First Trust ROI Podcast

Ep 60 | Kevin Bishopp | Is AI a Friend or Foe to Financial Advisors? | ROI Podcast

• First Trust Portfolios • Season 1 • Episode 60

Share episode

Will AI replace—or empower—financial advisors?  Performance coach Kevin Bishopp shares how financial professionals are already leveraging AI tools, potential risks ahead, and new opportunities to thrive in an AI era.

----------------------------------------------------------------------------------------------
Subscribe Here to the ROI Podcast & other First Trust Market News
Website: First Trust Portfolios
Connect with us on LinkedIn: First Trust LinkedIn
Follow us on X: First Trust on X
Subscribe to the First Trust YouTube Channel
Subscribe to the ROI Podcast YouTube Channel

Ryan:

Well, it's been about three years since artificial intelligence has come on the scene. Since then, it's really been guiding the narrative in the economy, in the financial markets. Many white-collar employees are worried about disruption, how that will impact their job two, three years down the road or 10 years down the road. That's no exception when it comes to the financial services industry. And to help think through how this might impact financial advisors in the years ahead and how it's already impacting our industry. Today I'm joined by Kevin Bishop. Kevin is a performance coach and national speaker at First Trust with about three decades worth of experience in the industry. Most of that, again, has been focused on helping financial professionals be more productive, be more efficient. I'm really looking forward to this conversation with Kevin. Thanks for joining us on this episode of the First Trust ROI podcast. You've been around for a while. I think I was looking at your bio and it said that you 30 years, but there's no way you're old enough to have been in the industry for 30 years. I mean, you're a spring chicken, Kevin.

Kevin:

Yeah, well, so I I got my first job in nine in 96. So next next year it'll be 30 years. That's crazy.

Ryan:

Um okay, so over the past 30 years, uh, what would you, as you kind of retrospectively look back, what do you think the biggest change has been compared to 30 years ago, looking at where we are today?

Kevin:

So in the financial services space, the number one answer from my perspective is complexity. It is massively more complicated. There are far more products, there are more complex and volatile markets. We've got higher regulatory standards for financial professionals and teams all across the country. That's that's not going away. Um you've got clients who now have access to more information, uh more data, which uh prompts their inquiries to their financial advisors saying, hey, what are we thinking about on this topic, on that topic? Uh so those clients want more service advice and planning. Uh and and the technology in our industry just continues to adapt. I I remember a time where um we got this really cool thing called email, uh, and and it was awesome because you could actually just send an electronic message to a colleague. And it was it was internal and it was clunky, but but it it ratcheted up the level of efficiency in the in the role that I was in. And you look at where we're at today, uh it's it's entirely different. I mean, when I when I started in the industry, we were just moving away from dial up internet, right? I remember prodigy and dial up internet, and today everything is 5G on your phone in your pocket, iPads, tablets, docu-sign, you name it. So um it's it's more complicated and it's moving at a faster pace. When I'm in front of a large audience, oftentimes I'll say, Okay, how who in the audience has been in the business 25 or 30 years? A number of hands go up, and I say, Okay, can you tell me which year it got easier? And and every time they chuckle, they laugh because they know every single year it's it's moving at a faster pace with a higher level of complexity. And when you when you couple that with the advisors who have had success, they've grown their businesses, they have more clients, that just puts even more demands on their time. And so they are under even more capacity pressure today than ever before.

Ryan:

It's it is crazy to think back just how much has changed in. I mean you mentioned email, and I was just thinking like my first, I don't think I had an email address that I used until maybe 1999. I mean, I maybe I had one, but you know, if you have an email address and nobody to email, you know, you just don't do anything with it.

Kevin:

Um I re I remember my first my first legitimate email address was when I was a freshman at the University of Washington.

Ryan:

Yeah.

Kevin:

And I got a a Washington.edu email address, and and I I didn't know what to do with it at first.

Ryan:

Yeah.

