The Advisor Journey

Navigating the AI Future for RIAs and More with Jason and Dasarte

Episode Summary

Jason and Dasarte discuss the ethical considerations surrounding AI in finance and how financial advisors can balance technology and the human touch. The hosts also share practical insights on how advisors can integrate AI seamlessly into their practices, unlocking new avenues for growth and client satisfaction. ABOUT ALTRUIST: We’re on a mission to make financial advice better, more affordable, and more accessible to everyone. Altruist is an all-in-one platform built exclusively to help RIAs start, run, and grow their practices. Our platform saves you time and reduces your costs: You can manage your entire book of business, get performance reporting, and bill your clients with ease and efficiency. Want to find out how Altruist can help you grow? See more at STAY CONNECTED: Instagram ► Twitter ► Linkedin ►

Episode Notes

Jason and Dasarte discuss the ethical considerations surrounding AI in finance and how financial advisors can balance technology and the human touch. The hosts also share practical insights on how advisors can integrate AI seamlessly into their practices, unlocking new avenues for growth and client satisfaction.


We’re on a mission to make financial advice better, more affordable, and more accessible to everyone. Altruist is an all-in-one platform built exclusively to help RIAs start, run, and grow their practices. Our platform saves you time and reduces your costs: You can manage your entire book of business, get performance reporting, and bill your clients with ease and efficiency. 

Want to find out how Altruist can help you grow? See more at


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Episode Transcription

JASON: Hey friends, this is Jason with my friend Dasarte Yarnway. And we are really excited to talk about scaling your advisory firm. And, you know, how you can use support staff, how you can use tools. And we'll spend probably more time than we should talking about AI and hopefully dispelling some myths about the overlords coming and taking all of our jobs and financial planners being unnecessary. Spoiler alert, that won't happen. But we'll tell you kind of why and show you some best practices on building your team. When to hire, how to think about paying them, what you should and shouldn't be doing and then where to use people versus technology. So, super jam packed episode. I'm stoked to be hanging out with Dasarte. We're finishing 2023, strong jumping to '24. We're super, super excited about it. If you're listening on your favorite podcast platform, please make sure to subscribe, like, share and drop a comment. Actually, the comments are incredible because it's really fun for us to see what you're thinking. It also helps the podcast reach more people. We started this journey, The Advisor Journey that is, because we really believe in human delivered advice. We want to make it better. We want to make it more affordable. We want to make it accessible to everybody. The best way that we can do that is not just build tools for advisors, but also to share some of the best practices. And so if you're listening and you're learning just know that there's probably tens of thousands of other advisors out there that could really benefit as well. So help us spread the news. With that said, let's jump right on in.

JASON: Welcome to The Advisor Journey, a podcast by Altruist dedicated to giving advisors the edge they need with proven RIA growth strategies. Each week, Dasarte Yarnway and I will have hard hitting conversations about the topics that matter most to the modern RIA. How to scale, how to maximize efficiency, and how to effectively reach your goals. It's real advice from people who've really done it and we're so glad you're here.

DASARTE: Welcome back to another episode of The Advisor Journey. I'm your co-host Dasarte Yarnway, along with my partner in wealth, Jason Wenk. Jason, what's going on?

JASON: Lots going on, but I'm stoked on this episode. We get to talk about, I mean, a lot of things, but I do know we're going to talk a little bit about AI, which we haven't talked much about, actually. Just, like, little dips here and there. So kind of fun to riff on that. Not just that, but just in general how advisors can use support, people, tools to accomplish more for their clients, which is a ton of fun. So stoked on the episode. Life's good. No complaints. How about you?

