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18. The Truth About AI in Wealth Management: Tool or Trap? · Dime After Dime

• 0:00
  SPEAKER_01: What's a bad use of AI?
• 0:02
  SPEAKER_01: I would say that a very poor use of AI would be relying on it to make predictions, especially when those predictions are long-term, involve events that haven't been really seen yet in its training data, or when it requires a certain level of nuance or judgment that the AI wouldn't have context for.
• 0:24
  SPEAKER_00: You're listening to Dime After Dime, a Moran wealth management podcast.
• 0:28
  SPEAKER_00: Every episode, your host, Tony Steak, brings in financial professionals to discuss strategies and insights for investors who want to grow and protect their wealth.
• 0:36
  SPEAKER_00: With that, here's Tony.
• 0:48
  SPEAKER_02: Patrick Moran's here today, the CTO of Moran Wealth Management.
• 0:52
  SPEAKER_02: Patrick, thank you for coming on for the show to talk all things sophisticated investors in AI.
• 0:58
  SPEAKER_02: Why don't you introduce yourself to the audience, Patrick?
• 1:01
  SPEAKER_01: Sure.
• 1:02
  SPEAKER_01: My name is Patrick Moran.
• 1:03
  SPEAKER_01: I am the Chief Technology Officer at Moran Wealth Management.
• 1:06
  SPEAKER_01: How long have you been with the firm?
• 1:08
  SPEAKER_01: So I've been with the firm about a total of eight years.
• 1:10
  SPEAKER_02: Eight years?
• 1:11
  SPEAKER_02: And you've been dabbling in the technology stuff for most of your career, but now you're officially the CTO.
• 1:16
  SPEAKER_01: Yes, that's correct.
• 1:17
  SPEAKER_02: That's awesome.
• 1:17
  SPEAKER_01: I would say the technology portion of it started really ramping up about three to four years ago.
• 1:22
  SPEAKER_02: That's your passion, though.
• 1:23
  SPEAKER_01: Yes.
• 1:24
  SPEAKER_02: Yeah.
• 1:24
  SPEAKER_02: Passion, right?
• 1:25
  SPEAKER_02: Efficiency gains, um, just unlocking things around advice and how to deliver better advice, and of course, all the stuff behind it, the stuff around infrastructure and all that.
• 1:35
  SPEAKER_02: But today we're going to talk about something different.
• 1:37
  SPEAKER_02: As you know, the dime after dime audience is really that sophisticated investor.
• 1:41
  SPEAKER_02: They've they've achieved some level of financial success, right?
• 1:45
  SPEAKER_02: They might be in their late 30s, 40s, or even 50s.
• 1:48
  SPEAKER_02: And now the decisions they're making are they understand the ramifications.
• 1:53
  SPEAKER_02: This isn't just reallocating into different equities or stocks.
• 1:57
  SPEAKER_02: This isn't the 60-40 blend.
• 2:00
  SPEAKER_02: These decisions are really tough, right?
• 2:02
  SPEAKER_02: And why we thought you'd be perfect for this episode is because of the rise of AI, right?
• 2:08
  SPEAKER_02: And how the sophisticated investor might lean towards AI.
• 2:13
  SPEAKER_02: And we thought no better person than you to kind of talk through the good parts about AI and how it might help you, and then the not so good parts about AI and where it can lead one astray, right?
• 2:24
  SPEAKER_02: Because I think we're going to see that uh throughout the course of the next couple of years is where AI has its limitations and where humans should best be involved.
• 2:32
  SPEAKER_02: Absolutely.
• 2:33
  SPEAKER_02: All right, so let's uh dive right into this episode.
• 2:37
  SPEAKER_02: I think we we talked about the buzz, right?
• 2:39
  SPEAKER_02: We talked about all the buzz.
• 2:41
  SPEAKER_02: There's a few really impressive AI tools out there.
• 2:44
  SPEAKER_02: Thinking about the modern investor, start with the buzz.
• 2:47
  SPEAKER_02: Like, what's the hot things around AI that helps the modern investor?
• 2:50
  SPEAKER_02: And then let's talk about the shortcomings.
• 2:52
  SPEAKER_02: But start with the with the good stuff first.