Kevin:

Um so you know, we're that's 34 years ago. We've come a long way in a relatively short amount of time.

Ryan:

Yeah. It's uh it's and and most of those changes in retrospect, I mean, it's there's there's no denying that email makes it easier to stay in touch with people and communicate with people, and that all the information at your fingertips on your on your cell phone gives you more information, more access to information. It means you have to interpret a lot more information and you know you have a lot more questions and a lot more um different viewpoints on the answers to those questions. So I think the complexity, not just in our industry, but in society in general, um, has maybe increased over that time period.

Kevin:

Oh, absolutely. And you have companies now that are they are competing for your attention. Because their their model is is advertising clicks. And if they can they can draw you in, whether it's with a link in an email, whether it's a pop-up ad in your browser, something inside of an app, right? Every time you get lured away and you click and you go down that track, that's that's revenue for a lot of these companies. So they're competing for your time and attention. So you know, we as consumers, regardless of or as business owners, whatever industry you're in, right, it it's an onslaught, right? And so one of the things that um that I share with teams is you know, you have to be highly intentional. If you're gonna manage your capacity as a business, and in this case a financial professional, um, you have to be willing to say no to a number of activities, right? We we we can't do everything, we can't have everybody as clients. Um we we uh we certainly need to limit the the amount of intake of information because you've got wholesalers and different asset management firms knocking on your door, calling, sending emails. Um so the best teams that we work with have become increasingly protective of their time because that's their most precious resource. The time that they have to spend with their clients as a team to build their business. Um that is for for virtually all of them their biggest financial asset as well. And so they I don't want to say they go into protectionist mode, but they're very, very diligent about making sure that they're spending the right, the right amount of time on the right activities with the right clients. And that's that's a hallmark of success for the best uh teams that we work with across the country.

Ryan:

So I think all of these technologies that we've been talking about are are inherently disruptive. If you look back, you know how they were disruptive, and you kind of know who the winners and losers and the benefits, the puts, the takes. Um one that we don't know the answer to yet, and this is uh largely why I wanted to have you on the podcast, is artificial intelligence. And you know, you and I had the opportunity to speak at the same uh event um a few weeks ago, maybe a month ago. Um, and I I got to listen to your take on how AI is going to impact the financial services business. And you hear a lot about white-collar professionals being disrupted, and you know, you you don't really know what to do with that, I think, as a financial professional and as a professional in another industry, you know, because we don't know how you're going to be impacted. We don't really know the full potential of these technologies, we don't know what AI is going to be very good at a few years from now, that maybe it's not as good at today. Um so I wanted you to share a little bit on your perspective of you know how is this going to be disruptive? And at this point, do you think who should be afraid and and who shouldn't be afraid that AI is going to displace them or take their jobs?

Kevin:

