Why the Future of Financial Advice Is Human-Led and AI-Enabled with Michael Liersch

Jack Sharry: Hello everyone. Welcome to WealthTech on Deck, our weekly podcast dedicated to examining the convergence currently reshaping financial advice. Each week we engage with executives from wealth and asset management, insurance, retirement and fintech sectors to discuss how advances in technology operations, investment solutions, and user experience are collectively enhancing outcomes for investors, advisors, and firms. Talking with industry pros, we work to dismantle silos, share practical insights, and explore how increased collaboration is driving greater connectivity, efficiency, and client centricity within financial services. So for the past five years, our podcast has analyzed the evolving landscape of financial advice, featuring 250 distinguished guests. Our episodes have been downloaded over 70,000 times as we showcase forward thinking leaders who anticipate industry trends and emphasize their impact at the intersection of digital and human advice. Today’s episode features a discussion with my friend Michael Liersch. Michael has been one of the most popular guests on WealthTech on Deck as he brings deep expertise in behavioral finance and wealth planning and so much more. Michael has been an executive at some of the top global financial services brands over the past many years. He joined Edelman Financial Engines in August of last year as chief planning officer. At Edelman, Michael leads the firm’s strategic agenda around the convergence of financial planning, advice, technology, operations, investment solutions, and user experience. So for today’s podcast discussion, we’re going to focus on Michael’s perspective around AI and automation, which is a huge part of his role in bringing it all together at Edelman. Michael, my friend, welcome back to WealthTech on Deck. Glad to have you here.

Michael Liersch: It’s great to be here, Jack. And I do want to say that introduction makes me feel just as dorky as I really am. I really appreciate it. And we’ll try to get you over a hundred thousand downloads.

Jack Sharry: Here we go, we’re gonna prove it. So Michael, if you would share with our audience your role at Edelman Financial Engines? What do you do? What do you hope to accomplish? What’s your focus? Fill us in.

Michael Liersch: Absolutely. So technically, I lead our investment management technology and product organizations. And so I like to think of that, Jack, as the production arm of Edelman Financial Engines. And when you think of the production arm of Edelman Financial Engines, that’s why all the things you said are true. You want to make sure what you’re producing could actually be delivered in the intended way from a risk, efficiency, growth, and ultimately to the end constituents desired outcome. And you and I have talked a lot about that. You call them goals or you could call them, you know, moments or you want to meet those moments. You want to help the end constituent achieve those goals. And at Edelman whether that’s a plan sponsor or a plan participant, you know, whether that’s a human being outside of the defined contribution environment, we help well over a million people achieve the things that they’d like to and institutions help those people achieve the things that they’d like to with their money. So it’s a pretty exciting job. I at times feel very overwhelmed by the magnitude of the mission, but it’s exciting to be responsible and accountable for getting people to where they want to go with their money. So I couldn’t be more honored and proud to be working at Edelman Financial Engines.

Jack Sharry: That’s great. Welcome aboard. Not that I have any right to say that, but good to have you there, because I know we’ve talked many times over the years about all this kind of stuff. Pulling it all together is the challenge, and you are now responsible for doing that at Edelman, so good luck.

Michael Liersch: Thank you. I’ll take it.

Jack Sharry: Here we go. So one of the critical pieces of all that, I think everyone agrees, I’m sure not everyone fully understands it based on what my many conversations on the topic, but you may have heard that AI is everywhere. So my assessment is the industry is still in the baby steps phase, which is primarily in the talking and figuring it out stage around AI. So you and I have talked about AI for a while now. I know you have many thoughts on this as it is crucial for what you’re looking to accomplish, I think for all firms trying to pull it all together. So if you’d fill us in on your thinking around AI and what you’re developing.

