Brad Johnson: Quin, welcome back. Shannon, welcome.
Shannon McGinnis: Thank you.
Brad Johnson: So, those unfamiliar, Quin is the CTO at Triad. Shannon, Chief Compliance Officer at Triad. And today we are going to talk about Claude for Financial Advisors, which is making quite a bit of noise. Today, as we record this, it’s September 18th, 2026. Rolled out when? Monday?
Quin Kilgore: Monday.
Brad Johnson: So, what would that have been? The 12th, 15th?
Shannon McGinnis: Four days ago.
Brad Johnson: Four days ago. Don’t do math on camera. So, anyway, today we’re going to really dive in, open discussion, early takes. This is days old, but obviously AI’s not going away. We’ve been running an AI mastermind inside of Triad with many of our members for the last year or so, and this was a very hot topic on our call yesterday, and we said, “Hey, let’s sit down, let’s do a recording, and let’s just talk about the pros, the cons, where this thing’s at,” because there’s a lot of advisors out there I know at Future Proof that just got unveiled this new tool. So, we’re going to have three different takes here, which is really fun. I’m going to really play the role of financial advisor, sales guy.
It’s really the world I’ve been side by side with a lot of advisors over the years, so I kind of understand how many of y’all think. We’ve got the tech side, the tech stack side, all of the connections, how they work. We’ve got the, “Hey, let’s not get ourselves in trouble” side from Shannon. So, I’m just going to throw the first question out. First take right now: Claude AI for financial advisors. Quin, if you’re an advisor out there, what would you be thinking right now?
Quin Kilgore: I think it’s incredibly exciting, right? It’s one of those that advisors work in their tools that they’ve worked with for the last 10 years, right? Their CRMs, their portfolio accounting, the financial planning, it’s all a different tool. The custodians even. You have to go out to a new tab and use these tools. Now they’re introducing a way to use one interface inside of Claude to connect all of these workflows, which begs the question of, we talked about this, where are we going to work in the future? Are we still going to have reasons to go out to these tools when, in theory, an agent could go run all of these little tasks, and you can run in a headless way, which is just connecting everything to Claude and having Claude make these different workflows work. So, it’s pretty, pretty cool.
Brad Johnson: So, just to paint a picture there a little bit, because this stuff can get technical really quick. All of us now, at this point, have interacted with Chat, Claude, Gemini, some form of an app probably on our phone with more of a chat interface or even voice interface. What you’re saying is we may be looking into the future where that is how I’m pulling the data out of my CRM, how I’m pulling the data out of Orion or eMoney to where it’s just like, “Hey, give me my three appointments for the day. Summarize them.” Boom, there it is prepared for the day.
Quin Kilgore: Yep. Now, devil’s in the details, and we’re obviously going to get deep into this here. But we initially ruled out AI and tried to keep client PII out of it, right? So, our acceptable use policy says basically no PII in the AI tools, especially AI tools that are not accepted at Triad, right? So, everyone’s going to need to go review their AI acceptable use policies and update it.
Brad Johnson: That they might not have at this point, to be clear. So, first point for you advisors, like that is very important. We talked about that yesterday. We’ll throw that to you in a second, Shannon. So, you should have a policy. So, what you’re saying is if everybody in your firm is walking around with Chat or Claude on their phone, they probably shouldn’t be using it for business purposes. In personal accounts.
Quin Kilgore: In personal accounts. Yep. If they’re using their work-related accounts, then it’s probably okay, assuming that they’re following all the other guidelines that are inside of their AI policies.
Brad Johnson: Yeah. Gets complicated pretty quick.
Quin Kilgore: Very quickly.
Brad Johnson: Shannon, same question to you. If you’re an advisor out there, there’s this new tool. What would you be thinking more from a protect-my-business standpoint?
Shannon McGinnis: So, Quin and I talked about this a little bit before the podcast started, and I think this is a really exciting development because it means AI has come mainstream for advisors, but that means your compliance program has to also be elevated to that level. So, AI isn’t a novelty that anyone’s using just for creating a new marketing piece with graphics and copy that’s already complied, right? It’s starting to pull from a lot of these sensitive areas, and it’s starting to prepare things that would be client-facing that would impact decisions the client might make. So, that means, like you all just touched on, you have to have a pretty sophisticated compliance program to support this.
