Jack Sharry: Hello everyone and welcome. Thank you for joining us for this week’s edition of WealthTech on Deck. I’m delighted to be having today’s discussion. Conversations on this podcast, across our industry, and everywhere else, it seems, have increasingly centered on the evolving role of artificial intelligence and its impact. Many of us are exploring AI’s applications, determining where it integrates most effectively, and seeking to understand its broader implications. Today we are joined by an expert in this exponentially expanding field. Our guest and friend is Amy Young. Amy has been a managing director at Microsoft, leveraging her extensive background in capital markets, wealth management, and consulting to establish strategic partnerships with Microsoft’s major financial services clients. These partnerships have focused on data monetization through generative AI. As we will get into in a moment, Amy recently set up a consulting practice around helping firms be more productive, effective, and competitive as they determine how best to leverage AI. Amy’s consulting practice draws on insights from her three decades of experience in technology partnerships, management consulting, and equity research to assist disruptors in reimagining the wealth management sector, ensuring value delivery for clients through AI. I’ve had the good fortune of knowing and learning from Amy for many years, and I am pleased to welcome her back to our podcast. Amy, good to have you on WealthTech on Deck again. I’m excited with what we’re about to talk about.
Amy Young: Thanks so much, Jack. It’s always a pleasure to meet with you.
Jack Sharry: Yeah, we’ll have some fun here. So Amy, take us through if you would, what you’ve observed, learned, experienced over the course of your career and more recently at Microsoft.
Amy Young: As you said, I started my career more on the institutional side of things, equity trading and equity research. And I really came to the wealth industry 10 or 15 years in, shortly after finishing my MBA. And that was where I developed a real passion for behavioral science. Kahneman had just won the Nobel Prize and this idea of humans, there being a big gap between what they know they should do and what they actually should do, was really starting to seep into the business consciousness. And that coincided with starting my first management consulting firm. And I started doing some work in the wealth sector on go to market and financial planning strategy, things like that. But at that time, the legacy model, the traditional model of advice, in-person meetings once a year, that really didn’t offer any practical or scalable way to combat the cognitive biases that were preventing people from doing what’s best for their financial well-being and their financial future. And so of course the iPhone gets dropped into the middle of this conversation. And that was really what, you know, the first wave of fintech sort of around 2012, 13, 14, really excited me about the opportunity to democratize advice. Because, you know, we have this thing that’s with us all the time that we could design experiences to nudge us towards the behaviors and actions that are good for our financial well-being. So that was really a turning point for me. And ultimately that’s what led me to Microsoft about six years ago, because I wanted to, having come from a capital markets and finance background, I knew tech was the vehicle to changing how this industry works, but I really didn’t know much at all about tech. So joining Microsoft, the idea was to learn more about that.
Jack Sharry: So you’ve parted ways with Microsoft and you’ve hung your own shingle. Talk a little bit about what you hope to accomplish, what you hope to do. I know you’re already doing a bunch. So, fill us in.
Amy Young: So first of all, I mean, the job that I did at Microsoft was working with Microsoft’s largest wealth and asset management and financial data companies in the world. So that was truly a privilege to have the opportunity to have this front row seat over the last few years at this really pivotal moment in history, this evolution of gen AI. And I’m incredibly grateful for the learning opportunity that that afforded. But what I had started to see in my final months there was as the gen AI technology has matured, and we’ve clearly pivoted from the experimentation stage to the application and implementation and scaling of AI. And I saw a need amongst the industry for somebody who could help them bring together the technical knowledge with the industry domain expertise. We still have, I think the biggest challenge that’s impairing the wealth industry’s adoption of AI is that leaders have a bit of a skill gap. They have a huge learning curve to scale on AI and maturing AI, like building a whole stack and a strategy and a roadmap really requires those leaders to upskill. And that’s where I think I can help them navigate that path. The firm that I’ve created is called Advice Architects. And that name, actually suggested by Gemini, I got to give credit where credit is due. That name captures the idea that advice is absolutely central but that how we architect our stack is a critical success factor for the delivery of that advice.