DASARTE: No complaints. Life is good. I'm so happy with where I am in my business, and I can't wait to talk about the support staff stuff, because we've been talking about giving up control and inviting people to help you on your mission to scale your business. And I think this could have a lot to do with that. Now, let's just talk about this, support is necessary for a business. I think that for all intents and purposes, you can't do it by yourself. And I think that I thought I was a super hero, and I've learned very quickly that I need help. Whether that's help through technology, help through human hands. And I know for you, when you were running your business, you prioritized getting the right people in the right seats, paying them well so that could help you grow. Why don't you remind us of that story? I remember hearing you, like, I paid myself a small amount to pay an assistant very well. And that really made a big difference in your firm.

JASON: The first thing I'd say is, look, I don't get this always right. The older I get, the more I realize how little I used to know. There was a time period in my 20s, probably where I was like, I think I know everything now. What else is there to know now that I'm 26? And then when I got in my 30s, I was like, Well, I'm sure glad I know as much as I do now that I'm in my 30s, because I was a real idiot in my 20s. And now that I'm in my 40s, I'm like, God, I was so incredibly inept and I still am. All of a sudden you get this moment of self-revelation. You're like, I still have so much to learn. So all that bravado about figuring it all out kind of goes out the window. So I think the sooner you can realize, one, that you're always in a constant state of learning, there's people you can learn from, things you can do better, the better off you are. But I am very grateful that very early on in my journey, there was just like, you know, I'm a math person for those who don't know. I was a computer science major and always pretty interested and good at math and sciences. And so, this is going to sound incredibly simple, but I remember reading early in my career once about how, listen, if you work backwards, let's just say that you have a business and you're like, I want my business to generate $200,000 of revenue. Just hypothetically. And if you're just like, you know, again keep it really, really simple, you're like, Okay, and I'm going to put in 2000 hours a year, which is a fairly full year, but it just keeps the math simple. So all of a sudden you're like, If that's the case, then, if I want to make $200,000 of revenue and I have 2000 hours that I can work a year, you can do pretty basic math and go, If I do that, all the work I do has to be worth at least X dollars an hour. But just, again, insert your math program if you want to make $500,000 or whatever it's obviously going to be more. $250 an hour versus $100 an hour and so forth. So then you start to go, Well, what things do I do that are worth less than $100 an hour? If I want to do $200,000 of revenue on 2000 hours of my time, what things can I do that are, you know, because the other thing that's interesting is, I was like, I'd read this thing and be like, some of the stuff you do, you're making like $500 an hour or $1,000 an hour. And I'd be like, damn. Okay. So, it just became a math exercise for me in the early days where the cheat code was just, how many things I did that were really high value tasks? And then, who could I get to do the other stuff, maybe as good or better than when I was doing it? Especially for something I didn't like. Even better. So yeah, the way the story goes for me is when I kind of hit like, you know, I was probably like right around $100,000 of revenue that was fully from my work. So I was basically productive to the tune of like $50 an hour, but I realized that when I was using my time well, I was generating a lot more than $50. Like, a couple hundred dollars an hour. So I was like, I need to find somebody else to do all the other stuff. And instead of getting a relatively, again, when you think about, the tasks you do, I was like, I could find somebody that I could pay $20 an hour or $15 an hour, but they're probably only going to be able to do $15 and $20 an hour tasks and I'll still have to do the things that are $30 and $40 and $50 an hour tasks. And that's not very efficient for me. So I just was like, what would it take for me to be able to basically transfer anything that was a sub $100 an hour task to somebody, even if I had to pay them, whatever, $50 or $75 an hour? Something that was a relatively high wage. And so I forget the exact number off the top of my head, but I want to say I hired somebody and paid him $75000 so that I could make $25000. But it just freed up all the time. This person could take care of clients. They did the books. They paid the bills. All the stuff that I didn't like to do, or kind of was under this kind of dollar per hour threshold. And man, I got more productive. All of a sudden it was like, Whoa, I can add more clients. I can provide better services to clients, which allows me to have happier clients, who'll give me referrals. So, there's all this leverage you get. And that's a very simplified way of thinking about it, but it just resonated with me because I was just a math guy and I was like, Well, I mean, hard to argue with that math. And I trusted it and it worked out really well. The business basically doubled within 12 months. And so it went from, again, you can do the math, I probably had $10 million of assets or something to do $100,000 a year of revenue. And then the next year was $20 million of assets. And then the next year I doubled again, brought in 20 more new million dollars. Then after that, it was like every year was 25, 30 million a year. And a lot of that was from just one employee. I didn't hire three or four $15 an hour people. I hired one person and paid them really well. A lot more than I was paying myself at the time.