Michael Liersch: Sure, Jack, and I’m happy to do that. I’ll give a little bit of a preface here. So I’m a cognitive psychologist, as some of your listeners know, and some of your listeners may not know that. And all that really means at the end of the day is that I have a PhD in how the mind works and I have a specialty in terms of how the mind works when it comes to money. And so I don’t really actually know, and no one really knows what’s going on in the mind, but I’ve mathematically modeled that in certain situations, experiments, giant data sets, and at all the companies that you mentioned. And so when you think of kind of inputs and outputs and the mathematics around it, the inputs being financial information, emotional moments when it comes to money and the output being the behavior and the decisions that you make, AI becomes a really interesting capability in three ways. And I’d love you to react to this, Jack. The first way is, a lot of people fear AI. They think it’s something very nouveau. They’re not sure what it’s going to do to them. It’s like, know, HAL in 2001 or the Terminator, you know, it’s going to somehow take over jobs, the world, humans. So that’s kind of thing one. And I find that particularly fascinating because AI has been around for a long time. And we must know that because some of the things I alluded to, you know, movies were made in the 1960s around the topic. So obviously AI has been around for a long time, Jack, right? So… we’re still so scared of it. The second thing I find interesting is that we’re, I think we are in a truly new and unique era of recognizing that machines, you can call that AI, right? That the machine and humans can complement each other truly. So it’s moving away from that fear in thing one to thing two, which is what is that complement? And I don’t think anyone quite knows, Jack. We’re all experimenting to your point. That’s the baby… And the third thing is really around how can we be the most transparent in this journey where we’re not pretending it’s human when it’s really a machine driving and we’re not pretending it’s a machine when the human’s really driving. And I hope that makes sense. So that last one is like manual processes, making it look like it’s a machine. And the other one is, you know, the human saying things and they’re prompted by the machine, right? And so there’s just effectively a skin over what the machine is really doing. And there’s a lot of research on that where that’s very offensive to people. People do not like being, “tricked.” So there’s just a lot going on in those three things. So we can dive into any of those, but I’d love your reaction to that as a preface.

Jack Sharry: Well, I’m one of those baby step people. I’m using AI every day. I do a lot of thinking with it. I find it’s a great way to help organize my thinking. And I’m very low level in terms of how it’s, I think it will be used. I do think it’s where it’s going to have its biggest application. First of all, I find it’s just a time enhancer and I think that’s kind of where everybody starts. It’s a…

Michael Liersch: Capacity.

Jack Sharry: And frankly, I think better, but I’m doing the thinking and I’m using that to help me organize my thinking. That’s how I use it. But the more I do it and try it out and think with it, we couldn’t get where I want to get with it without me, if you will. It’s like I’m the critical piece and that makes me think better, I guess maybe is a funny way to say it. So there’s that. And so then as I read more and I try to understand it more, because I really want to be able to leverage it and stay competitive in the marketplace. I’m sure, I’d love to hear your thoughts back on all this. But as I’m going through the exercise, I’m realizing really where it’s going to be best applied is that places like from where you sit and how it’s going to be infused in the experience of working with a financial advisor at Edelman Financial Engines. In other words, how will you enable the advisor? How will you enable the client? How will you render information? And really at that level, that’s where I think it has its greatest power at all levels, not only the client experience, but also the investment experience and capabilities, all that kind of stuff. Everybody gets better up and down the value chain. So those are my thoughts. I’d love to hear your thoughts.

Michael Liersch: So that’s really an excellent segue then into what we’re actually doing at Edelman Financial Engines on this topic, because to your point on the capacity component, I’ll describe a few things there. And I think it’ll blend nicely into the preface in the sense that I’ve never worked at a place in my career, and I can say that very definitively, where there’s such an openness to new ways of serving clients as I have. That’s pretty exciting. That creates a great opportunity to do some of the things you just described. You’re playing around with artificial intelligence. And in this case, you’re playing around with, it sounds like, summaries of information that help drive forward your thinking. So we’re doing a version of that here at Edelman Financial Engines, which is essentially getting permission from clients to record calls that generate summaries for clients and planners, as we call them here, to collaborate around. And those summaries give, and Jack, no exaggeration, hours back to planners every week. And when I joined, that’s the first thing they told me. It was just such a value. And what they said is there are a couple of things that were valuable. It was just the transcription itself, right? The second thing was trying to remember everything. And when you’re trying to remember everything, document everything in the moment, you stop listening, right? So they couldn’t be as active of a listener, Jack, and you know how important that is in this business. And the third thing was how, to your point, it organized the information, revealed insights that they hadn’t recognized in the conversation, almost like the central nodes in what was being discussed, whether that was around retirement or a life event or the desire to purchase something, make a big purchase. Suddenly, it just all became clear from the hour long meeting in that summary. So there was a really big lift there. So when I joined, we also decided then to launch, based on that summary, we wanted to collect other information from Salesforce, from Orion, which is part of the investment platform we’re using, as you well know, from other data sources we have on information from our clients to create also a meeting preparation document. And now that’s even been, I would say, more well received than the summary because you can take between the summary and between the prep document, you can not only cut capacity, but you can increase the quality of the feedback interaction with the client, create an agenda, document a follow-up note, who’s on first, who’s doing what. So what we’re going to do this year is really package that all up and really create an extraordinary client contact experience, whether that’s a full review or whether that’s reactive, proactive, really create a whole package end to end for everyone to interact around. So it leans into your capacity piece. It leans into your baby steps piece. You can say, you see, we’re doing it incrementally and building in a sense and only focusing Jack on time to value in this case for the desired outcome, which is for clients and planners to interact around what matters most. And the planner to be able to ask questions and listen, the client to be able to be in the moment. And then for that follow-up to be transcribed and not prescribed, but described, if that makes sense, Jack, so that everyone can get the job done that they need to. So it’s a pretty, like huge unlock for us. I hope that resonates.