• 2:53
  SPEAKER_02: Like, how can this, how can AI help an investor uh achieve their financial goals?
• 3:01
  SPEAKER_01: I think that for the sophisticated investor, AI is best thought of as a sort of diagnostic tool or diagnostic aid.
• 3:10
  SPEAKER_01: It can help you understand certain elements of your portfolio and how it may be affected in very limited ways, but it can help uncover perhaps different facets of your portfolio composition that you may not have really fully realized yet.
• 3:29
  SPEAKER_01: Um, and that can help inform your longer-term goals.
• 3:34
  SPEAKER_02: I love that.
• 3:34
  SPEAKER_02: So almost like a diagnostic tool.
• 3:36
  SPEAKER_02: Like that's that's an interesting way to put at it.
• 3:38
  SPEAKER_02: So like just to kind of give because it has AI, most AI technologies have like a lot of information at their fingertips, right?
• 3:45
  SPEAKER_01: And I think that's actually a great way to think about it, is that AI is very good at helping you surface what the relevant information is, and also if you ask it questions, it can help explain some of that information to you.
• 4:00
  SPEAKER_01: What's a bad use of AI?
• 4:02
  SPEAKER_01: I would say that a very poor use of AI would be relying on it to make predictions, especially when those predictions are long term, involve events that haven't been really seen yet in its training data, or when it requires a certain level of nuance or judgment that the AI wouldn't have context for.
• 4:23
  SPEAKER_02: That's very helpful.
• 4:25
  SPEAKER_02: So what you're suggesting is like from a historical perspective, like a rear-rear mirror, AI can really help, right?
• 4:31
  SPEAKER_02: But when you ask it or challenge it to look into the future, again, these are pattern recognition tools.
• 4:38
  SPEAKER_02: We shouldn't really rely on that data because it doesn't have the intellect that a human does, but also no one really knows what's going to happen in the future.
• 4:45
  SPEAKER_01: Yes, it's not a crystal ball.
• 4:48
  SPEAKER_01: And none of us are prophets either.
• 4:52
  SPEAKER_02: Right.
• 4:53
  SPEAKER_01: But there's something to be said about the level of experience and human judgment that can be exercised by a financial professional that these AI tools just wouldn't be able to match.
• 5:09
  SPEAKER_01: They wouldn't have the correct context, they wouldn't they wouldn't be able to answer questions that are open overly general or open-ended, such as should I retire in three to five years?
• 5:21
  SPEAKER_01: It can't answer that question because it doesn't know you.
• 5:24
  SPEAKER_01: Should I donate to charity?
• 5:27
  SPEAKER_01: Should I leave this money that I've accumulated over the course of my lifetime?
• 5:32
  SPEAKER_01: Should I leave it to charity?
• 5:33
  SPEAKER_01: Should I leave it to my kids?
• 5:35
  SPEAKER_01: It can't help you answer that.
• 5:38
  SPEAKER_02: What's really interesting there too, Patrick, uh, and I think you're kind of implying this, is that it will answer the question, though, and that's a mistake, right?
• 5:46
  SPEAKER_02: It and it'll make it sound so definitive in its answer.
• 5:49
  SPEAKER_02: But because it's it's relying on the limited information you provided and the large swath of data that it has, that it actually can be very um not damaging, that's the wrong word, but it's gonna answer in a definitive way, and it might kind of uh persuade the user to follow that path.
• 6:07
  SPEAKER_01: Yes.
• 6:08
  SPEAKER_01: I mean, I I would say something to understand about these systems is that the way they are designed, they're meant to produce an answer.
• 6:17
  SPEAKER_01: They are guided towards an answer.
• 6:20
  SPEAKER_01: So they have a very strong incentive to produce an answer, and if they don't have all of the information to accurately answer that, they will fill in the blanks, they will make things up.
• 6:30
  SPEAKER_02: Yeah, and that's a scary thing, especially when it comes to making decisions about your financial life, right?
• 6:36
  SPEAKER_02: So let's shift gears a bit.
• 6:37
  SPEAKER_02: You are, again, the CTO and you do a lot of technology shopping, right?
• 6:42
  SPEAKER_02: Yes, and part of your job is to kind of get past the marketing fluff, right?
