Guest: Matt Reiner, CFP®, CFA®, Managing Partner, Senior Investment Advisor at Capital Investment Advisors, a $7 billion AUM firm with more than 100 team members.
In a nutshell: For financial advisors, the question isn’t whether to adopt AI, but how to use it in ways that deepen client trust, enhance efficiency, and future-proof your practice.
On today’s show, Matt Reiner and I dive deep into the current state of AI in wealth management, including the mindset shifts advisors need to make so that they can scale smarter and stay ahead of the curve.
.Matt Reiner and I discuss:
- The rise of agentic AI and how advisors can experiment with new tools to gain efficiency without losing the human edge.
- Overcoming compliance, privacy, and cultural adoption challenges.
- How the “Human in the Loop” (HILP) Principle can leverage AI to save time while maintaining quality control.
- Matt’s framework for balancing risk-averse innovation, speculative innovation, and exponential innovation in tech adoption.
- The importance of high-EQ advisory skills.
- How to frame AI as a tool that will elevate team members rather than replace them.
- Working backwards from your desired outcome to identify potentially impactful AI integrations.
Matt Reiner on the most common AI integrations in wealth management:
“ First and foremost, a lot of firms are using AI notetakers, which I think is a big step up in organizing and staying up to date. I think that that’s the most adopted because it seems the simplest and the lowest barrier to entry for advisors. The AI notetaker creates a summary of the meeting, creates a list of action items for both me and the client or prospect. Then it also can create that final follow-up email to anybody on the team or the client. And some of these notetakers allow you to also push into CRM. I’m starting to see teams do that for efficiency and organization. And then the final way that I do see some people use it is as a transcription tool.
“And then, of course, I think you see a lot of advisory firms now starting to adopt large language models LLMs) like ChatGPT. But I think that those are still way far behind the AI notetakers these days. What I’ve been hearing as I talk to other advisors is that whether their firm allows them to or not, team members are using one of those LLMs within their day-to-day, and they have familiarity with them because they’re using it in their personal life. And they find value in it and they’re bringing it into their professional life. I think that firms should move forward on trying to create an infrastructure to allow AI to be within the organization.”
Matt Reiner on “agentic” AI:
“I think the easiest way of thinking about agentic AI is it is executing on your behalf. I have one agent with only an understanding of our investment committee research, and then another agent that is only understanding of how to read our portfolio statements, and another agent that is only understanding of our Salesforce environment. On top of that, you have a ‘queen bee’ or an an agentic leader that gets a task from me. That bee will then go to each of the other agents and work on your behalf, like a human going to their team. It’s working without being told exactly what needs to be done. It knows what to do, and I believe that is the future. Teams are going to have human employees and we’re going to have agentic employees. McKinsey recently just launched 12,000 agents that they’re managing to help with every aspect of that business right now.”
Matt Reiner on staying curious and experimenting with AI:
“ First and foremost, stay curious and always be curious about what’s going on in AI. I think that this is a paradigm shift in the world of how we work and how we live. I would challenge organizations to start thinking more like Google than Goldman. Start thinking about how do you brainstorm, how do you create the psychological safety within your organization for a new employee to come in and say, ‘I think you’re doing this wrong, and this tool could really help,’ and accepting that. And I think that I would ask everybody to experiment. That’s part of staying curious. Experiment with these technologies and learn something new. Because every new innovation that’s going to happen within your organization is built on lessons that you’ll learn in every one of those failures or those experiments that you do. And it may not be applicable today, but there will be an applicability to that information you gain in the future.”