So, that starts by addressing AI use in your compliance policies. That starts by having, under the new Reg SP, a really good vendor vetting system to vet anything that you’re going to use with AI. It starts by having an AI policy that has owners and that is specific. Quin said, “If our AI policy says you can’t use it, then you can’t use it.” Well, now you also have to test everything that you’re saying. So, if you vet a vendor and there’s a certain set of criteria that’s there that you’re comfortable with, you have to check it again later and make sure it hasn’t changed. If you say people can’t use it for X, Y, or Z purposes, how are you validating that no one’s using it for X, Y, or Z purposes?
And even if you have a list of approved tools, how are you validating that they’re not using unapproved tools to circumvent the rules and systems that are in place? So, still super exciting, but does draw attention to the fact that just because it exists doesn’t mean it’s ready to immediately turn on. Due diligence in all of these systems is going to be critically important.
Brad Johnson: Well, and one of the things that I believe Claude for Financial Advisors addresses is the logging and archiving, like there’s ability to connect that on. Correct?
Quin Kilgore: So, you need to go up to the enterprise version of Claude. So, it can’t be the Teams account.
Brad Johnson: Real quick, so rewind for those maybe, here are the levels of Claude. Like, I download the app for free, and then what are the actual options?
Quin Kilgore: Yeah, so there’s the individual account, which I think you can get a pro account, right? But that’s for individuals. For companies, there is a Teams account and an Enterprise account, and they have different logging mechanisms within there. The logging and the auditing that we would need for the RIA space is the Enterprise version. That has the ability to go say, basically, track how many tokens are being used, what messages are being sent, where the data’s going. That is the Enterprise version of Claude, and it is the most expensive tier, and that also brings up some other questions that financial advisors should be aware of. You don’t need to be using the highest-end model for every function within Claude, right?
If you’re just rewriting an email, you might be able to use a lower model like a Sonnet or an Opus over a Fable, to be able to pull these things off. That’s the tricky part here.
Brad Johnson: So, don’t take the Lamborghini to go get groceries, essentially?
Quin Kilgore: Exactly right.
Brad Johnson: Okay. Well, because obviously we’re exploring this at the Triad enterprise level, and one of the things you mentioned at the enterprise level if you’ve got team members that literally have access to Fable, which is very expensive, it burns through tokens like a Lamborghini burns through fuel, very quickly. You could turn it on and have a $10,000, $20,000, $100,000 spend, depending on the size of your enterprise, in a month because people are just out crunching tokens all day with no constraints. So, a lot of complexity really quickly. Shannon, you said something yesterday that I want to hit on. You said, “Just because it’s archiving doesn’t mean you’re covered.” Can you explain what you meant by that?
Shannon McGinnis: Yeah. So, it’s great that they spent the time to understand the rule and the requirements to have the logs, but now someone has to go look at the logs. So, yes, you need the logs, but the reason you need the logs is because you’re expected to supervise the logs, and that supervision goes to the coordination that I believe every firm’s going to have to have between compliance and technology. I mean, I’ve been in compliance for a long time, but I am no means a tech expert. And so, I think it’s really going to take those two teams and those knowledge bases to work together to understand regulatory requirements, and then also probably have someone be able to translate to you, “Here’s a log, but what does it say? What did it do? Where did the data go? Where did it come from? What prompt was used? Is that prompt a problem?” You know, like all of those things.
So, yes, it’s great that they built it to already generate all of that, but they built it to generate that because there’s a regulatory expectation that you have that and inspect that. And then if it’s not aligning with your process, your policy, or the regulations, you’re going to fix it.
Brad Johnson: Yeah. Well, it’s already super complicated if you look at social media, emails, texting. Obviously, if you’re an RIA, all of that needs to be archived and reviewed, right? Well, that’s checkers compared to chess if you’re going to AI, because now it’s connected to all these tools, so just the complexity immediately just grows exponentially. And so, I think a lot, I’m going to go back into financial advisor here, “Oh, here’s this new tool. This is amazing. I can just pull all this stuff in and be whipping up summaries out of eMoney, and here’s my five appointments for the day.” But what I think we’re all saying here is, “Just a second.” Take some space because you sure don’t want to be playing with the new tool and breaking a bunch of rules that are going to end you up in an orange jumpsuit at the end of the day.
