1 min read
Takeaways:
- More capacity means spending more time with clients: AI can help RIAs absorb growth by reducing the preparation, follow-up, and operational work that expands with every relationship.
- Personalization can scale across the firm: Automation can surface client needs and opportunities more consistently, making proactive attention possible across more relationships.
- Holistic advice becomes more practical: AI can reduce the work of gathering, reconciling, and monitoring information, giving advisors greater capacity to address more of a client’s financial life.
- Connected data makes AI more useful: AI can deliver more relevant insights when it draws on trusted, connected household data that is rich with context rather than information trapped in individual applications.
AI has quickly become part of the conversation for RIAs. The real opportunity may have less to do with the technology itself than with the capacity it can create.
Many RIAs experienced AI for the first time in the form of an AI notetaker. The appeal was instant: less time documenting conversations, more time focused on clients. But that early use case raised a much larger question: How can AI give independent advisors more room to grow and serve clients, without adding complexity?
I believe the conversation needs to start with the problem a firm is trying to solve instead of the technology itself. AI is a tool, not the objective. For growing RIAs, the challenge is familiar: serve more families, more proactively, across more of their financial lives, without a comparable increase in resources.
To explore where AI can make the biggest difference, I spoke with AJ Emanuele, Senior Vice President of Product Management at Dynasty Financial Partners; Suzanne Cook, CEO and Founder of Ainstein AI; and Michael Israel, Managing Partner at Revolve Wealth Partners. Their perspectives point toward a practical benchmark for AI: not how much technology a firm can deploy, but how much high-value work it enables advisors to do.
So, what do advisors really want from AI?
1. Capacity to Serve More Clients
Each new relationship brings more service requests, preparation, follow-up, implementation, and coordination. Unless the way work gets done changes, growth often means adding staff.
For RIAs, that makes growth fundamentally a question of scalability: How can a firm manage more clients without increasing advisor headcount at the same rate? The goal is to create nonlinear scale—to enable the same team to do more.
Michael Israel, Managing Partner at Revolve Wealth Partners, points to where the pressure accumulates. “The biggest capacity constraints for growing RIAs are centered around preparation and follow-up for client meetings, not the client meetings themselves,” he says.
Meeting preparation, CRM updates, service requests, planning implementation, trading coordination, and follow-up are essential, but their demands grow with every relationship.
AJ Emanuele sees economic opportunity in maintaining the client experience as the firm grows. Firms, he says, want to “add clients and AUM without needing to add people at anywhere close to the same rate, and without the client experience getting watered down.”
That is where the time savings become commercially meaningful: Emanuele says advisors are already seeing “things that used to take hours now take minutes.”
The first test of AI for a growing RIA, then, is whether advisor capacity can grow faster than the operational burden around it.
2. Personalization Across the Firm
Capacity becomes more valuable when firms use it to raise their standard of service. Historically, proactive and personalized attention has been easiest to deliver to a firm’s largest relationships. AI creates an opportunity to make that attention more systematic across the firm.
Israel says automation can help surface “planning opportunities, life events, service requests, and other moments that may warrant outreach.” Instead of depending on “chance or memory,” advisors can have a more consistent way to know when engagement matters.
Suzanne Cook, CEO and Founder of Ainstein AI, sees that intelligence moving closer to the advisor. AI-powered portfolios, she argues, can continuously deliver personalized information and insights directly within the portfolio.
“By making portfolios intrinsically smarter, advisors can actually be on the receiving end of AI,” Cook says, “supported to simplify their own work and scale their business, with far less time pressure and minutia.”
Emanuele offers a concrete example: one advisor sent more than 80 personalized year-end reviews “in about the same time it used to take to do just one.”
“That’s not a productivity trick,” Emanuele says. “It’s a totally different economics of service.”
That distinction matters. The objective is not to automate personalization. It is to make timely, relevant attention less dependent on an advisor having enough hours in the day to manage every client need manually.
3. More of the Client’s Financial Life
Serving more clients is one form of growth. Serving existing clients more comprehensively is another.
Tax, estate planning, insurance, retirement income, and other needs increasingly sit alongside investment management. But broader advice brings deeper operational demands: more information to gather, documents to interpret, tools to coordinate, and changes to track.
Israel argues that technology should absorb some of that complexity.
“When tax, estate, insurance, retirement, and planning tools are integrated into the firm’s existing technology stack, advisors can spend less time gathering information and managing processes and more time helping clients make informed decisions,” he says.