Yeah. So that that is the number one question that I get from financial professionals and teams is hey, are are our jobs at risk as financial advisors as a result of AI? And there's a two-part answer to that question. The actually it's a three-part answer. The first part is no, your job today is not at risk unless your business is commoditized. Meaning, if all you're doing is building portfolios, some basic planning, addressing clients' immediate needs, you know, get them into a 529 plan, talk to them about some insurance. Um, if if you're operating at the commodity level, which is immediate needs for clients, you run a higher risk of being displaced by AI because that's the first place that AI is going to go. Because it's the least complex of the work that you do as a financial professional. So if you if you want to if you want to decommoditize yourself, you move away from immediate problem solving of basic needs for clients, and then you start to talk about goals. When do you want to retire? How do you want to fund kids' college education? What do you want to have happen if uh if one of you predeceases the other, what happens in the in the form of disability? These become more complex questions. These uh start to require some more calculations, some more math, but also requires you to truly understand what clients care about, what they're passionate about, how they're feeling about on certain topics. And so that's the next step away from commoditization is to start talking about a client's goals. That's going to be the next place that AI tries to go. It's going to try to work up this chain of what we call modern value, but it's going to take time. So layer one of modern value is commoditized, basic needs. That's where AI will chip away first. Second tier would be critical goals for clients. Uh, third tier, and this is where you start to get further away from what AI will be able to do, or said another way, it will take it much longer to get to this space, is you engage clients in a conversation around, hey, what does it really mean to feel financially secure? What gives you peace of mind? Now you start talking about how assets are custodied, transition of wealth to next generation, you start talking about taking care of aging parents, um, long-term care insurance, all these sorts of things so that you get to a place with clients where they know my my team helps me with wherever life and wealth intersect, or excuse me, yeah, wherever life and wealth intersect. My advisor is there for me. And they've put solutions in place, plans in place, a client experience model where if we do these things, we we're confident that we're gonna be okay. We're gonna have what we need for retirement, we're gonna be able to protect those savings, we're gonna be able to pay for kids' college to the degree that we want to, weddings, etc. That's that's tier number three, would be financial security, financial freedom. And then tier number four is all about helping them build a legacy. When you have a conversation with a client around, hey, what type of legacy do you want to leave behind? You are you are at a place where you're in a position to add unique value. It's as far away from commoditization as you can be in our industry, and it's also the place where you can command premium pricing, or said another way, you are the most fee-worthy in terms of what you're delivering to a client. So part one of the answer to your question is AI is not going to replace the advisor unless they're stuck in that commoditized zone of only dealing with immediate needs. Yeah. Second, the second piece of that is the caveat that says, now you you might be operating above that commoditized zone and talking to clients about legacy, but you might actually run the risk of being displaced not by directly by AI, but by another advisor or team or firm that's using AI to enhance their capabilities, to go deeper with planning, better understanding of clients, build better portfolios, better client experience, more content, more education they're making available. So you you get to a place where now it's it's not a direct threat from AI, but it's a competitive risk from other teams that are that are using AI to their advantage.

Ryan:

Yeah, that's uh that's a very good point. And actually, that makes me uh kind of wonder about where we are today with respect to AI and its impact and the tools that are being used already by financial professionals in achieving some of the uh objectives that you just kind of laid out for us. Um, you know, the things that that help them add unique value. So you talked to a lot of financial advisors, you're kind of much more keyed in on this than I am. Uh, where are you seeing AI already have an impact on some of those financial advisors, especially in areas that maybe those that haven't embraced AI should be aware of because it is a competitive threat?

Kevin:

Yeah. Hands down, the number one capability that advisors are benefiting from and that larger firms are are putting in place is the ability to have AI sit sidecar in conversations and to be able to transcribe and summarize the conversation and deliver it back to the financial advisor or team. These would be tools like Jump or Zox or maybe your Zoom note taker or your Team's AI note taker. That capability advisors are telling us that that capability is giving them hours back per week. And the more innovative uh tools in that space, they don't just transcribe and deliver a meeting summary. They allow you to customize the order in which you want that summary to come back to you. So you can you can talk with a client about any number of topics in whatever order it can flow naturally, and then when you get back your summary that AI has delivered, right, you can you can create a template so that it always comes back to you in the same order. You know, we caught up on goals, on life, then we talked about taxable accounts and qualified accounts, we talked about insurance, and and it will take the kind of the jumbled conversation that you've had with the client, deliver the summary back in that order. It will call out any to-do items that were agreed upon, and the more innovative tools will then build tasks for the team's CRM, could be Salesforce, could be Wealth Box, Red Tail, right? It'll it'll can pre-construct the tasks for the team. It will even draft a potential follow-up email to go out to the client. Now, if you think about that as being the new paradigm that we're operating in, what have we taken away from the advisor? We've taken away note-taking. We've taken away having somebody else in the meeting to take notes. We've taken away the 15 to 30 to 60 minutes post-meeting to read those notes, organize those notes, dictate them, copy, talk, drag in into your PC, review them, you know, distribute them, then build tasks, and then you still have to get on the keyboard and start typing an email. Hey, Bill and Sue, great to see you today, et cetera, et cetera. All of that is gone. Now we're at a point where it's the summary is delivered, the tasks are pre-built, the email is pre-drafted. I just need to go in and review that, make a few modifications, and and send those things along. That that is the number one capability that we're seeing advisors get the most productivity lift from is that AI sitting sidecar, transcribing meetings, and then getting involved in the follow-up activities. Second big thing that we are seeing at firms, and this is for larger firms, wirehouses, bigger independents, is they're taking all of their back office operational processes, all of the intel in all their procedures manuals, and they're loading that into an AI model. And they're they're creating their own chatbots behind the scenes, they're creating their own GPT so that if uh a financial professional or their support staff have a question, they don't have to go searching for answers. They could just say, What forms do I need to open up a 529 plan in the state of Virginia? Boom. Right? And and it just automatically will start returning the information that's needed on the forms, the process, etc. So they're they've taken all of this library of information, process, procedures, all of that, and and turned it into something that's on demand just via uh uh chat box. Okay. Um where they're going with that is is some firms are already starting to dabble with all of their investment Intel, all of their uh information on financial markets, products, behind the scenes, putting that at everybody's fingertips as well in in the same fashion. Um third biggest thing that we see advisors benefiting from is the use of Chat GPT, co-pilot, um, your your your more traditional generative AI. They're using that for everything from helping with drafting of simple emails all the way through to uh scripting for podcasts, scripting for video, writing articles, writing white papers, um the the generative AI, the the co-pilots, the GPTs uh if you give them great prompts, you will be blown away at the draft of output that you can get back from them. And um it's all of that just adds up to more productivity for financial professionals and teams.

Ryan:

I was listening to your um the the first uh section of of what you just laid out for us about note-taking, kind of verbally recording and taking notes and having follow-up, and I remember just a couple years ago, uh maybe it was a year and a half ago, I was in, I was traveling with um one of our salespeople in South America, and we were talking to a I believe it was a pension fund, and they were Spanish speaking. And the person that we were speaking with was English speaking, and you know, I I have a little bit of high school Spanish, but it's not uh anything that is uh quality, high quality enough to be able to communicate with somebody in in financial terms. But we had this meeting, and before that they asked if they could record it, and we said, sure, go ahead. And they had an output that not only did all the things that you were saying, but it also translated it from English into Spanish and provided those notes so they could then distribute it to their team. And I thought, man, this is just this is a game changer. Um, the the ability to actually communicate even across different languages. It's it's really good.

Kevin:

Yeah, so I I I have a similar story, right? I I was asked to speak at a conference in Texas uh by one of our larger partners. And they were the first, they were the first firm to ever make this ask. They said, could you record a 90-second promo video for your session so that when our teams are looking at the conference agenda, they can click on the different uh previews for all these different sessions, and they can not only learn what it's about, but they can see your speaking style, a little bit more about you, etc. And I thought, well, that's a great idea. So I I jumped on a platform just like what we're using today. I recorded a video, I sent it to Steve Nelson, one of one of the guys who's critical at First Trust in video production and all things marketing. I said, Hey, can we put a bumper on this on the front end, on the back end, polish it up a little bit? He said, Great, I can do it. And then maybe 10 minutes later, 15 minutes later, I get a link, I get an email back from him, and it says, Hey, I just it says, I just doubled your audience, dot dot dot. And I thought, well, what could he have done to my little promo video to double the number of people that are come to my session, come to my session? And so I I opened the video that he sent back, and it was my promo in Spanish. My face, my mouth moving, appearing like I was speaking Spanish. I knew that that AI could do some cool stuff from a video perspective. Uh I had no idea that it that it was that simple or that though that those tools existed. Now there's there's a whole nother more nefarious side of that with the deepfakes and and all that kind of stuff. But um I mean the capabilities are are astounding. And the application of of a lot of this uh AI in terms of modeling, crunching numbers, data has tremendous application for process development, for business uh efficiencies, for better logistics, inventory management. Um it'll it'll continue to revolutionize the biotech industry because uh a lot of the testing that we do will be replaced with AI simulations. And so it's it's gonna continue to transform uh virtually all areas of our lives. And and for some people that that can be exciting, for some people that makes them more nervous. Um but but we're all gonna have the opportunity to experience what that looks like in the coming years.