• 6:48
  SPEAKER_02: And see through and understand, truly understand the technology and its limitations.
• 6:54
  SPEAKER_02: So, you know, if if you were to give advice to someone who's kind of looking at AI tools to help them along the way, how would you guide them, those investors, to making sure they're not falling for the marketing fluff and instead finding the right tool to help them again provide that diagnostic review like you suggested before?
• 7:14
  SPEAKER_01: Yeah.
• 7:15
  SPEAKER_01: Well, I would encourage people to look towards tools that one are very well documented and have extensive explanation on how they work and how to use them effectively.
• 7:28
  SPEAKER_02: Okay.
• 7:29
  SPEAKER_01: And two, uh lean towards tools that position themselves more as aids or assistants because that's the true role of technology, after all.
• 7:39
  SPEAKER_01: It's a tool.
• 7:40
  SPEAKER_01: I would steer clear of tools that make overly bold claims about forecasts or um entire replacements.
• 7:50
  SPEAKER_02: I like that.
• 7:51
  SPEAKER_02: I like that a lot because you're you're right at the end of the day, technology ought to compliment one, someone, right?
• 7:57
  SPEAKER_02: Be a compliment to them, not necessarily uh replacing them, especially when it comes to, again, these decisions around your financial life.
• 8:04
  SPEAKER_02: So you're cutting through the clutter, you're looking for well-documented platforms, you're looking at their logic and how they answer questions.
• 8:12
  SPEAKER_02: Is there any particular, you know, when you think about diagnostics, I I don't want to throw a curveball at you here, but when you think about you're given people, like let's just say you you want to use the technology, I don't want to name any names, but like what are the risks about importing your information into these tools, especially as it relates to your finances.
• 8:30
  SPEAKER_02: Are there risks there?
• 8:31
  SPEAKER_01: Oh, yes, there are absolutely risks there.
• 8:33
  SPEAKER_01: Um I mean, not to get overly technical here, but things you should absolutely be looking for, you should for any generative AI tool, you should be making sure that um they aren't training on your data, um, that they have uh zero data retention policies in place with any subprocessors.
• 8:53
  SPEAKER_02: Yeah, like zero day, right?
• 8:55
  SPEAKER_01: Well, zero zero data.
• 8:57
  SPEAKER_01: So essentially nothing's being so if if you have an AI tool, we're gonna call it um I don't know.
• 9:04
  SPEAKER_01: Mark.
• 9:05
  SPEAKER_01: Mark.
• 9:05
  SPEAKER_01: Yeah, mark AI.
• 9:07
  SPEAKER_01: And under the hood, it's actually using open AI models to power it.
• 9:15
  SPEAKER_01: And it's sending information that you put in to open AI, open AI does its thing and it sends back a response.
• 9:26
  SPEAKER_01: And this is done through something called an API, okay, an application programming interface.
• 9:32
  SPEAKER_01: You want to make sure that what MARC AI is sending to OpenAI isn't being retained by OpenAI.
• 9:41
  SPEAKER_02: Got it.
• 9:41
  SPEAKER_02: Because there's a there's a whole risk of obviously, you know, there's data penetration risk, PII risk, but also just generally speaking, like you are kind of open up the kimono a bit.
• 9:50
  SPEAKER_01: Yeah.
• 9:51
  SPEAKER_01: Right?
• 9:52
  SPEAKER_01: And that wasn't to name open AI in specific.
• 9:55
  SPEAKER_01: I mean, this this applies to pretty much any of the major model providers.
• 10:00
  SPEAKER_02: Yeah.
• 10:00
  SPEAKER_02: So let's so there's been some promises made by AI Tools, right?
• 10:04
  SPEAKER_02: They're they've suggested, you know, and generally speaking, if you know, with portfolios at least, they they might be able to show you risks that you missed, right?
• 10:12
  SPEAKER_02: Or exposures that you missed.
• 10:14
  SPEAKER_02: They might suggest that they can provide projections for you.
• 10:17
  SPEAKER_02: We talked about this before.
• 10:19
  SPEAKER_02: Um, are they living up to that hype?
• 10:21
  SPEAKER_02: Are they meeting those those suggestions, or are you not seeing, are you not seeing the results that they're promising?