DASARTE: Do you think that an advisory firm can grow without support? Because I found myself, obviously, I use this analogy. It's called clearing the runway. So, essentially my philosophy, you tell me how you think about this, is that if you have a lot of garbage distraction and just things on your runway, it's going to be hard to have your goals land. So part of the exercise for me is taking the things that I probably don't need to be doing. Maybe I'm going to too many conferences or maybe I'm just not focused. On social media, right. Taking those things off of the runway so that I can land on my goals. That's number one, just getting clear about what I want to achieve and what's not serving that. But in addition to that, there are things that I don't want to do. But I have seen, not even a handful, just a few advisors that are doing ridiculous numbers by themselves. So I guess the question is, at what point should someone be looking at a person or technology to scale their business? Is it a dollar amount? Is it foreseeing problems? Is it just, I don't like to do this? And then we'll get into how AI can support that.

JASON: So first of all, there's nothing wrong with being a solopreneur. I know advisors that it's just them. They work from home. No staff, small number of clients, really happy people with great lives. And their clients are really happy, too. So, I think hiring for the sake of hiring, not the world's greatest idea. First, know that there's a need. And a lot of times that need is going to be what you just mentioned. It's either going to be, I really despise doing this, or I feel really insecure about the value I'm providing my clients because I'm wasting too much time on minutiae. That's more people related, I'd say. Your question on the tech side, I think almost always people should be, if there's a better way to automate something, you know, like, again, an overly simplistic example would be, if you run a meeting with somebody and you have CRM and you're able to just hit a button in your CRM to kind of prompt a follow up sequence that automatically crafts a thank you email to the client and then knows that they're going to be due for a new review meeting, let's say, in a few months. And so then it automatically sends that out and gives them a booking link to book. That's a better experience for the customer. It's way better for the advisor. And it's much cheaper than hiring people to solve that problem. That's a very inexpensive low lift thing that now can just free up a lot of time, versus like, oh, I'm putting a reminder in a notebook. There's a lot of things that you can just automate that would save people a lot of time. Where tech goes wrong is when people spend so much time monkeying around with the tech that you would have been better off just picking up the telephone and calling your client. So, I think if you're really careful about trying to overoptimize tech to solve problems and, similar with employees, don't get caught in the vanity of like, oh, we've got ten people on our team or something. When it's like, if five of them are doing 90% of the work, get rid of the other five. Keep the five that are doing all the work. That's just a good business principle. But a lot of advisors, and myself, most of us weren't entrepreneurs to begin with. We were practitioners. And that's a different muscle, learning how to be an entrepreneur and think about, okay, managing people. Not exactly the same as doing financial plans or managing portfolios. And so you just have to be ever the student and be okay being uncomfortable sometimes because it will be different, hiring and managing people.

DASARTE: I just want to hone in on that. Where tech goes wrong. Now from this podcast, some advisors will reach out to me like, hey, I want to pick your brain for a little bit. So did a number of those calls over the course of this year. And I find people talking about their tech. Like, I have done all this with tech and I'm automating this. And every call is about tech. It's like, when do you meet the people at that point? So I agree 100% that people spend a lot of time on tech, and sometimes that's just a distraction from the bigger issue, which is the fear of putting yourself in the world to attract your type to your client. So I just want to say that loud and clear, if this is you listening to the podcast, this is your signal. Go get the people.