Jack Sharry: Totally. I wanna add an element, love your thoughts on this. As you know, I teach classes at Babson around listening, around persuasion. And a lot of what I talk about rooted in basically philosophy, frankly, not psychology.

Michael Liersch: You have a book on that, Jack.

Jack Sharry: I have a book on the topic, in fact, I do. But one of the things I found interesting as I’ve done more and more research on this, and there’s a whole school of knowledge and body of knowledge out there around listening. So a new term I’ve come up with recently from one of the people I follow closely. It’s called disclosive listening. Listening so hard that you disclose opportunities. What’s at the heart of it all, what the problem is, what the issue is. Because my experience having been around this industry for many decades is that most people come in and they don’t really know what the problem is. They just know they don’t feel good about it and they’re not sure what to do about it. So as you can listen well, as you can really understand what matters to them and their family, their concerns, health, you know, all the stuff that people, they come in not, they talk about money, because that’s what you’re supposed to talk about with a financial advisor, but it’s usually having to do with where to live and, you know, how to access healthcare in the best way, et cetera, et cetera. That actually, as people are heard and as they can sort it out, particularly using AI, as I think it will be used, it will help you formulate better solutions, better prescriptions around what you might do. And then as you test it out, and then that doesn’t feel quite right, we tried this, whatever the back and forth is, what ends up happening, because you’re freed up to really listen if you’re an advisor and really find out what’s up, that at the end of it, my experience is that if you really listen well to people and they feel heard, they feel comfortable, they trust. And isn’t that what we’re all about? Do you agree? As I would assume you do.

Michael Liersch: I totally agree. And I’ve done a lot of research at the different firms I’ve worked at on this idea of what inspires and instills trust. And I couldn’t agree with you more, Jack, on what that is. It really is this idea of listening, but in a way where to your point, you’re really trying to get to the root cause of not just the problem, but what your advice could be around potential solutions in a very empathetic way. So I couldn’t agree more with you. And back to AI, that’s what’s interesting about the machine is because it doesn’t really have any of its own feelings, at least not at this time, or that we know of. You know, Hal and the Terminator, right? We’re not sure, but we don’t think it does. It really does a great job of giving itself entirely to the human and doing almost what you described at like a level of precision that humans find challenging. So I love that idea.

Jack Sharry: So this is at the advisor client level, which is fundamental to the whole exercise, right? But then you also, because you’re responsible for it, you’ve got to figure out how to make all that bigger machine, that factory that you got going at Edelman Financial Engines, not technically a factory, but you get my drift. You got to make the planning, the decisioning around all that, the investment management, the coordination of accounts…

Michael Liersch: Kicking-off processes, account opening, all of it.

Jack Sharry: All of it, there’s a lot of it.

Michael Liersch: I’m responsible for all of that. It’s the truth.

Jack Sharry: Yeah, exactly. So I know you’re working on that and AI will play a vital role, I’m assuming. Talk about that a little bit because that’s, it plays out in the client advisor planner discussion, but it also has to be sort of in the guts of the operation.