So, I’m going to kind of open it up here. What other things should, if you were a financial advisor, would you be thinking about? Maybe we go back to the tech side. This is very cool and very exciting. But what are the things that you are going to start to see with how you think about building your tech stack, how it evolves, the speed, how all of this plugs in, whether Claude or other AI models for advisors in the future?
Quin Kilgore: Yeah, there’s a lot here, right? So, obviously, Anthropic beats OpenAI to this. You got to think ChatGPT is going to catch up and have their version coming out very, very soon. I think another story here outside of the connectors that came in the plugin, which was a core like twelve of them, which ones are missing? So, right now financial planning is completely missing from the connectors.
Brad Johnson: Can you hit a summary of some of the ones in there that you saw, just workflows or tools?
Quin Kilgore: Help me out here, but I think the most important one is Schwab. So, Schwab being a leader in the custodial space, being able to connect to AI, I think that sends a message about where things are going. Addepar, Orion, Envestnet, Black Diamond, all the portfolio accounting, the big names there are all in it. Wealth.com, and then I want to say there are a couple more investment-related, like FactSet is in there for plugins.
Brad Johnson: That’s pretty good rattling those off from memory. But anything we missed, we’ll throw it up, and you’ll see it somewhere on the screen here, all of the options that exist as of September 2026. And I’m sure a bunch more will be added as this thing evolves. So, okay, so you’ve got all these connections. It is sending a message back to Schwab. But you said financial planning’s missing. Speak to that.
Quin Kilgore: So, right now, and I’m going to lean on you here, but you shouldn’t use AI for financial planning. You don’t understand the engine there that’s actually coming up with these tools. You want the financial planning tools to actually do the crunching. So, you wouldn’t want Claude calculating performance. You’d rather use Orion for that. Same idea with financial planning. I don’t think software providers understand how to price this in the future because if people aren’t going to their hardware, or sorry, their software, and entering in clients and doing all the work there, how do they make money, right?
Brad Johnson: So, basically, software as a service is where do we go from here?
Quin Kilgore: And we’ve seen the models where some people charge for their API to get API access to build really customized workflows.
Brad Johnson: Remind everybody what an API is for the layman out there.
Quin Kilgore: Yeah, it’s application program interface. It’s basically a way for two tools to interact with the same data.
Brad Johnson: So, here’s Claude. There’s a piece of software. Here’s Orion. Those two talking together, that’s the API.
Quin Kilgore: So, this is where the confusing part. When it comes to AI, they call their API equivalent MCP, model context protocol.
Brad Johnson: And why is it different?
Quin Kilgore: That’s a great question. It’s very technical, and no advisor needs to know that.
Brad Johnson: Okay. But it’s essentially an API?
Quin Kilgore: It’s essentially the same thing. A way to make a connection that’s universal so they can pass the same data from tool A to tool B.
[COMMERCIAL BREAK]
Brad Johnson: Quick break to tell you about Belay, who helped sponsor today’s episode. One of the very first hires I made when we started Triad was my executive assistant. We got connected through Belay. She started out at 20 hours a week. I quickly realized I needed her for 40, and then shortly after, brought her on full time. Bottom line, if she wasn’t on my team in the early days, I don’t know how Triad gets built. So, if you’re an advisor and you’re still scheduling your own appointments, sending your own follow-up emails, or dealing with other tasks keeping you from bringing on more clients, you are the bottleneck.
Belay pairs financial advisors with vetted assistants who actually have financial industry experience. They are US-based and background-checked. And if your first hire isn’t the right fit, they make it right. So, go find your EA at belaysolutions.com/dbdl.
[INTERVIEW]
Brad Johnson: So, financial planning’s missing, and by the way, I mean, I’m a fairly heavy AI user, and it still hallucinates.
Quin Kilgore: Oh, yeah.