JASON: And I think, as it relates to tech, I mean, I don't know if this is a good golden rule or  simple rule to kind of frame around, but I would generally try to figure out what are the least amount of tools I can possibly have to deliver the outcome I want for my clients. Because where I see it go wrong is where someone's like, well, I use these three different financial planning tools. Well, because my clients are so different. Some benefit from this one, some from this one. And I'm like, well, that sounds like it's not just a tech problem that sounds like a client problem. Meaning you said yes to too many different types of clients. You shouldn't, you know, how do you possibly even get your brain to go from three different client personas that are so radically different that they have to require different financial planning tools? So super common mistake. And I'll just sell my own book here for a minute. Being multi-custodial when you have under $1 billion is just absolutely bonkers. It's just the biggest waste of time and you lose so much efficiency. It boggles my mind why the industry is sort of, like, people have a trigger. It's like, oh, wait a minute, I filed my ADV. I've got a 150 million. I better add another custodian. And I'm like, but why? Why would you ever do that? And now again, we're unpacking that for people. We're helping people be like, okay, you don't need three custodians. You can have one. And it's working here. But I do think that people forget that you start adding not just tech, but getting vendors and all of a sudden it's, well, when I want to do an RMD, here's the process of this firm, here's the process of that firm, here's the process of this other firm. And a client wants to do a qualified charitable distribution. Well, here's the process of this firm. All of a sudden your staff have to be cross trained. People are less efficient. You're calling different support people for different needs. So, it's a lot of things that people could be doing to be more efficient. More is not more. Oftentimes less is more. So, less vendors as possible to deliver really killer outcomes to clients. And you will find you have a lot more time, a lot better margins. Your employees will be happier, you'll be able to retain them. So you won't be constantly having to hire new people. It's a net net. Everybody wins. But it's very easy in this industry to kind of, yeah, get sucked into, like, I better hire more people because I'm at a certain size. Or I better add more tech because I'm at a certain size. And oftentimes that's just not the real reality.

DASARTE: I love that. One of my biggest sayings is less is more when less does more. And because advisors, I like to joke around and say, advisors are buyers. We think more is more. And that's not often the case. I want to just acknowledge that we are ushering a new era of AI into financial advice. And that's the hot topic, right? When we were down in San Diego for the National Conference, a lot of advisors were packed wall to wall for Charesse Spiller's AI portion or breakout. She'll be on the podcast soon, so you'll be able to hear from her directly. But everyone's interested in AI. So after sitting in her room for about 20 minutes, I put it on my notes. I write a lot of notes. I'm old school. And I was like, I got to check out AI. Just to see what it can do. And to date, I've been able to do two things really well with AI. The first thing is meeting notes. If it's virtual, it'll transcribe the entire meeting for me so I can look back and say, like, oh, I didn't catch that. Costs me nothing. And I can get a whole transcription of the meeting that I just had. And then some research. So, if I'm like, Hey, I was going to say Siri, but AI doesn't have a name, I guess. Hey, what are the seven biggest things that California entrepreneurs should be worried about? And then it'll just spit out whatever I need to know about that thing. And I can almost create my own content plan based on what AI has spit out. I don't do it often, but it's something that I know is a capability of that sort of software. My question is, is there a world where AI can replace or make advisors more efficient in sort of the way that I just mentioned? Because it's still relatively new for financial advice. I'm not built like that from just, like, I like to go find the answers by myself. I read a lot of books. I watch a YouTube video from time to time. But is there a place where this new technology can do some of the support stuff for us?