Michael Liersch: Completely. And that’s why I wanted to start where I did, which is, to your point in baby steps, which is, we can employ things that feel very normal, natural, that we’re all doing on, you know, our phones right now in that kind of, in planner or advisor interaction. When it gets to the things you’re alluding to, where we’re focused mostly is on, I would say two primary areas. First, really, and this one’s a little challenging to describe, but we want to create almost drafts, Jack, of plans, drafts of account opening documents where, where artificial intelligence using agents and large language models are actually drafting those things and kicking off those processes on behalf of the client and planner. So that’s thing one. And that helps move beyond just prompting to your point, recording, summarizing and into actually implementation. So that’s one area where we’re really focused. The second area where we are really focused is on this idea of, and this one I think has had a little bit of a mixed reputation in the industry, you know, in terms of like a next best action framework, Jack, but almost what is the must do, should do, or could do framework in terms of internally an employee or a financial advisor or a planner or a client or a prospect, what are the things they should be considering? And that’s something we’re extremely focused on. And what’s great is that at Edelman Financial Engines were fiduciaries. So there’s a best interest lens to that, and that creates a really great first principles approach to that, you know, must do is always about truly the essentials. And so when you’re able to use agents to serve up data, information, prompts, next best action kind of ideas within that framework, it is extremely human centric. It’s extremely client centric. And it’s really about motivating regardless of the financial incentives or outcomes, the relationship forward in the most productive way, which I think leads also to your element of trust. You know, trusting the machine, trusting the financial professional and inspiring that client to provide more information about what’s really going on so you can help them. So those are the two areas that we’re really focused in terms of using agentic AI, large language models, just other mechanisms even into automation instead of fancy machinery and AI to really drive forward that process. So does that make sense, Jack? I just want to check in with you.

Jack Sharry: Totally. And then again, all this is at the client planner or advisor level. What about the factory? What are you doing about the factory?

Michael Liersch: So the factory, well tell me more about what you mean about the factory.

Jack Sharry: Well, client portfolios, of which you’ve got thousands if not millions, you got a lot of, they got a lot of portfolios, and you got to kind of keep them all straight. And then you want to optimize, maximize their outcomes so that when the conversations take place, they’re at an optimal level. What are you doing about all that?

Michael Liersch: So when we think about then, when I think of factory, I would almost recast it in terms of the institutional approach to personalizing money management, Jack, if that’s… And so the scaling of that, we are still in, let’s say, the nascent, early stages of evaluating what that looks like using artificial intelligence. Right now we use more traditional things, you know, Monte Carlo, guess, is a form of artificial intelligence, but we’re, you know, in terms of portfolio optimization, asset allocation, resource allocation, asset location, things like that. We’re really still using more rules-based mechanisms, Jack, rather than focusing on AI as our core set of principles and tools. The primary reason is that the training of the machine and ultimately the risk it introduces in terms of, and I don’t want to call it making mistakes or hallucinating, but really providing a, to your point on prescription, you know, a recommendation or an approach that may or may not be, you know, nuanced enough to serve the end plan participant or the end client is something that we’re taking a really close look at. And I recommend to everyone who’s using those types of capabilities do the same. Because I’m not saying that the other stuff that we talked about, those factors aren’t as important, but there’s more of a human in the loop element to them, if that makes sense, Jack. It’s more transparent as to what’s going on. You know you were there, you were the one talking, right? If it’s making a mistake, you’re like, I didn’t say that. Like that didn’t happen. When it comes to portfolio recommendations, you know, really trying to understand how the machine came to that, especially, you know, to your point, if you’re thinking of the factory or an institutional level, because that is how we build portfolios, you know, I lead the investment management arm of EFE as well, Edelman Financial Engines. So that’s an enormous responsibility, over $300 billion in assets. And we want to make sure that that is held with care.

Jack Sharry: So Michael, this has been great. Clearly the primary focus is on that client planner interaction and how to make that better, stronger, more sustaining on both ends. And you’re working on contemplating, developing what you might do for the factory, pardon the expression, but the bigger institutional effort. One of the things you and I have talked about that I’m curious, love to get your thoughts on is the concept of “over AI-ing”. So talk about that. What does that mean? Explain that to our audience who I’m still not sure I understand it so let me hear it from the horse’s mouth, what does that mean?