Jack Sharry: So fill us in a little bit, if you would, Amy, you’ve seen the industry from the biggest brands in the world. You’ve seen what’s going on. You’ve watched the early stage evolution across lots of different kinds of firms, whether they’re asset management, wealth management, operationally oriented places. So talk a little bit if you would about where the industry is today, then we’ll talk about where things are headed next.
Amy Young: Sure. It’s been really dazzling to watch the pace of change of how these gen AI capabilities have evolved in the three or so years since ChatGPT hit the scene. So if we think back to November of 2023, when this all started, ChatGPT was just a language model and a chat interface. Its data source was the model itself. You might recall people said, you can only answer questions up until something like October of 2021, because that’s the data that had been trained on up until that point. What’s happened over the last three years is we’ve decoupled the model from the data sources and built a whole bunch of other tools around it. And that activity has dramatically improved the effectiveness of AI. We can now point the model at a whole range of context to make sure that it’s interpreting our questions correctly and that it’s using trusted governed data to answer our questions accurately. And there’s all sorts of technical guardrails and evaluation tools and things like that that have evolved around this. So we now have, it’s not just about the models on their own anymore. It’s about how we build applications to harness the language skills of those models with all of this trusted governed data around it. And that’s, that’s really been the transformational thing. Because when it first started, we didn’t know what data it was trained on. The hallucination rates were off the charts. And, of course, everything you were putting into it was being put out into the public domain to train open AI’s next model. So for the first year, 18 months, it really looked like this gen AI thing was going to be a big nothing burger for the wealth industry. But as it has continued to evolve, I think we’re well on the way to having meaningfully addressed a lot of those concerns.
Jack Sharry: So you mentioned that AI has become more effective and accessible. So talk a little bit more. What does that mean? Where does that take us?
Amy Young: Well, so the effective piece, I think it was what I’ve already talked about, the accessibility piece is a little different. So the metaphor that I use here, if you think back 15 years ago, if you wanted to build a website, you generally needed to hire a developer to help you build that website. Well, today, most folks have built a little website at some point, whether it’s their careers or their personal lives, right? Maybe it’s for your kid’s soccer team or, or whatever, you know, we have these tools that have made building something like a website completely accessible to people with pretty much no technical knowledge. Well, the same thing has occurred in terms of building AI tools. Again, I’m a finance person. I’ve never written a line of code in my life. But I’m speaking at a CFA Society of Los Angeles event in a couple of weeks. And they’re focused on having demos of actual wealth tech experiences. And so I have created a prototype of a wealth tech experience. I’ve done it in Google’s Gemini and I’ve also done it in Anthropic Claude just to see how the two different tools work. And it’s been quite dazzling what I can do still having no clue how to write a line of code. So this, the, the democratization is also occurring in terms of the developer process. Now to be clear, this prototype should not be anywhere near a client or a scalable application. So firms that actually want to build, need to build industrialized productionized stuff that still requires development resources, but it requires way, way less than it used to. And so I think that’s, these… a much more sophisticated tech stack is now accessible to much smaller firms than it’s ever been before.
Jack Sharry: Yeah. As I understand it, because I’ve been reading up on all this stuff, just trying to understand, because I’m a layman, I’m more of a lay person than you on this. I’m pretty impressed with what you just told us you built. But it sort of sounds to me what I’m hearing is that’s kind where we’re going. At least in our company at SEI, we’re using it. I’m using it daily, mostly for the kind of stuff to just speed things up, help me organize my thinking, et cetera, et cetera, all very, very useful. But I gather the objective is to then use it more proactively in the way you just described and that I can start to impact that. They’re not going to take anything I might develop and use it out in the public, just like you mentioned. But talk a little bit about that, because really what’s underway is it’s going to be easier, faster, quicker to start building this sort of stuff. And I think certainly for the big firms, they’re going to take it a lot further. So I’m kind of curious how this plays out because again, it strikes me we’re early stage on all this, but where does all this lead?