Ryan:

Yeah, and I think that also begs the question on reliability, because I I had a similar experience uh one of our podcasts, we actually had me speaking in Japanese, which was um which was really interesting, but we ended up not releasing the podcast in Japanese because there was some errors in the translation and it just wasn't high quality enough. And the same is even true, I think, with some of the output that financial advisors might have from those meetings. Um and and is that the case in your experience? I mean, how important is it to kind of check the work that these chatbots and um you know the different AI applications are what check their output?

Kevin:

Yeah, so it's it's paramount that if you're gonna use AI for any generative activity, you're gonna generate uh written content, you're gonna generate a video, you're gonna generate a script. Uh, you have to go back and review that for accuracy. Right? And the reason that you need to do that is because in the event that a financial professional or team is audited, whether it's FINRA, whether it's the SEC, let's say they come back in and they say, hey, this particular marketing piece that you prepared and sent out has some inaccuracies, you can't format data this way, that way, etc., it will not be a sufficient defense to say, well, that's what ChatGPT gave me. Right? That's that's not gonna hold any water. So it's it's on you to verify it for accuracy. But even beyond that, um, it's very, very important that whatever you send to a client, right, if you pull it out of AI and directly try to pass it off as yours, you will be perceived as inauthentic. And that will happen very, very quickly because your clients know you. They know your voice, they know how you talk, you've sent them a variety of emails, you may have language on your website or content that you've written. And so they've established in their mind their perception of, hey, when I interact with Ryan, my advisor, I I know it's him because of the way that he talks and what I get from him and the tone of his emails, etc. If you're just taking stuff straight out of AI and purposing it as your as your own, even if you source it, it you run the risk of being perceived as inauthentic. And if clients start to sense that, hey, I'm I'm getting things from my advisor that seem like they're just boilerplate stuff that I could get out of AI, they're going to begin to question and wonder now, why are we paying the fees that we're paying if if I can get this type of information with a good prompt into ChatGPT or Copilot, et cetera. So you have to take enough time, put enough energy and creativity into refining what you get out of AI to make sure that your voice is heard within that particular output.

Ryan:

Yeah, and that's I've noticed that I don't know if if uh those that have iPhones have used this tool at all, but AI on your iPhone will now, responding to a text, make a suggestion. And I have not once, never ever used that suggestion because it doesn't sound authentic at all. It's some I don't know who it sounds like, uh, but it certainly doesn't sound like me. Um and I'm uh it just seems like one of, I mean, no offense to Apple, but one of the most useless AI applications I've seen so far is the uh the response that I would give in a text. I mean, I've just never used it.

Kevin:

So what is likely to happen, right, or the natural evolution of AI in that space will be in the future, there'll be enough bandwidth, there'll be enough horsepower so that AI will have been paying attention to previous text responses that you have written, and it will go in and refine and optimize its recommendations. And the only reason that I say that is because that's now happening with ChatGPT Copilot and a lot of the generative AI. For example, if I if I prompt ChatGPT to create something for me, it will it will inherently do a couple of things that it didn't used to do. The newer version of ChatGPT will act as its own prompt engineer. And it will say, hey, here's what I here's what I'm giving you based upon your prompt. But if you modified your instruction in this way, then I think you will get better output and what you're actually looking for. So it's it's running its own prompt engineering. It's basically saying, hey, you gave me some instructions, but they're not very good instructions because based upon how I've been trained and and and the way that other people are looking for the same information, I think I can get you what you really want if we modify the instruction that you've given me. Now just think about that for a minute. It's engineering your request and optimizing it. Not it's not only giving you back what you asked for technically, but it's saying, hey, we can actually make this better. And then it will even say things like, hey, and because you're a for me, because you're a consultant for financial advisors and teams, have you thought about presenting it this way in the form of a you know a McKenzie layout or a Boston consulting layout on this particular slide? Like it's it's taking what it knows about me and it's taking my my basic prompt, trying to enhance that, and even figuring out how it relates to the type of work that I'm doing. So that type of capability is just going to continue to be enhanced in a variety of forms.