Michael Liersch: Well, in the spirit of bringing it all together, that’s a really great question, Jack, to your point to say in that client conversation, the right amount of AI is enabling humans to do what they do best, which is listen, share information, and collaborate around it with artificial intelligence being a supporting cast member in that job. So again, descriptive, more than prescriptive. Of course, there can be prompts and again, in that framework, must, should, could, do, but all of that is permission-based, Jack. So I would say that’s a core principle here and not over AI-ing things, the permission-based complement that AI would provide. The second one would be into what we just talked about, which is this idea of institutional portfolio management at scale, portfolio recommendations. I mean, you can go on to certain kind of my AI types of functions, take a picture of your portfolio and get recommendations today. I mean, and not at financial services providers, Jack, you can do that just generally speaking. And it will tell you what it thinks you should do. And I would say that would be another example of over AI-ing it. Those types of recommendations, especially to, and I don’t even want to call it the naive user because that’s not fair, but to a human that’s trusting to your point on trust Jack that assumes it’s been trained properly, that assumes that it’s been risk managed properly, that assumes it’s for them. Right. It’s like watching someone on the news or someone on a TV program tell you what you should do with your money. Right. You know, for some people, they might just implicitly trust that, you know, because why else would they believe otherwise? That’s another example where I think we should all be cautious of over-AI-ing it, because it doesn’t behoove anyone to make mistakes at scale on that topic that’s not advantageous to financial services in general. When I talk about over AI-ing, that’s what I mean, Jack. We always need to be very transparent about the risks and rewards and the complement of using the machine. And we also need to, again, have this human-centric, human-in-the-loop type of approach as we’re taking the baby steps toward making sure that the machine and the human are collaborating in the most productive way rather than an unproductive one. One more thing I want to mention, because you said this upfront in terms of AI giving you capacity back even like in the fun, like my AI kind of way or ChatGPT type of way. So you say it gives you capacity back. You could imagine another world where it wouldn’t because you could go down the rabbit hole, right? Like, you know, scrolling social media or TikTok and things like that, where actually instead of helping you, it just becomes so fun and engaging, it sucks you in the rabbit hole and you end up not doing things like exercising, interacting with other human beings, you know, all that stuff. So again, that would be another example of over AI-ing it. So we just really need to make sure the machines are doing what machines do best to enable humans to do what provides them with the most utility to achieve or accomplish what will move that human being or that set of human beings forward. So I just wanted to make that really clear. That’s what I mean by over AI-ing it.

Jack Sharry: Talk a little bit, if you will, because I know you’ve been studying this for a long time and in depth and at different firms with different perspectives. Everyone’s trying to figure it out and you’ve been in that figuring it out stage for a while. I’m going to… not guess, I know you’ve figured out far more than most. What’s your prediction timeline-wise? Where are we? Where are going? What’s next the one to three years? I don’t know. How does AI go from being an interesting notion, not a fantasy, but something that’s interesting and scary for many. Talk about what do the next few years look like? How does it become more incorporated? And most importantly, how does it play out in terms of having real impact, positive impact for everyone?

Michael Liersch: Sure. I think that’s uncertain right now. So I’ll just say that out of the gate. Like I am not omniscient. I don’t know the future. I have a hypothesis. So I’ll share that. But before I do that, my hypothesis is predicated on a fun framework and I can’t remember who shared it with me. This is not a framework I developed, Jack. So I want to just make sure everyone knows that. You know, I don’t steal people’s ideas, but I can’t remember who it was, but it had an X and a Y axis. So the X axis was like, very mundane AI kind of things to like the innovation, like extraordinary, like I can barely even imagine it kind of AI stuff. So that’s the X axis. The Y axis is like internal to a company or organization, you know, that’s producing it versus exposing it to their external constituents. So that’s the thing. So you can imagine this, there’s a quadrant of that where it’s like extraordinary, crazy innovation, exposed to the end constituent, like that’s one category. And I will say, Jack, in your continuum, we’re not going to get there for five to 10 years, at least, because there’s going to be some big missteps and mistakes on that topic, kind of like we just described. And then it’s going to cause all of us to want to pull back. And I don’t know what those will be, Jack, but I think we all just need to be wary and aware of them. And then there’s the other quadrant, which are the very mundane basic things that are internal to a lot of companies, kind like we talked about, efficiencies, recording things, automation versions of AI, like AI agents, basically, you know, things like that. That’s already happening at scale, as you well know. So I think where we’re really at is testing the waters on how much we want the machine to do and think on our behalf. Right? So there’s like physical activities almost as well as the cognitive ones. How much do we want it to do? Because we all don’t necessarily want it to go to the machine, basically becoming human. But we know there’s more for the machine to do than like stuffing it in, you know, the basement and doing like, you know, tasks that we’re just not all interested in doing or thoughts that we don’t, we’re like bored of like exploring. So I would say five to 10 years before we get to some really extraordinary public things at scale, when you think about that, Jack, it’s not too far off, which is I think why we’re all talking about it. And at its foundation, all of this is going to be predicated on having enough power, not computational power, but literally energy to power the machine. And so I think that will end up a gating factor as well as just the human capacity to really digest that the machine is going to be such a big part of our lives. The final thing I’ll say on that is someone shared with me, there’s a belief out there that this is the last year that managers at companies are just going to be managing people. They’re also going to be managing machines. Literally like performance managing machines, if that makes sense, Jack.