• 10:29
  SPEAKER_01: I would say that for the most part, especially on the projection part, that is actually very much overhyped.
• 10:37
  SPEAKER_01: Um, they are good at surfacing data, they can help you catch things you may have missed or that you did not think about.
• 10:44
  SPEAKER_01: But ultimately, they're surfacing information, they can help explain that, but the judgment lies with you, the human.
• 10:53
  SPEAKER_02: Sure.
• 10:53
  SPEAKER_02: And what what we've already heard about this a bit, and I know you've seen this in your research.
• 10:58
  SPEAKER_02: There's also challenges with sources sometimes, right?
• 11:02
  SPEAKER_02: Where we're finding these AI models that are pulling up sources, you double check those sources, and either they're misconstruing the data, or that data's fabricated.
• 11:12
  SPEAKER_01: Yes, that's a very important piece of it.
• 11:14
  SPEAKER_01: And I think this gets to the question of responsibility.
• 11:17
  SPEAKER_01: Who's responsible for the output of any of these AI tools?
• 11:21
  SPEAKER_01: Ultimately, I I would say that it's the human.
• 11:24
  SPEAKER_01: It's the human reviewing it, it's the human reading it.
• 11:27
  SPEAKER_01: It can be challenging with the speed and the volume at which these tools can produce an output, but ultimately you have to review it to make sure it makes sense, to make sure it hasn't fabricated something or it it isn't relying on an unreliable source.
• 11:42
  SPEAKER_02: Yeah, so one I I think this is advice that you've given many folks at this firm that when and if you seek out information from uh an AI tool that you have to double triple check sources, right?
• 11:55
  SPEAKER_01: Yeah.
• 11:56
  SPEAKER_01: Yeah, sources and then also just an intuitive check.
• 12:00
  SPEAKER_01: You know, does this make sense?
• 12:02
  SPEAKER_01: Does this seem right beyond just a surface level superficial scan of it?
• 12:09
  SPEAKER_01: Because it will seem right at that level.
• 12:12
  SPEAKER_01: It will generate a plausible output, but you have to dig deeper to an a second level.
• 12:17
  SPEAKER_02: So let's get into like more like actionable things that an investor might use AI tool for.
• 12:22
  SPEAKER_02: So for instance, it might prompt, it might show it the portfolio to the AI tool, and it'll say things like, is my portfolio ready for inflation at 2%?
• 12:32
  SPEAKER_02: Or is my like essentially stress testing, right?
• 12:36
  SPEAKER_02: Or saying, is my portfolio ready for a correction?
• 12:39
  SPEAKER_02: Do you think AI in its current state can answer those questions validly?
• 12:45
  SPEAKER_01: Those questions, I would say probably no.
• 12:47
  SPEAKER_02: Probably no.
• 12:48
  SPEAKER_01: Probably no, because I would say those questions are a little bit too general.
• 12:51
  SPEAKER_02: Okay.
• 12:52
  SPEAKER_01: So it'll fill in the blanks with what you've given it, and that may be applicable to your circumstance, or it may not be.
• 12:59
  SPEAKER_02: Because there's a lot around the demographics, your financial demographics, your social demographics that that an advisor across the table can get from you, right?
• 13:08
  SPEAKER_02: But AI, it's not going to ask you, tell me more about you.
• 13:12
  SPEAKER_01: Exactly.
• 13:13
  SPEAKER_01: Well, actually, some of them will provide follow-up questions at the very end of it.
• 13:18
  SPEAKER_01: But I would say that's actually probably a better way to engage with AI for the average person.
• 13:23
  SPEAKER_02: Okay.
• 13:23
  SPEAKER_01: Far too many people ask it for just to do something or do produce an output as an end product when a more iterative back and forth conversation where you ask it to kind of explain how this connects to this or why this is this way will ultimately give you a better end result.
• 13:46
  SPEAKER_02: So let me let me uh throw a curveball at you, right?
• 13:50
  SPEAKER_02: Um and I know you know a lot about risk, right?
• 13:53
  SPEAKER_02: And the scoring of risk, right?
• 13:54
  SPEAKER_02: The propensity of an investor uh for risk.