JASON: So, certainly. But I think it's easy to, like, the absolute best use cases are still very impractical for most financial planners and advisors. So I think one of the things that's important for people to understand is, how does AI work at its most simple form? Most AI, if you're using ChatGPT, for example, that is programmed via neural network, essentially what it's doing is it's doing pattern recognition. That's why you hear people talk about things like large language models. This is the data you train an AI on. So it's using, again, a neural network to identify patterns within a large data set. Which is very different than a way like a web crawler would work. Like a Google. Or a Siri, because that's essentially using like a web crawler type of a mechanism. And so the limitation for most advisors would be, we don't have enough data to train a model to be particularly relevant to the very unique things about your clients or your business. And so instead you have to go out to where there's large, large amounts of data. And this is where largely many of the models are trained on the internet. So data on the internet, you've got just these unthinkable amounts of data, it becomes a lot easier, again, the bigger the data source, the larger language model. Now, if you have proprietary data sets, you can also do some interesting trainings to be like, what if you studied the tax code or the CFP curriculum or CFA curriculum or like a master's in financial services curriculum? And essentially you could train in that curriculum. But again, there's a little bit of limitation because of the fact that it's really looking for pattern recognition. And pattern recognition can be tricky because this is where you get when people talk about hallucinations. If there's too much data and some of it’s inaccurate inside the data set, that can be conflicting, it'll actually kind of make up what it believes to be how the answer would actually, you know, what the answer should be. Not actually the data that it was trained on, which is a little bit tricky. And there's all these kind of toggles as far as how you want it to train. There's sort of, like, tuning if you will. And that's actually done by humans. So, there's lots of interesting things about learning how it works. So to unpacking that in terms of what does that mean for an advisor, I do think that chat based or language based models can be great because you can train them on your own data. So you have a blog, you have a YouTube channel, you could theoretically train it on your data and it can actually write in your style. So I've done this. It's kind of fun. I'll be like, Okay, here's all my medium articles, decade of blog articles, use this to write like you're Jason Wenk. And then here's what I want to write about. And then it kind of gives you an outline. It helps kind of unblock writer's block, things like that. So this use case, again, it's not great yet for us. But I think as CRM gets better and AI gets integrated better into CRM for us, those meeting notes that you have with clients will become essentially your proprietary data set. You have to be careful how you use that. There's like a lot of risks with making that. Like, I wouldn't take those notes and plug them into like a OpenAI's public facing. Like if you had a proprietary or enterprise license, you can. You can own your data, but otherwise, like you're literally giving your data to them to be trained on. That's not cool, you don't want to have your client data floating around on the OpenAI servers or their cloud servers. So, I think there's some for sure use cases. But again, I think once it's at a certain point, what'll be cool is, like, some event could happen in the world. It could be like, oh gosh, there's, I don't know, Microsoft buys Google. Hypothetically. And yeah, obviously that'll never happen. I'm just being super dumb here, but you could be like, hey, what clients should I send a note to? And what should I send them as far as what should they know about this? And boom. Hits your database. Here's all the clients who own that security. Here's anybody who's ever written notes about here's ever worked at those companies, crafts a note. Boom. You can send that out. Now, just in seconds, you can give what feels like a personal note message, high value to your clients, and it takes you no time. The other use case for AI, I think, for a lot of advisors is going to be more around automation versus information. And that'll be things like codifying better outcomes for clients. So something as simple as hey, which clients that I have might benefit from a backdoor Roth IRA or Roth conversion? Or which clients do I have that could benefit from some tax loss harvesting? Or which clients do I have that could benefit from making a contribution to a solo 401 (k)? These are taking interesting different sets of data, so data that might live in your CRM, data that might live in your KYC data, data that might live inside of your custodial platform or your performance accounting platform, and kind of putting those into one place to be able to go, okay, if I had access to all this information, how can I automatically very, very programmatically get better outcomes for my clients just by like tying all that loose, kind of disconnected data together? So I think there's, in the future, some really cool things. Today, the biggest use case is actually just how you're using meeting notes, helping get get going with an idea around whether it be an article or a video or some type of content creation. I'd be pretty afraid to use it for a lot more than that. I certainly wouldn't let it automatically manage portfolios just yet, you know, things like that. I think there's some cool personalization that you could do. And there's again, lots of financial planning knowledge and tax knowledge that I think will just shortcut our ability to know things instinctively for clients. And that's yet to come. It's not fully baked and ready for prime time just yet.