Amy Young: Well, so this is where I think we should talk briefly about agents because that’s been the hot topic for the last several months. And lots of folks, me included, believe that 2026 is going to be the year that agents sort of hit prime time and we start to see them deployed at scale. And so an agent, I was talking earlier about how language models are now, gen AI solutions are now not just about LLMs, but about applications built around LLMs. Those applications, we now call them agents. And the, putting all of these other building blocks around the LLM has allowed us to do a whole bunch of new things. Probably the most important of which is a shift from using them to find information to using them to execute tasks. And some of those tasks, like I don’t want people to start thinking about AI as taking over the whole process, because it’s not that. Tasks could be as simple as find me podcasts about the future of wealth tech and put them into my calendar? Six months ago, you had to do all of that manually. It couldn’t connect to your calendar and take the action of booking that event. So that’s a huge shift with these agents. You mentioned being proactive. A big part of this, I think, is going to be that agents will be able to look at things like our meeting transcripts in the background and take the idea of next best actions to a whole new level. So one of the examples that I’ve talked a lot about in my public speaking of late is elder care. And I know you’ve had some great speakers on this podcast about elder care. So let’s take that as an example. Picture, and I want people to picture something like an elder care agent. And what it would do is it would help advisors have conversations about elder care when they don’t have particular expertise at that. So it could, and the thing that I’ve been mocking up for this CFA event, it analyzes transcripts looking for signals that a family might be approaching some kind of a need for elder care. So it would identify references to, you know, mom sold her house and moved to a retirement apartment or something. One of the next best actions could be to ask the client about powers of attorney. Or, you know, have they created a trust of some sort, all of these things that lead up to the estate planning conversation. And the proactive piece is that instead of waiting for the client, the elderly person to have some kind of a crisis event, right? They have a bad fall. And then the client comes to you and they’re like, my goodness, I don’t have any of the documentation in place to care for this aging parent. It’s a horrible scramble at a time where everybody’s already really stressed and upset. So I think there’s no end of things like that, whether it’s moving house, changing jobs, all of those things have a lot of complexities to them and AI can help advisors proactively have those conversations. And I know at SEI, you guys use Microsoft’s Copilot. One of the important aspects of this, and it doesn’t matter if you’re a Copilot shop or a ChatGPT enterprise shop or a Anthropic shop, all of those platforms offer what Microsoft calls the UI for AI, which means that they aim to be a single entry point that simplifies the user’s interface to engage with all of this stuff. So in a wealth context, everybody’s talking about meeting prep, right? Well, I think meeting prep is a chassis, if you will, that is going to evolve over time to provide richer and richer next best actions. And that could include things like an agent, an elder care agent, adding to your meeting agenda, saying, I found these signals of a need. Here’s a way that you can open this conversation based on what I found. Not a generic, here’s the elder care conversation, but here’s what I’ve diagnosed about your client’s situation. And here is the right way, the personalized way to approach this conversation. So it’s no new tool, right? It’s no new tool for the advisor to learn. It all feels to the advisor like it just sort of magically shows up in whatever their interface of choice is.
Jack Sharry: So I read an article today, there’s a company called Jump that does sort of meeting planning, pretty simple, straightforward tool, but very wisely. They’re now monitoring the conversations anonymously, but they’re monitoring them to see what’s important to clients. And guess what? Those advisors that address client fears ultimately sell more stuff. That’s not how their press release went. But you got the idea. And it struck me that, I shared with some colleagues, I felt sort of dumb like saying, clients want you to understand their fears and then address them. But I think in our industry, and this is part of the evolution now underway, and I’d love to have you comment on all this, is that advisors tend to want to sell investment stuff. I mean, I’ve had that experience personally where the advisor team I work with, they can’t wait to talk about investments and I don’t really care. I just know I just buy models and I set it and forget it. It’s just not what I’m interested in, especially at this stage of my life. Just don’t want to lose and I’m not looking at a home run, just how it is.