Brad Johnson: So, you sure don’t want to be taking your client’s future and, oh, we hope this works out, right? So, advice I hear you saying is financial planning needs to stay in financial planning at this stage of the game, and as things evolve and connect, there’s an interesting future where there could be this kind of summary feeding through AI based on the prompts you’re giving it.
Quin Kilgore: Absolutely.
Brad Johnson: Okay. Shannon, other thoughts? I know you have a lot on, like, here’s some stuff that could get you in trouble if you’re not careful.
Shannon McGinnis: Well, I think as a high-level takeaway, because we haven’t been able to get into the tool and see all the connectors, I think it’s helpful to just think of AI as a new employee. So, if you’re operating a financial services firm and you hire a new employee, most likely you’re going to do a background check on that person. So, that would be our equivalent of vendor due diligence, right? And you probably, before you do that, you have an HR policy, right? So, that would be the equivalent of the AI policy. And then when you get that new employee, you don’t just set them down at a desk, likely, and say, “Okay, here you go. Here’s every access to every system we have with all the PII,” and not give them any training or explain to them what your business model is, right?
So, one of the things we talked about yesterday with our mastermind, this is for financial advisors, but that means specifically the wealth space. So, most of the people we work with are independent financial advisors who, yes, offer AUM services, but also believe in fixed index products on the insurance side. So, if you turn this on, and that’s your model, I don’t know what the output’s going to look like, and it may not be representative of your firm’s philosophy on how to manage assets too, right? So, you may be spending a lot of time getting very quick output that doesn’t one-for-one align with your overall planning philosophy. So, you’re going to have to train all of this, which that’s part of AI, right? We’ve been talking about it for a long time. Even for marketing, you’re training it to talk in your voice fonts that you like, your colors.
So, again, using this analogy, we’re training the new employee, and then once you train an employee, though, you don’t just move on. You have one-on-one meetings, you have performance evaluations, so that’s this ongoing supervision of the tools you’re using. You expect a new…
Brad Johnson: Essentially quality control, making sure that it’s actually putting out what you’re asking it to put out.
Shannon McGinnis: Yeah, and if you hire an accountant, you probably expect them to do accounting work, not to start doing creative work. So, if you start to see their performance drifting or they’re doing something else, or they’re using some new thing to do something that you didn’t ask them to do, then we probably need to check on that, right? So, it’s this ongoing supervision and training, and then you also are going to expect them to evolve in their career. So, we would expect AI to continue to evolve and continue to add new capabilities, but then you’re going to kind of start over again with that, right? You’re going to check and see what that is, how are they using it? Is it aligned with our business model?
So, I think if financial advisors can just adopt that mindset, that AI is really new and exciting, it’s become mainstream. We talked a little yesterday about the SEC is not going to believe you if you say you’re not using AI. They understand that almost everyone is using it in some form or capacity, so they’re expecting you to explain how you’re using AI, who’s using AI, who’s responsible for everyone using AI. So, again, if you understand that and you treat it like a new employee and understand the framework there, I think that’s the right way to think about adopting AI, whether it is Claude for Financial Advisors or using it with your marketing team. You still need to understand all of those things.
Brad Johnson: Well, couple of thoughts. So, the first theme I’m hearing loud and clear, and it was loud and clear on yesterday’s mastermind conversation, back to your comment on the SEC, it is a widespread tool. Well, I know ChatGPT was the quickest downloaded app ever in the history of the App Store, and I’m sure Claude followed right behind it. So, shoot me straight here. If I’m a financial advisor out there doing business today, and I do not have an acceptable AI use policy in my business, am I putting my business at risk right now?
Quin Kilgore: Yes.
Shannon McGinnis: Yes, and I would say before you get an acceptable AI use policy, if you’re a financial advisor in business and you don’t have a very good tech consultant or strong knowledge base in your business to help you write an AI use policy and oversee it, you’re putting your business at risk.
Brad Johnson: So, back to making sure this is serving your clients, building holistic financial plans based on the actual tools, financial tools that you utilize in your business, right now, it would be eliminating a big piece of that toolbox, is what I hear you saying.
