, what they can and can't do.”
Brett Bernstein, the CEO and co-founder of XML Financial Group in Rockville, Maryland, said his firm is “adopting AI very intentionally, leading with compliance, governance and risk management,” making sure “to build proper policies and procedures first. We have to protect our clients, our data.” Once that’s completed, the firm expects to build out its own platform in-house using Microsoft’s Copilot.
Don't automate just because you can
Firms are tempted to chase every new AI capability. That is probably the wrong strategy. The better question is: Where is the friction in our business?
If advisors spend hours preparing for meetings, start there. If client follow-up is inconsistent, solve that. If advisors struggle to identify opportunities across a large book, use AI to surface them.
If administrative work is keeping advisors from spending time with clients, look for workflows AI can simplify.
And if a process involves sensitive client information or regulated activity, bring compliance, security and legal teams into the conversation before deployment, not after.
The firms that get the most from AI won't necessarily be the ones with the most tools. They will be the ones that connect AI to the way their advisors actually work.
“There’s got to be a human in the loop,” says Bruckenstein. “AI can create reports for clients, emails to send to clients, etc., but a human has to review them first.”
The notetaker is a good starting point because it solves a clear problem and delivers an immediate productivity win. But it should also raise a bigger question: What happens next?
The real opportunity is to build a practice where AI handles more of the preparation, documentation, research and routine follow-up, while advisors spend more of their time doing the things technology still can't replicate well: asking the right questions, understanding what matters to a client, making judgment calls and helping people navigate important financial decisions.
AI notetaking may be the first step.
The firms that look beyond it will be the ones figuring out what comes next.
“Firms have to invest and have a long-term strategic plan for AI,” says Welsh. “But AI does not work unless all their data is harmonized, cleansed and unified. That’s a massive data project. Build a data lake, then you can leash the AI on it and you’ll be light years ahead of everyone else.”
“The clock is ticking,” says Bruckenstein. “If you had asked advisory firms a year ago what they were doing, they were playing with ChatGPT. Fast forward one year and advisory firms are investing significant amounts of money to build things out.”