Amy Young: Well, and more importantly, you’re savvy enough to know there are no home runs. If they are, they’re luck, right? They’re not repeatable.
Jack Sharry: Exactly. I’ve tried a couple of those. They never work out. They’re always a strikeout or a fly ball or whatever they are. Anyway, point of all that is that consumers have issues and they want those addressed. Often not, by the way, how we get paid. That’s a whole other matter that we’ll get to at some point maybe. But the point is that how they get paid is selling stuff, namely investments, but not providing the advice, which is really what I’m after, I think, to your elder care example. I guess the question is, in the practical application of this, at firms that are just have to be mindful of governance and compliance and so forth, that would seem to be a real drag on what might be. So comment about, as this goes into effect, where you’re giving advice on elder care, where there’s no expertise present other than access to information to AI, how do you see that playing out? I’m kind of curious.
Amy Young: Okay, well, first of all, I don’t mean that AI is going to just go pull random information. What I intended to convey is firms will develop knowledge sources that they trust for the different mechanics of elder care, and they will create agents that use those knowledge sources. I’m thrilled to go check out this Jump AI research that you mentioned because it has seemed obvious to me for years that solving clients’ day to day problems around, I’ve called them micro steps of life events in the past, but like the, know, historically the industry, it’s life events are, you graduate college, you buy a house, you get married, you have a kid, and you retire. Those are kind of it, right? And like, what about the 40 years of life that happens between that? There are all sorts of events that create complexity for people. Every time you start a new job, you have new benefits, you have new comp plans. Think about an agent that ingests your offer letter so that your advisor knows how you get paid, when you get paid, and they can proactively help you plan around that. I mean, I could rant about the, this idea that people have ongoing problems to solve and that solving those problems will help you consolidate assets. And that is how you will get paid. So I think, I don’t think we necessarily have to upend the whole revenue model of the industry. We know clients have their assets spread across a lot of different places for a lot of different reasons. And that’s always been the promise of holistic financial planning, right? That it would consolidate assets, but we haven’t historically had tech that was advanced enough to understand the unstructured data piece of our life, right? All it had access to was the stuff we typed into fields in a financial plan. Well, now we can add all of these layers of resolution and context on top of that. And that’s, I think now we actually can fulfill that promise of holistic advice leading to consolidating assets and the firms that get out in front of that, I think are going to reap substantial financial benefits from that.
Jack Sharry: Yeah, and we’re going to push on to bring this to a close here shortly because you and I could go on on this. I know we’re both passionate about it. But one of the things that strikes me, particularly as people move toward retirement, toward that, so the tail end of that work, those working years and into a whole new next chapter with a whole bunch of stuff that like where to live and how to deal with healthcare and then later elder care and all the things that frankly most advisors aren’t terribly comfortable with talking about. They’d rather talk about portfolios and that kind of thing. But the way I envision it, I’m sure you find it the same. It will be a better way to help people like me get on the right path to getting resolution and working with other professionals, whether it’s estate attorneys or whoever it might be to work out my particular highly personalized set of issues.
Amy Young: Yeah, I think, and I’ve actually had new perspective on this from this prototype that I’ve been building just over the last couple of weeks. If you think about how advisors advise on something like an elder care life event today, you either ask the firm to give you customized collateral for like the three top situations, right? Like we say, here are the segments, here are the typical paths. We’ll give you specific guidance on how to answer, how to address, help clients in these three paths. But of course we all know that there are hundreds of permutations on that, right? So one to three isn’t enough. The other thing is, so the other alternative is we create a 50 page white paper that gives you the details of how to handle every permutation. Like it gives you the rules and gives you some examples of how to apply them. The beauty of this gen AI stuff is that it provides the mass personalization by understanding the individual client situation. I have a trust, I have a financial power of attorney, but I don’t have a health power of attorney. Or I have the powers of attorney, but… whatever those details are, right? And then it takes that 50 page white paper and it tailors the rules and guidance to your specific thing automatically. And so that mass personalization, I think, is the unlock.