• 13:57
  SPEAKER_02: And this depends on time horizon, of course.
• 14:00
  SPEAKER_02: Um, and what we usually rely on here is stated risk scores, right?
• 14:04
  SPEAKER_02: We ask a series of questions, right?
• 14:06
  SPEAKER_02: And and an AI tool could do that, right?
• 14:09
  SPEAKER_02: But we still have the intuitive nature as humans to look across the table and look at them as an investor, having empathy, sympathy, and in turn, we might.
• 14:22
  SPEAKER_02: I'm not saying we're gonna change their risk score, but we can analyze those answers based on what we see on the paper.
• 14:27
  SPEAKER_02: An AI tool can't do that.
• 14:31
  SPEAKER_01: An AI tool could give you a number.
• 14:34
  SPEAKER_02: On the questions it asks, right?
• 14:36
  SPEAKER_01: But the thing is, it's always going to be assuming that you are answering those questions perfectly truthfully.
• 14:43
  SPEAKER_01: When in fact we often deceive ourselves about the amount of risk that we're willing to take.
• 14:49
  SPEAKER_01: And it takes an experienced professional to really sort through that and know how to really get to the truth of the matter.
• 14:59
  SPEAKER_02: So let's talk about like multi-generational planning, retirement planning, very long-term, kind of larger goals, if you will.
• 15:07
  SPEAKER_02: Um can we rely on the projection?
• 15:11
  SPEAKER_01: Okay, I'm just gonna say no, on that one.
• 15:15
  SPEAKER_01: Uh it could probably handle basic scenario analysis, stress testing, um, on a first order level.
• 15:23
  SPEAKER_01: But for the kind of multi-generation or long-term planning you're talking about, uh one, as I mentioned, it's not a crystal ball.
• 15:33
  SPEAKER_01: And then two, those topics often involve a great deal of nuance and context and judgment, um, and empathy, human understanding that the AI probably isn't going to have unless you literally wrote all of that out for it.
• 15:50
  SPEAKER_02: Yeah, and oftentimes, again, it goes back to the stated versus like the the known.
• 15:55
  SPEAKER_02: But even across like when we deal with multi-generational wealth here, it's also three or four different people across the table from the client, right?
• 16:04
  SPEAKER_02: We have an attorney present, we have a state planning specialist present, we have the advisor present, we have a large swath of, again, intuitive humans empathetic to your situation.
• 16:14
  SPEAKER_02: Whereas the human with the AI tool, it's just black and white.
• 16:19
  SPEAKER_02: It's just matter-of-fact.
• 16:20
  SPEAKER_02: And there's details within the details, right?
• 16:23
  SPEAKER_02: Yes.
• 16:24
  SPEAKER_02: And even more so, I think with AI too, some people might look at an advisor shop and say, oh, you know, they charge money or whatever it is, um, and they're not doing everything in our best interest or whatever.
• 16:36
  SPEAKER_02: And I I challenge those folks to say, okay, fine, let's just say you don't want to pay an advisor for the services.
• 16:42
  SPEAKER_02: But aren't you will you're so you're willing to take the risk that the mistake you might make with an AI tool could be far larger in terms of the potential loss than paying a team to help you along that way.
• 16:54
  SPEAKER_02: Like, what is the, you know, and this is not a question for you really, but just imagine asking people to put a dollar figure on that to say, are you really prepared to impact multi-generational wealth strategies, your children's estates, because you want to save a few dollars and use AI?
• 17:10
  SPEAKER_01: I would say that's not worth the risk.
• 17:13
  unknown: Right?
• 17:13
  SPEAKER_01: I mean definitely.
• 17:14
  SPEAKER_01: I mean, it perhaps you could use it to help explain perhaps some terms you are unfamiliar with.
• 17:20
  SPEAKER_01: Use it to help rephrase or express your thoughts, your opinions, your values in a different way that's more organized or perhaps um more concise, really gets to the heart of what you want to convey to an advisor in a more effective manner.
• 17:39
  SPEAKER_01: But it can't provide the actual advice.
• 17:42
  SPEAKER_02: Sure.
• 17:42
  SPEAKER_01: At least not truly.