DASARTE: Huge upside I would say. 

JASON: Totally, yeah. Yeah.

DASARTE: With AI and what's to come. But right now for me and my business, I think speed and information is, like, if I want to know something really fast, I can type it in and I can get it pretty fast. So it helps in that regard. What I would say, now, all those AI enthusiasts might not agree, but I would say pay special attention to the other things. And I think you hit on it a little in the beginning of the show, your custodian, like, how can your custodian support you? Is the financial planning software supporting you in the way that you need? Why do you need four or five of these things? So I think we are quick to jump on these trends which could be around, and I think AI will be around for a very long time, but.

JASON: I think it'll change everything. I think, literally. Like, AI drove me to work today. Hour and forty-five minute drive. I barely touched the steering wheel the entire time from door to door.

DASARTE: That's awesome.

JASON: That entire programming of that self-driving feature is done by AI. So it's AI programming the AI to drive the car based on, again, all of the inputs from hundreds of thousands of vehicles driving all over the roads of the world. So, it's already, like, there are certain applications where it's really, really good already. But the pace of innovation, this is going to put Moore's Law to shame. As for how fast, like, because AI will just be able to go much faster than humans could ever go. Which is why when we're building chips, we can only expect them to double an output on a certain basis. The ability to create, write code, and develop software is going to be pretty remarkable. And so, yeah, I don't think it's a question of will it be a big deal. It'll be a huge deal. It'll change a lot. But it's just not ready yet for advisors. And a lot of it's because of the sort of the PII nature of our industry. Like, you got to really protect your client's information. And here's a really cool example. And this will be challenging for independent advisors, who knows if this will happen with big firms, but I was talking to an executive at a very meaningful fintech company, and we're talking about the use of AI. And he says, Look, here's one of the use cases I think would be quite interesting. We hire a whole bunch of really great CFPs, the best ones. We pay them a ton of money. And we get them to leave wherever they're at. We bring them in. Tons of knowledge. And we start letting them work directly with clients. And they're taking calls from clients, they're taking emails and we're actually using all of the knowledge. We're feeding it with tens of thousands of data points daily. And over time it'd be this small army, maybe it's 20, 30 CFPs, but they're serving thousands and thousands of clients. And we're able to monitor every action, everything that happens, how they're making changes. And we're literally training that. We're training the model on that data. Basically, what would the best, like, the collection of the best financial planners in the world managing clients, what is it that they're doing? It's literally training the model. So again, these models they use pattern recognition. They're kind of able to see, oh, this is how they speak to clients. Oh, this client clearly is upset. Here's how they kind of calm them down. Oh, here's how they build a plan. Here's how they optimize for taxes. Here's how they build portfolios. Now, he's like, Then what we start doing is we start letting the AI augment these humans. The humans never go away, but we just start bringing in more and more customers, and we just start letting the AI sometimes respond to the emails. And we let the AI sometimes go ahead and make the recommendations. And meanwhile, the humans are still working. So it is a evergreen kind of learning model. It's always constantly kind of rolling out kind of new knowledge. And in this way, the AI gets smarter and smarter and smarter. And he's like, In time, one CFP could theoretically support 10,000 clients. And then he's like, and the clients, the end client, would never know the difference. It'd be an incomparable difference. Even the style of writing. The relationships that they're building. You think about like, why is Grok super weird and quirky? Well it trained on Elon Musk's personality, I guess. And, Twitter's data set, which is weird. But, we see that these biases get formed in these models. Like, if you train a model on images and if all the people in those images are white people, for example, they're going to think all people are white people. Well, not all people are white people. That's a silly, silly thing. But that's how AI works. It doesn't know anything other than the data it's trained with. So yeah, we have a really interesting I think future in this space. Because if you're an independent RIA, do you trust that type of data access like what I just explained? A company that hires somebody, they can play God here and be like, we're going to just do everything. We're Big Brothering you and how you run your business, but are you going to let your fintech vendor Big Brother how you serve your clients?