Shannon McGinnis: Yes. I believe you could probably work around it, right? It could probably still speed up a lot of the service you do for AUM. While we talk about it as something you offer a new client as part of their total plan, at some point you are managing just AUM separately than you’re managing insurance once they have that ongoing plan. So, it could still be super useful there, I mean, especially with the connector to Schwab. But when we talk about bringing in new clients and getting a total picture, it’s probably still a limitation there, which, I mean, Brad, you and I have worked together a long time. Our industry has continually had that issue of not being able to bridge the two worlds in a seamless place and one source of access, so.
Brad Johnson: That’s why we have Quin.
Shannon McGinnis: That’s why we have Quin.
Brad Johnson: He just fixes it all. He makes it all work, and it’s so easy.
Quin Kilgore: The tech team.
Brad Johnson: Well, that’s what I meant, the collective Triad tech team. No, it has been a problem forever. It is one that we are aggressively working to fix. And that is what’s exciting to me. Tools like this are going to accelerate it. Now, we have to do our due diligence. We have to make sure everything’s buttoned up before we plug it in to… We haven’t talked about PII much, on that note. So, one of the things that has been a theme in our mastermind that we’ve been running for a year is this would be really great. However, here’s the protection around my PII, my client’s information, SOC 2 compliance, all of that. And a lot of the tools require you to plug in, and it goes outside of the protected sandbox. How’s that work with Claude for Financial Advisors, the enterprise-level agreement? Does that change any of that?
Quin Kilgore: Yeah. So, I mean, this is my take, so feel free to disagree with me. But I think this is kind of the first shot that we need to start using the PII, which is context for AI to actually make these pattern recognition across all these tools. So, what that means is upgrade to the enterprise, so we have the auditing capabilities that we need, also the setup to make sure that your salespeople aren’t coding, right? So, have these little blocks in place, and then you need to go out and vet every connector. So, Shannon and I were talking prior to the podcast. The Schwab connector, as it turns out, is not going to send client PII. It’s going to send balance information, but we have no idea how it’s going to identify Brad’s IRA, right?
Brad Johnson: Interesting. So, how is that going to work? So, it’s got no client names or anything, so.
Quin Kilgore: You’re going to have to know that like, hey, for Brad Johnson, how is it going to make that connection behind the scenes to pull back your balance information? They’re doing something there, but that’s why every connector needs to be audited to know how it works, so you can audit it and know, hey, this decision was made based on this connector that is read-only from Schwab that pulled in this information, and then likely sent it back to your CRM, right? So, it gets very complicated very quickly. But back to PII, it’s probably the start of people getting comfortable bringing in client PII, taking an action inside of AI, and then sending it somewhere else.
So, last step here is you have to update your acceptable use policy, and you have to really tighten up your vendor management program. And then I would say there’s an added layer too, that anything that touches AI is you need to then go track the data lineage. What’s being sent from every connector? What do we get? What does it read? How long does it store that data? So, complicated very quickly.
Brad Johnson: We’ve got a few advisors out there right now, eyes are starting to glaze over.
Quin Kilgore: Sorry.
Brad Johnson: No, this is why we’re talking about it, because it’s not as simple as, “Cool, it’s out. Let’s start using it.” It’s not that simple. And that’s why we’re talking about it. So, Shannon, other thoughts on PII specific to how Claude for Financial Advisors kind of changes the game or maybe how you see it?
Shannon McGinnis: I would just echo what Quin said. The use of PII with Claude or any AI, it’s just going to mean that, like we said at the beginning, you have to have good vendor diligence. You have to have good policies and procedures to watch it. Quin said right now Schwab isn’t transferring PII. All of this seems to be evolving at a much quicker rate than we’ve ever seen software evolve before. So, if in three months they do start transferring PII, you need to repeat your process over again. So, I would say to that notion, concentrating on what does and doesn’t have access to PII through these connectors and through these systems is going to be critically important, and then understanding whether or not your evaluation of the use of a tool changes based on access to PII.