• 17:45
  SPEAKER_01: It will probably provide some something that looks like advice, and it'll seem plausible, but I think you should ask yourself do you really have any way of knowing whether the advice it's giving is grounded in the realities of your life?
• 18:02
  SPEAKER_02: I love that.
• 18:03
  SPEAKER_02: That's a great one.
• 18:04
  SPEAKER_02: Um let's shift gears even more, okay?
• 18:07
  SPEAKER_02: Because you're you're CTO of an advice uh nice uh RA firm, and a lot of advisory firms are now promoting the use of AI, right?
• 18:14
  SPEAKER_02: We obviously, if you use Microsoft, there's Copilot.
• 18:16
  SPEAKER_02: There, of course, there's different AI models for financial advisors now.
• 18:19
  SPEAKER_02: There's note takers everywhere, you're seeing it, you look at them every day.
• 18:23
  SPEAKER_02: Um but put your investor hat on and you're gonna go to an advisor shop, an RA, and you're gonna say, Hey, I'd like, you know, please provide me some financial advice.
• 18:33
  SPEAKER_02: And they say, by the way, we use AI tools, or this is how we you know operate.
• 18:37
  SPEAKER_02: What questions as an investor would you want to ask those advisors before doing business with them?
• 18:43
  SPEAKER_01: That is a fantastic question, Tony.
• 18:46
  SPEAKER_01: I see, I I love that question.
• 18:48
  SPEAKER_01: I really do.
• 18:49
  SPEAKER_01: Because at first, simply them mentioning that they use AI.
• 18:54
  SPEAKER_01: Well, I think the natural follow-up to that is well, how are you using AI?
• 18:59
  SPEAKER_01: That will provide you far more information than just the fact that they're using AI.
• 19:03
  SPEAKER_01: It's all about how are they using AI?
• 19:06
  SPEAKER_01: Are they actually using AI as a productivity expander?
• 19:12
  SPEAKER_01: Are they using it to enhance the services they provide to their clients?
• 19:15
  SPEAKER_01: Or are they using it to replace personalized service with a very robotic and synthetic automation?
• 19:29
  SPEAKER_01: And you want the personalized service.
• 19:30
  SPEAKER_01: AI used properly is actually a great enhancer of personalization.
• 19:39
  SPEAKER_01: AI used poorly can lead to an erosion of judgment, um, a sort of almost milk toast feel.
• 19:50
  SPEAKER_02: Big word uh erosion of judgment.
• 19:52
  SPEAKER_02: I love that one.
• 19:53
  SPEAKER_02: Um What about data security though?
• 19:56
  SPEAKER_02: Like if you're again, you walk in the door to an advisory shop, they're like, hey, we're gonna use AI, like what questions would you want to ask them around data security?
• 20:02
  SPEAKER_01: Well that would be that would probably be my second question to them.
• 20:06
  SPEAKER_01: One, I would want to make sure that they had you know proper risk controls in in place because that would it's my data.
• 20:12
  SPEAKER_01: I want to know that it's being used responsibly and securely.
• 20:15
  SPEAKER_01: And on the technical side, you know, you can start to get into is it encrypted at rest?
• 20:20
  SPEAKER_01: Is it encrypted in transit?
• 20:22
  SPEAKER_01: Are there zero data retention policies in place?
• 20:26
  SPEAKER_01: Um, which subprocessors are they actually using?
• 20:29
  SPEAKER_02: So that's I mean, that's great because I think those two, those are probably the two big questions, right?
• 20:34
  SPEAKER_02: First being, is this AI tool you're implementing designed to help the client experience to make my interactions with you better, more meaningful, more fruitful, or is it to replace you to do less work?
• 20:48
  SPEAKER_02: Because if it's the latter, not ideal.
• 20:51
  SPEAKER_02: If it's the former, great.
• 20:52
  SPEAKER_02: That gives me more FaceTime with the advisor.
• 20:54
  SPEAKER_02: You might be offering more services now with the AI.
• 20:57
  SPEAKER_02: But the second one's just as important because it is your data, right?
• 21:01
  SPEAKER_02: It's your personally identifiable information.
• 21:04
  SPEAKER_02: And if that is at risk, right, there's significant ramifications.