Jack Sharry: It doesn’t, so help me.

Michael Liersch: So you can kind of already see where we already are. It’s already too late. It’s happening. It’s just, to your point, more on the matter of time and how, I don’t want to call it dramatic, but how intense it gets versus, the change management is more dragged out over time. Does that make sense to you, Jack, or no?

Jack Sharry: Totally. So let’s as we start to think about closing our conversation for now, because as you and I are wont to do, we will be continuing this dialogue, not necessarily on a podcast over time. So as you’re looking out, you’re still less than a year at Edelman Financial Engines. You wound up in a wonderful spot. You’re doing cool work from all I hear and observe. What does the next year or so look like? Not just about AI, but just, I know you’re doing a lot of exciting stuff and I’m sure you’re not gonna share the details of all that, but where do you hope to get? What do you hope to be able to accomplish? What are you looking to do? Because AI is a tool, AI is a capability and an answer. But what does Michael Liersch, in your leadership role, what do you hope to accomplish?

Michael Liersch: That’s a really deep question, Jack, I’m gonna be really honest with you. You just like, you sprung that one on me. I’m going to tell all your listeners. So there’s no preparation for this one. So I’m just going to be authentic about it. Because I guess I have to be now. Otherwise I… I really want to move Edelman Financial Engines and the financial industry in general in the direction of having advice be the actual product that is not only delivered, but is that we get compensated for in the industry. That would be my life’s desire, Jack. And it’s where I’m really nudging Edelman Financial Engines toward because it is such an advice engine. Our planners, our employees, our workplace business, and all the people that work in that, for our plan participants and our plan sponsors and record keepers, and we have a whole employee planning business. They’re so passionate about advice and we have so many extraordinary advice capabilities. It’s like the perfect marriage between what we just talked about, the machine and the human. And if that becomes the product, you’d have all the things that are part of it, you know, investment advisory services or management services, estate planning, asset location, where all that stuff becomes a part of it. But in the spirit of where you started us off at this idea of putting everything together, advice just puts it all together. And that’s what I would like. You react to that, Jack, because you’ve known me for many years. So does that sound Michael Liersch consistent?

Jack Sharry: Well, it’s totally Michael Liersch, it’s also Jack Sharry. So we’re birds of a feather in that regard. And the great news from where I sit, and it completely supports what you just said, is that we’re getting there. You and I have talked about this, but I’ve been through a planning exercise not too long ago. And it was interesting to be on the planning side, because I’ve never really done it. I’ve done pieces of it, but not really. This time it was a very comprehensive plan, very sharp advisor team, knows their stuff. And they were just chomping at the bit to talk to me about investments. And that wasn’t my interest. My interest was advice about real estate, about children and grandchildren, about healthcare. That’s the advice I was seeking. And they still, we just had a review session recently. They were chomping at the bit to talk about investments. And I just buy models that fit my risk parameters. And I’ve made it abundantly clear, taxes are the enemy. That’s what we’re working against. And I’m not trying to hit home runs. I’m way past that. I never really did it in the first place, but I know that that is not the game. That’s not gonna get me where I want, but what happens with my family and my lifestyle and my health and all the rest of that stuff, my life experience, that’s what I want help with. And they’re good about it. They humor me. And I want to make sure, because I’m going to assume my wife will be around longer than me, I want to make sure she’s taken care of this. This not her jam, although she’s incredibly talented in so many ways. This type of stuff, she hasn’t been around it as much as I have. Anyway, a long way to say that what I want is advice. I want guidance. I want to know what makes sense for me. And I don’t want to look at a lot of stuff about it. I just assume, they wanted to review the portfolio, I said I know what we bought. I know how it did. Just give me the high level. Yeah, okay, they were making the case I would beat the benchmark. Okay, great. I don’t care about beating the benchmark. Benchmark’s fine by me. But my point of all that, and to your point about advice, I think that’s what people want. And whether it’s enabled by AI, which it will be, I believe, and by the kind of work you’re doing on the factory, that’s got to be part of it as well. All that’s coming together. So II’m personally very bullish on where it’s all going. I think of AI as an enabler, not as a detractor. And I understand all the issues around that. But I’d love to hear your thoughts. I mean, it sounds like we’re, I know we’re birds of a feather in this…