Ryan:

Yeah, that that's that makes a ton of sense. I think the one of the biggest challenges to using some of these um ChatGPT or all the other variations and platforms is understanding how to prompt it in such a way that it gives you the output that you really want. And it seems like it's a learning process to figure that out. But anything they can do to accelerate that to understand, you know, that this is an iterative process where you get some output and you say, well, this was good, but I want it with a different tone of voice, or I want it optimized for a certain type of consumer or a certain type of um of one of the things that you pointed out in the speech that I heard you give was um optimize for search results, if it's a blog or something like that. I mean, I hadn't even thought about that before. So I think the ability of these platforms to actually help consumers understand how to prompt them is going to be something that could be uh a really maybe even a game changer in terms of helping people adopt them in a better way.

Kevin:

Yeah, we we attack that in our five-part series that we have on AI. It's called Unlocking the Power of AI. And one of the things that we clearly spell out is when you prompt, put three different components into your prompt. Tell ChatGPT, your co-pilot, the the role that you want it to play. Think like a business owner, think like a financial professional, think like an architect, think like an entrepreneur, think like a software business owner. Give it the role that you want it to play, then give it the goal. That's the output that you want. Write me an email, draft me a blog post, right? Give it the goal that you want, and the more color that you put with that the better. And then the third component is the soul. And the soul is the emotive side or the preference side. I want it, you know, a thousand words, I want it written to, you know, uh MBA level audience, um, or I want it more casual, etc. When you put those three components at a minimum into your prompt, you will get better output. So it's the role that you want ChatGPT to play, how you want it to think, the goal is the output that you want, and then the soul is the emotive side. If you ask Chat GPT for all the ingredients for a great prompt, it's gonna give you eight different components. That's too many for the vast majority of us. So that's why we default back to starting with those three role, goal, and soul. And the more detail you can put into your prompt, the more specific you can be, the better output you will get from these tools.

Ryan:

So your team puts out a lot of content, and I know the AI uh part of that content has been very well received. Uh, for those that are interested in receiving some of that content, is the best way to maybe understand or get a hold of that just to talk to their first trust uh wholesaler? Or how do they typically find that?

Kevin:

Yeah, so the the easy button for the financial professional is just to reach out to your first trust wholesaler, either the internal wholesaler or the external wholesaler. Say, hey, I sat in on the ROI podcast with Ryan and Kevin. They talked about some AI resources that First Trust has for financial advisors. And if they even want to get more specific, they could say, you know, there's a five-part webinar series, can I get access? And we can send them the flyer. We have the same information in a 55-page white paper, which is long. Uh it's great white paper, a lot of information. Uh it's got a glossary of AI tools in the back of what we've seen teams using. It's got 17 different ways that financial professionals are currently leveraging AI. What I've been encouraging people to do is to get that white paper and then throw it into Chat GPT and say, give me a bullet point summary of the white paper. And I do that, I do that for two reasons. One is I want to make it kind of more accessible, easier for them to use because 55-page PDF is a lot to read. But I also want them to start to dabble and see the capabilities that exist with the AI that's already at their fingertips.

Ryan:

It's really, it's really interesting because you could go either way with AI. You could have this list of uh an outline or a summary and say, write me a 55-page white paper, and it would it would do that to some degree. Or you can take the 55-page white paper and you say, boil this down, do an outline and some bullet points, and it can go that way as well. So it's it's uh it is an interesting um, you know, just a variety of ways that this technology can be used.