• 21:09
  SPEAKER_02: So, which is why not to toot your corn, but when you see an RAA that has a CTO, you know those SOPs, standard operating procedures are in place.
• 21:20
  SPEAKER_02: You know you have the infrastructure, you know you have the risk, right?
• 21:23
  SPEAKER_02: You have it all built out because that's your responsibility.
• 21:26
  SPEAKER_02: Where a lot of these you know firms, smaller firms especially, they don't have that.
• 21:30
  SPEAKER_02: And they're just putting trust in the person that sold them the software.
• 21:34
  SPEAKER_02: And if something goes wrong, who points the finger where?
• 21:38
  SPEAKER_01: Exactly.
• 21:38
  SPEAKER_01: Which is why it's important to do your due diligence.
• 21:42
  SPEAKER_01: Um, just speaking from my own personal experience, to do due diligence on the other firms you're working with, the tools you're using.
• 21:49
  SPEAKER_01: Are they handling the data that you're handing them securely?
• 21:53
  SPEAKER_01: Are they handling it responsibly?
• 21:56
  SPEAKER_01: Um, and then more from a business perspective.
• 21:59
  SPEAKER_01: Is this actually?
• 22:00
  SPEAKER_01: Actually enhancing the services you provide.
• 22:03
  SPEAKER_01: Is this benefiting the client?
• 22:07
  SPEAKER_01: Or is this just saving time?
• 22:10
  SPEAKER_01: Is this just replacing tasks and you're calling it a day?
• 22:14
  SPEAKER_01: The latter is not so good.
• 22:16
  SPEAKER_01: The former is really what it should be used for.
• 22:20
  SPEAKER_01: I mean, AI properly used um can be very beneficial in helping to surface relevant data, such as data from the CRM before the meeting.
• 22:29
  SPEAKER_01: When you have a question, being able to actually query an internal database or CRM for the particular details on a client or a portfolio and surface that automatically without having to go and search for all of those things can be very beneficial.
• 22:49
  SPEAKER_01: It's great for automating routine tasks, which saves time by eliminating the need for a human to do those tasks.
• 22:57
  SPEAKER_01: But then the question is, what do you do with that time?
• 22:59
  SPEAKER_01: Are you are you using it to just cut costs?
• 23:03
  SPEAKER_01: Are you are you using it to go golfing?
• 23:06
  SPEAKER_01: Yeah.
• 23:06
  SPEAKER_01: Or are you using it to increase the level of service you're providing?
• 23:11
  SPEAKER_02: That's a a great question to be asking.
• 23:13
  SPEAKER_02: Is like what the why of implementation, but also like what is the outcome?
• 23:18
  SPEAKER_02: What is your objective goal?
• 23:20
  SPEAKER_01: If you went to an advisor and they said that they used AI, but after working with them for a while, you found that you spent most of your time speaking with and interacting with apps and dashboards and automated notifications rather than talking to an actual person or getting communication from an actual person that was tailored to you.
• 23:44
  SPEAKER_01: That should be a red flag.
• 23:45
  SPEAKER_02: Yeah, no, I love that.
• 23:47
  SPEAKER_02: All right, one more one more segment here.
• 23:49
  SPEAKER_02: Um at the beginning, you talked about how AI tools can't predict the future.
• 23:54
  SPEAKER_02: But I'm gonna ask you to predict the future uh in wealth management.
• 23:57
  SPEAKER_02: Three to five years, how do you see AI, you know, in a positive way changing the wealth management space, especially in the in the eyes of the end investor?
• 24:07
  SPEAKER_01: I think that AI in the wealth management space will over the next three to five years will lead to greatly increased personalization, more responsive reports, dashboards, reporting that are tailored to you and what the the end investor cares about.
• 24:26
  SPEAKER_01: It'll lead to greater personalization, a greater level of service, and a more responsive experience for the client.
• 24:35
  SPEAKER_02: Yeah, and with with me, with personalization also means maybe more services, right?
• 24:40
  SPEAKER_02: Like more time to help you with the state planning or more time to help you elsewhere that does take more time, right?
• 24:47
  SPEAKER_02: And if we can unlock efficiency gains with AI so the advisor can be across the table more frequently, that's a win-win.