Michael Liersch: I agree completely and maybe I’ll just add one more component of advice that we have in high demand at Edelman Financial Engines, which is just the behaviors that one can exhibit to maintain peace of mind and confidence in the plan. So I just did a webinar. When I talk about advice, I’m talking about all the things that to your point we’ve alluded to, discussed, investment management, your point on the factory, all the way to, you know, like the, in the conversation with the planner. But then there’s this sort of broader based advice, which is, you know, what are the behaviors that are going to get me to where I want to go? That’s one of the most in demand things at Edelman Financial Engines. So much so that we have these webinars. I just did one on, and Jack, I’m not kidding. Like it’s simply on how I can not be freaked out by the newsreel, an hour long webinar. That’s what people wanted to know from me.

Jack Sharry: Explain what you mean by not being freaked out by the newsroom.

Michael Liersch: Well, imagine you wake up, you know, the new year and you know, there’s Venezuela and Greenland and right. It’s like, what’s going to happen next? Right. And then people link it immediately to their portfolio. Is something going to happen to your point to my portfolio? Should I make a portfolio change and what are you doing at the institutional level? What should I do at a personal level? You know, should I save differently as well? Or do I need a bigger emergency fund? Should I get a different job in light of AI and all that’s happening, right? It’s all this kind of stuff. And so what, you know, I gave five methods of really, and I’ll just give one of them, of really filtering out the noise. And what I said is, you really have to be selective and this leads into the AI conversation too is you have to be selective of where you get your information these days. It used to be like information asymmetry, it was so hard to get information. Now there’s too much and too much unreliable information, too much biased information. So what I said is you really have to investigate where you should be getting your information from and not so that it’s consistent with your thinking like a confirmation bias, but so that it’s actually creating a dynamic where it’s challenging you in all the right ways to make the most productive decisions. Do something, don’t do something, pause and wait, right? Like that kind of stuff, because you can’t always be talking to the machine. You can’t always be talking to a human being. So that’s the kind of advice too that people are gonna need, Jack, on an ongoing basis. It’s gonna be one of the most critical components in tomorrow’s world.

Jack Sharry: Well, Michael, as always, thoroughly enjoyed speaking with you on all this. I think we’re way over time, but we can…

Michael Liersch: Sorry about that.

Jack Sharry: Oh, no, no, no, all fascinating stuff. But we should wrap things up and bring it on home. And in deference to our audience, we try to keep these to a half an hour. This might be a wee bit longer. And you’ve answered this question before. I’m going to ask it again to see if anything has changed. What do you do outside of work that people might find interesting or surprising, that you’re particularly passionate about or excited about. Anything new or more of the same? You lead a pretty exciting life as far as I can tell. But go ahead.

Michael Liersch: I don’t know about how exciting it is. My daughter, I think I’ve shared with you is a competitive squash player. She just crushed it in a big international tournament. So what I’ve started doing is actually on my off time with my wife, try to learn to play squash and I am terrible, Jack. Terrible. So next time we talk, I’ll let you know if I’ve gotten any better. But I’m gonna be doing lessons two to three times a week. My daughter’s not gonna listen to this, so I’m gonna keep it actually secret from her. And one day, just play squash with her and she’ll be surprised that dad can actually hit the ball.

Jack Sharry: Right, right. She’s still going to kick your butt, I would imagine.

Michael Liersch: Yes, for sure.

Jack Sharry: Based on what I understand, she’s highly ranked in the world, isn’t she?

Michael Liersch: Yes, she is.

Jack Sharry: Very cool. So Michael, thanks again. Really appreciate the conversation. As always, we’ll have more. For our audience, thanks for tuning in today. If you’ve enjoyed our podcast, please rate, review, subscribe, and share what we’re doing here at WealthTech on Deck. We’re available wherever you get your podcasts. You should also check us out at our dedicated website, wealthtechondeck.com. All of our episodes are there along with blogs and curated content from many folks around the industry. Michael, thanks again. It’s always a pleasure.

Michael Liersch: Thank you, Jack. Likewise.