JASON: I probably wouldn't. So the ability to kind of get the same out of AI, if you're a reasonably small business practicing as a financial advisor, will be very, very different than if you're a big business. So I do think, look, the fortunate news here is these big companies, they move at like the pace of, you know, whatever. Like, an aging snail or something. Going across shards of glass. So I don't think we have to worry about them, but they certainly have an advantage because they have employees that they can just play Big Brother on. And we can't do that. So I think there's a ton of cool stuff you can do. I mean, I'm sure there'll be tons of new innovation, but a lot of it will be like, you want to build a new website? You won't have to hire anybody. AI will build that for you. So you can have a killer brand as an advisor, probably with killer features on your website. Super-fast and easy. I'm sure there'll be a day where you'll be able to say, Hey, listen, I know Altruist has all these APIs, and I want to build a proprietary Yarnway Wealth front end on that back end that Altruist has. AI will build that for you. You won't need any engineers. It'll be like boom, fast, done. So there will be things that people will be like, wow, there's stuff we can do that will make my business better, make me more efficient, make my clients feel more loved, get better outcomes for them. But there will be some limitations because so much of what you'll get out of AI is based on the data that you allow it to learn from. And I, personally, would be really reluctant to let it learn on certain data that was specific to my clients.

DASARTE: Absolutely. That's a great breakdown of what we should expect from AI. My question for you, in our 2024 recap we talked about human advice being back. Does AI get in the way of that?

JASON: Now, again, it just makes them better. So I will say, look, my best guess is that if we're looking at a firm ten years from now, if a firm today requires ten people, that firm ten years from now for the exact same business will require four people. I think advisors that today are dropping a lot of money on professional services. So it's going to be things like, maybe it's design work, a little bit of web development work, could be content creation work. It could be tax, you know, like services for you, like tax planning for your business. Or tax preparation, legal entity formation, compliance overview and stuff, like, I think a lot of that stuff is what's going to be way more efficient for an advisor, probably way less expensive. And really, really good and proactive. So firms should have expanding margins. They should have more time. They should be able to serve more people. I think that'll be a real reality over the next decade. But I wouldn't be worried about the advisor themself being replaced. Because again, the only way that really happens is if all the best planners in the world agree to essentially become lab rats and let the AI train on all the things that we all do every day. I pretty firmly believe the absolute best of the best, they are independent. They don't work as lab rats. And so I think that you might be able to learn from and copy the average people who at best can be an employee, a cog in a wheel somewhere, but the actual superstar entrepreneurial advisors are going to say, Yeah, nah, we're good.

DASARTE: Keep that away from me.

JASON: Don't study me. And I think that's going to be, actually, a really strong differentiator to a consumer. I only need Dasarte at Yarnway Wealth. But I can get some, like, whatever Merlin super AI or something from Big CO in New York City. And I don't think that's what the world wants, actually.

DASARTE: Absolutely. Well, that's a good breakdown. I hope you guys go back and read our blog on AI  because we break down sort of the benefits, the pros and cons of AI. Which pieces of technology you should be using or experimenting with. I think today you can probably get a lot of information, maybe take some notes with AI, but we expect this thing to sort of make a footprint in the future. We'll just have to wait and see. We appreciate you coming on and spending some time with us to talk about AI and how to grow your firm with support staff or technology. You know where to find us on your favorite podcast platform. Do us a favor, go ahead, give us a review. We would like that. Share. Like. Subscribe, again. And until next time, we'll see you.

Thank you for listening to The Advisor Journey by Altruist. Don't forget to like, review and subscribe for future episodes. Each advisor's journey is different and your results may vary. While we hope you find this information helpful, success cannot be guaranteed. Also, Altruist and its affiliates do not provide tax or legal advice.