Kevin:

It's um so there's there's a couple other things I love to share with um with audiences. One is you know, if you think about the demographics of our industry, the financial services industry, average age of a financial professional somewhere in the neighborhood of 57, 58 years old. Um we're in an older industry at the senior level, and one of the realities that we battle is that technology adoption rates are inversely correlated to age. That's a fancy way of saying that older people have a harder time adopting new technologies. So my encouragement to everybody is hey, if if you find yourself um you know poking around and looking at AI to whatever degree you're doing that today, just do 20 more minutes of that per week. Just commit uh an incremental amount of time to paying attention, to doing some reading, to start playing around with the tools because it's it's not going away. Every firm on the street is trying to figure out how to use AI to get faster, more efficient. Uh, you're seeing significant amounts of layoffs at large firms, largely in part to the efficiencies that they're getting behind the walls with artificial intelligence. So commit some more time to it. And in terms of the the capabilities that exist, I'll I'll try to share just a quick personal story because it was enlightening to me in terms of what AI can do. Uh I've got three children. My youngest, he's a 20-year-old, he's in his junior year of college, finance and econ major. And when he was a freshman, so this is now a couple years ago, I was curious. You know, he he he moves away to college, he's on his own, he's out of the nest, he's going to class. Um I said, hey buddy, I'm I'm doing some research on AI for work. I'm just curious, as a as a freshman college student, like what role is AI playing in your learning? And I was I was trying to do it for two reasons. One, I wanted to find out if he was using it to write his papers and do his homework for him. Or and second, I wanted to figure out you know what capabilities exist. And his answer blew me away. He said, Dad, there is not a single assignment that I work on where I'm not using AI in some form. Meaning it's getting me information, it's gathering data, it's summarizing research that I need to read, it's reformatting data that I found on a source because I need it in a different format. Um, it's it's reviewing something that I've written and helping me tweak it. Um, it's checking for accuracy the accounting homework that I've done. Um or I took notes in an econ lecture and I didn't really understand what the professor was saying, so I asked AI to explain it to me a different way. I mean, every single thing that he's working on today, uh he's he's touching AI in some form. I mean, if you go into a college classroom, you'll see kids, they've all got their laptop open and there's some form of AI note-taker sitting sidecar because those things not only take notes, but they'll prepare flashcards, they'll do practice exams. I mean, it it has infiltrated education in an amazing way. And that's just going to continue to evolve. Um, but with that comes some risk, right? And the risk is for younger people over-reliance on AI. And this is actually for anybody, over-reliance on AI for activities and tasks that are problem-solving or creative tasks. The research that come that's coming out is saying uh you run the risk of material cognitive decline if you over-rely on AI in those areas, because your brain is a muscle. The way that your your brain gets stronger, you think through problems, you uh you push through, you grind, you solve it, you learn, etc. And if you're outsourcing that activity to uh Chat GPT prompt, um you're not gonna get smarter. And if you think about, especially as a young person, right, if you think about the competitive landscape that we're in, right, to differentiate yourself, you know, retain the ability to problem solve, to think strategically, absent the use of AI, right? Learn how to build relationships, learn how to work as a team because the the non-replaceable skills are the ones that are gonna keep you or get you employed in the areas that you want to be employed in the work that you want to do. Because if it's replaceable, if it's pattern recognition, programming data, etc., AI is just gonna chip away and and take away more and more of that. So I continue to be impressed with what I see. Um I I love that I get to research the space. I love that First Trust is doing this and and and getting this type of information out to financial professionals and teams all across the country. Um it's it's invaluable from our perspective, and so we're happy to be doing it.