That can allow firms to broaden advice “without requiring a proportional increase in staff.”
A client’s financial life also never remains static.
“A financial plan or a set of legal documents is a snapshot of one point in time, but life never stops moving,” Emanuele says. Clients divorce, remarry, have children, sell businesses, add accounts, and change goals. His vision for AI is to continuously compare that changing context against plans and estate documents, “catching the gaps between what was assumed and what’s actually true now.”
Technology can help identify what changed and where an issue or opportunity may exist; the advisor determines what it means for the client.
As advisors become more comfortable with AI and the technology becomes more capable, I think we’ll also see new services become practical for advisory firms of more sizes. The opportunity is not to replace specialized advice, but to reduce the work required to bring more of the client’s financial life into view.
Why Does AI Need Connected Data?
None of this works particularly well if AI cannot understand the client and household across all the places their information lives.
Wealth technology has fragmented over time—not only across applications, but across the data inside them. Relationship history may live in the CRM, portfolio data in another system, account activity at the custodian, documents in a central file repository, and additional context elsewhere.
Increasingly, AI agents are appearing inside each of those individual point solutions. The problem is that an agent operating within one silo may not know what is happening in another, making it difficult for intelligence and workflows to span the business.
A unified data layer changes that equation by making information across systems available to intelligence that can understand a broader client and household context.
Emanuele describes the challenge as making data AI-ready: “structured and connected in a way AI can actually use.”
Once that exists across the book, he says, the role of AI can change significantly.
“You’re not just getting insights anymore,” Emanuele says. “You’re getting a true chief of staff, a virtual assistant that’s watching everything across the book and helping the advisor actually take action on what it finds.”
Connected data also has to produce output advisors can trust.
Cook points to explainability: transparent, data-driven reasoning that shows “exactly how and why the AI suggests certain strategies.” Israel adds the governance layer: AI-generated information still requires human review, alongside clear policies and security controls governing client data and AI tools.
For firms that are cautious about AI, there is no need to make the leap all at once. Start with day-to-day processes where the risk is lower. Understand how the technology works, build confidence in the problems it can solve, and expand from there.
The point of unified data is not integration for its own sake. It is creating a coherent view of the household so AI can surface what matters in context, and give the advisor enough visibility to decide what deserves action.
The Bottom Line
What RIAs want from AI is ultimately practical: more capacity for higher-value work.
That capacity can help firms absorb growth, extend personalized attention across more relationships, and make broader advice more practical to deliver. But realizing that opportunity depends on connected, trusted data that allows AI to understand the client and household as a whole.
AI itself isn't the objective. The real measure is what it enables advisors to do with the time, context, and capacity it creates.
Trevor Hicks is CTO, RIA Segment, Advisor360°
For more insights on AI, advisor productivity, and the future of wealth management, explore the latest thinking from Advisor360°.
Frequently Asked Questions
What do financial advisors want from AI?
For many advisors, the goal is not simply more automation, but greater capacity: serving more clients, delivering more personalized attention, and providing broader advice without a proportional increase in staff and complexity.
How can AI help RIAs grow?
AI can reduce manual work that grows with the client base, including meeting preparation, follow-up, service requests, documentation, and coordination—freeing more time for client conversations, advice, prospecting, and other higher-value work.
How can AI help financial advisors personalize client service?
AI can surface planning opportunities, life events, service needs, and other signals that may warrant outreach, making proactive service less dependent on an advisor manually monitoring every relationship.
Can AI help advisors provide more holistic financial advice?
AI can help advisors bring together and monitor information related to investments, financial planning, tax, estate planning, insurance, retirement income, and other areas. Reducing the information-gathering and review work around those conversations can make broader advice more practical to deliver.
Why does unified data matter for AI in wealth management?
AI is limited when client information is fragmented across CRM, portfolio, planning, trading, custodial, and other systems. A unified data foundation gives AI more complete household context, making it easier to identify relevant insights and support workflows across technology silos.
What does it mean for wealth-management data to be AI-ready?
AI-ready data is more than accurate data. It is structured, connected, governed, trusted, and available in a form AI systems can use across workflows. That foundation becomes more important as AI moves from generating insights toward helping advisors prioritize and take action.
What risks should RIAs consider when using AI?
Advisors and firms should consider accuracy, privacy, cybersecurity, data governance, and the use of unapproved tools. Human review remains important when AI-generated information could influence client communication or advice. Firms should establish clear usage policies, security controls, and appropriate oversight as they expand their use of AI.