• 24:53
  SPEAKER_01: I would say so.
• 24:54
  SPEAKER_01: I mean, because AI has the potential to automate and to eliminate a lot of the very repetitive, albeit necessary, sort of background or back-end tasks that are just a function of this business.
• 25:12
  SPEAKER_01: But then that time savings can then be spent on what is actually important to the client, to the end investor.
• 25:19
  SPEAKER_02: Yeah, that's awesome.
• 25:20
  SPEAKER_02: I love it.
• 25:21
  SPEAKER_02: I love all of this.
• 25:21
  SPEAKER_02: I'm gonna ask you one more question, though, because this last segment was my favorite, because there are trade-offs, right?
• 25:27
  SPEAKER_02: If you if you're working with a firm that's gonna be really AI at the forefront, AI, right, versus a traditional firm, there are trade-offs.
• 25:35
  SPEAKER_02: And again, I think it's probably an unfair question to ask you, but as the as the investor, like, what should you be thinking?
• 25:41
  SPEAKER_02: Like, if you're gonna move forward a more AI-focused RA firm, you know, is it questions you're asking, or are there trade-offs versus more of a traditional firm?
• 25:51
  SPEAKER_02: And I I know it's it's it's pretty it's too open-ended.
• 25:54
  SPEAKER_01: No, I actually I I love this question too.
• 25:56
  SPEAKER_01: All right.
• 25:56
  SPEAKER_01: Uh because there isn't.
• 26:00
  SPEAKER_01: That's that's the that's the actual answer.
• 26:03
  SPEAKER_01: There isn't so much a trade-off whether in our whether a firm is using AI or is AI forward and versus a firm that isn't.
• 26:10
  SPEAKER_01: What the end investors should really be evaluating on are all the things that have always mattered.
• 26:16
  SPEAKER_01: Service, trust, reliability, agreement with the philosophy of their investments.
• 26:25
  SPEAKER_01: I mean, those are the things that have really always mattered for end investors who want to use the service the services provided by an investment advisory firm.
• 26:38
  SPEAKER_01: So whether they use AI or not, I think the end investor should actually be evaluating their experience on the same criteria.
• 26:48
  SPEAKER_02: I love that.
• 26:49
  SPEAKER_01: The burden is on the firm to use AI properly and responsibly to enhance the level of those services.
• 26:57
  SPEAKER_02: What a great way to wrap the episode.
• 26:58
  SPEAKER_02: I love that Patrick was thank you so much for joining coming on the show, Patrick.
• 27:02
  SPEAKER_02: We went all around the world with AI.
• 27:04
  SPEAKER_02: I feel like there's a lot of like insight and actionable items that these investors can be asking their advisory firms or if they're doing it themselves and going alone.
• 27:14
  SPEAKER_02: So thank you so much, Patrick.
• 27:15
  SPEAKER_01: Absolutely.
• 27:16
  SPEAKER_01: My pleasure.
• 27:17
  SPEAKER_02: I hope you all enjoyed the show too.
• 27:19
  SPEAKER_02: If you did, don't forget to like and subscribe, but also share this with a friend or family member who is trying to navigate their ways through their lives financially.
• 27:27
  SPEAKER_02: One dime after dime.
• 27:29
  SPEAKER_02: Again, I'm Tony, your host.
• 27:31
  SPEAKER_02: Thank you for joining us here today.
• 27:32
  SPEAKER_02: And Patrick, thank you again.
• 27:33
  SPEAKER_00: Thank you so much, Tony.
• 27:37
  SPEAKER_00: Thanks for listening to Dime After Dime.
• 27:39
  SPEAKER_00: To hear more episodes, follow us on your favorite podcast app and visit MoranWealth.com.
• 27:46
  SPEAKER_00: Moran Wealth Management LLC is an SEC registered investment advisor.
• 27:50
  SPEAKER_00: Registration as an investment advisor does not imply a certain level of skill or training.
• 27:54
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• 28:05
  SPEAKER_00: A copy of Moran Wealth Management's current writ disclosure statement as set forth on Form ADV discussing Moran Wealth Management's business operations, services, and fees is available from Moran Wealth Management upon written request or at advisorinfo.sec.gov.
• 28:19
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