Jack Sharry: Love it, love it. There are many more questions I’d love to ask you, but our time grows short. So I’m going to look to wrap things up here. So Amy, I really appreciate it as always. So I learned something every time I talked to you and I learned a bunch today. So thank you for that. As we look to wrap up, what are a few key takeaways you’d like to share with our audience?
Amy Young: So the way I think about is that there’s a why, a what, and a how. And we’ve all heard there’s some emerging research about clients who have advisors are increasingly consulting tools like ChatGPT for financial advice, either in between meetings or to check what the advisor is telling them. That to me is the why right there, because if advisors aren’t able to differentiate versus what a consumer can get from ChatGPT and it is, it’s pretty darn good, the industry is going to have a problem. So that’s the why, why folks need to care, invest in learning more about this. The what I think is about this sweet spot of a mid sized firm. So I say mid size because there are two things that I think firms need. The first is enough of a sample size of data. And that only comes from having a certain number of advisors having a data set of thousands of conversations, right? So the, the promise here is to capture the best practices of how the best advisors handle different kinds of conversations and use that to guide everybody towards those best conversations. So you need to have, I think a couple hundred to a couple thousand advisors for that to really start working for you. And similarly, you don’t need as many IT folks and product developers. You still need some, right? So this isn’t like the one man band kind of gig that’s going to change the world here. So that’s the what. And the how really is just that the tools are making it easier and easier. We’ve had a couple of big announcements of WealthTech startups raising some serious money in the last just two months. I’m thinking Range, Nevis, and FINNY, for people to go check those out if they haven’t heard about it. I think we’re the fact that the tools have gotten so much easier to use is going to unlock opportunities for those mid-sized firms to leapfrog.
Jack Sharry: Another firm that we’ve had on the podcast is Savvy. It’s an RIA that’s actually a year or more older, old, and same sort of thing. Just AI is fundamentally how they have been operating and intend to operate. So Amy, thanks. This is great. I’d love to keep going, but we’re going to close it out with my favorite question. You’ve answered it before as a guest on this show, what do you do outside of work that you are excited or passionate about that people might find interesting or surprising?
Amy Young: So last time I told you about how I make beer at home, but this time I have a much more interesting answer. So…
Jack Sharry: That was pretty interesting.
Amy Young: So about 20 years ago when I first started my consulting practice, a friend gave me a book called Never Eat Alone. And it was about just bringing people together at a human level. I know this is core to who you are, Jack, being connected, and I really embraced that. And so I’ve been hosting sushi dinners of random groups of women in my home for the last 20 years. And it used to be about business development for my business. But when I moved to New York six years ago, it became about making friends because you move to a new place, you know, you don’t have kids in school, you got to get creative. And so basically whenever I have a pleasant chat with somebody in a coffee shop or walking the dog. I invite these near strangers to my house for sushi. And the amazing thing is no one ever says no. They look at me a little funny and they’re tentative, but they still come and they always come back. So I’m thrilled to the opportunity to mention that on your podcast, cause I just moved again from New York to Nashville. And so I’m in full, you know, building my social network mode. So any of your listeners who live in Nashville or are passing through Nashville, this is my open invitation. Drop me a line.
Jack Sharry: That’s great. I find myself there once in a while. So I’ll take you up on it, I suppose it’s all right if you already know me, but in any event, that’s great. So Amy, thanks. This has been great as always. For our audience, thank you 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 our episodes are there along with blogs and curated content from many folks around the industry. Amy, thanks again. This has really been wonderful.
Amy Young: I appreciate the opportunity. Thanks, Jack.