Ryan:

I I think that's a really good caution because you even see that already with the ability of people to communicate with the advent of text messaging, for example, or you know, just the interpersonal skills, I think there's some muscle development that has to happen there. And if you, you know, I hate to be the old, the old man kind of you know yelling at the younger generation, but the interpersonal skills for for some that spend too much time looking down on their phone and texting people when there happen to be other people, you know, right across the table or something like that, you know, I I just think that that uh development, that muscle memory hasn't yet been established for some people. And so I think it's it's definitely a good idea to not let your problem-solving uh muscles atrophy because you're too overly reliant on some of these tools. I think that's a that's a really great point.

Kevin:

Yeah, I I had a uh financial professional tell me um that he had this backfire on him because uh for his wife's birthday, he decided he he he quote was going to write a poem for his wife. Well, he used AI to do it, and she sniffed it out. And she was she was not happy. She's like, you mean you couldn't even sit down for 10 minutes and think about something you know thoughtful and meaningful to write as a birthday message? And I to me that was a a very vivid cautionary tale to say, hey, you know, be be be diligent, you know, be careful about how you use these capabilities because you never want to be perceived as inauthentic in in any aspect of your life, right? Business uh between you and clients, between you and team members, between you and your your spouse, your kids, your your family, et cetera. Um and so the these tools kind of have have turned faces to screens more and more, and so fighting the urge to do that is important, especially especially for younger people.

Ryan:

Yeah. All right, Kevin, uh I I really appreciate you spending some time with us on the podcast. Love to do it again at some point in the future. But my final question, especially for those that have been a first-time guest on the podcast, is just more general. You can relate it to AI if you want to, or the financial services industry that you've worked in for three decades. But what are you reading these days? Any any book recommendations that I should consider or viewers or listeners of the podcast?

Kevin:

Yeah, so for those of you who who want an industry-focused book, we have a great book called The Advisor Playbook. It is on how to build a process-driven financial advisory practice. Easy read. Your first trust wholesaler can get you a digital copy of that book. We have teams who, when we go and see them, that thing is highlighted, you know, dog-eared, all over the place, sticky notes, etc. It's it has become a core manual for them in terms of how they're organizing their business. Two books that I really like. One is going to be very common to most people. I love the book Atomic Habits by James Clear. That's all about kind of reformulating your brain to think about improvement efforts, not as heroic, monumental, you know, paradigm change efforts, but more how do we get 1% better every day? If we just continue to improve on the margin every single day and we execute, then when you look back over longer periods of time, you're going to be shocked with how many things you've changed. And it's just, it's it's just the accumulation of all of those small incremental changes that adds up to significant progress. One of my favorite books, right, is a book called Legacy by James Kerr. It's the best kind of leadership team-building book that I've ever read. And it's told through the lens of the New Zealand rugby team. The New Zealand rugby team, they're called the All Blacks, and most everybody has seen them. They just don't necessarily know that it's them. It's the rugby team that goes out to midfield before the game. They all line up and they do that very aggressive chant. Right? They get those mean looks on their faces and they're chanting the haka at their opponents. The book is all about how they built the culture of that team, how they built it over the years and turned it into the most successful rugby, you know, national team franchise in the history of the sport. It's a program, a lifetime-long 87% win rate, which is astounding in rugby and international competition. And the book just does a great job of not just taking you through principles, but but sharing stories of how they implemented those principles and then giving you kind of a token version to say, you know, boil it down to what does it mean to play for the jersey? What does it mean when the captains of the team are the ones that are sweeping the locker room before they leave in a way match? Not the grunts that are doing that, the captains. Like they're setting the tone. That's a fantastic read. Again, it's called Legacy by James Kerr. So there's there's three recommendations for the audience.

Ryan:

All right, very good. Um, that was the two of those I've uh read personally, but the last one I have not. So thank you for all three recommendations. Kevin, it's been fun. Appreciate you uh taking the time for us to be on the podcast. And thanks to all of you as well for joining us on this episode of the First Trust RMY podcast. We will see you next time.

Head Shot

Ryan O. Issakainen, CFA | Senior Vice President | ETF Strategist

Host