Brad Johnson: And am I making something up? Because I could be, because we’ve talked about a lot of different things the last week or so. Okay, let’s just say I’m currently running a financial services firm, and let’s say Orion is heavily embedded on the wealth side, and let’s say eMoney is my financial planning software. Does eMoney have a connection at this point? No. Okay, so no financial planning connection there. Let’s just stick with Orion. So, Orion’s already vetted. We’ve already done the due diligence as a firm. Obviously, it’s the 800-pound gorilla in a lot of the wealth management space. As soon as I connect Claude for Financial Advisors to Orion, don’t I have to recheck both sides because now Orion is feeding data to a new tool? How does that work? What’s the technical side of that?
Quin Kilgore: So, you’re treating Claude as a vendor, you’re treating Orion as a vendor. What we’re suggesting is you also treat that connector as a pseudo-vendor, if you will, to really understand, okay, what doors does this MCP open between Claude and Orion? Does it give you full access to everything that it has, which is some financial planning stuff, or is it just strictly balance information? Because they’re two different data points, right? So, that’s where every connector needs to be very, very closely audited.
Brad Johnson: Okay. So, basically we’ve got… Actually, let’s use Schwab. That’s a better one. So, we’ve got Schwab. We’ve got Claude for Financial Advisor. Obviously, Schwab is vetted. Claude’s a new tool. Now, this connection, we want to make sure the data’s going here, and boom, it’s accidentally going over here because the connection’s jacked up, because it creates new issues of protecting that data that’s very important to protect. And then making sure Claude is actually using it properly and not sending PII somewhere where you don’t want it to go.
Quin Kilgore: Correct. Yep.
Brad Johnson: Interesting.
Shannon McGinnis: And on that point, everyone that we’ve mentioned that Claude can now connect to has been in this space, primarily only in this space. So, Schwab doesn’t also sell shoes, right? So, they have histories of needing to protect the information the same way we do. They have histories of working with really sensitive client information. We’re now introducing Claude into that, which Claude does a lot of things, and they don’t have a regulatory history of being tested on breaches of information. So, it’s just kind of that thing where it connects to a lot of industry standards where, yes, you’re going to do due diligence on them, but they’re also how many custodians are there out there, right?
Like, you can pick one as long as they’ve been in business for a while and they have a track record. But when we’re attaching these new things to it, you’re attaching a very new, untested thing to these existing things. And it’s coming from a space. It wasn’t only built for financial advisors. It’s not a regulated entity.
Brad Johnson: So, you’re making me think of an issue here potentially. Schwab, Orion grew up in our space. Lots of protections that have to be put around your data. Claude serves a lot of different businesses. If I’m a hacker, I look for the easiest door to walk through, right, to get the data that I want. Well, however, these connectors, back to vetting the connectors, if it’s read/write back and forth, now I go to Claude, and it’s now connected to everything that runs my business. I sure better be positive there are no ways they can pull data, transfer, agents go rogue. I mean, we’ve already seen recent news from ChatGPT of rogue agents hacking other companies, right?
Quin Kilgore: And that’s another reason for the enterprise upgrade, is they have more authenticated use cases for users to get in, like single sign-on and other things like that, to make it more difficult for an outside party to access it.
Brad Johnson: What’s the price point, rough price point for a Claude Enterprise?
Quin Kilgore: I don’t even want to quote it. Like, it’s usage-based. That’s the tricky part.
Brad Johnson: So, it literally is, “Here’s the Lamborghini. You pay for however much gas you put in.”
Quin Kilgore: It’s kind of like going back to early cell phones when you had so many minutes every month.
Brad Johnson: Ooh. Well, that’s why I had nights and weekends at 9:00 PM, so I could call my high school girlfriend. It’s now my wife, so it worked out okay.
Quin Kilgore: There you go.
Brad Johnson: Cool. All right. Well, I don’t want this to be all doom and gloom. This is an early take. I mean, this is less than a full week old, but I did want to grab some time and put this out on the internet. Let’s finish up with: what are you most excited about when it comes to Claude for financial advisors? Let’s flip to the abundance mindset, the optimistic side of it, because we’re talking about here’s all the stuff you need to check and could go wrong, and make sure you’re good on. What are you most excited about, Quin, when it comes to Claude for financial advisors?
Quin Kilgore: I think the headline is think about agents running on Claude for financial advisors. So, you have autonomous agents running across all the connections that you have, performing work, so all you do as the human in the loop is go make sure that all the things that just happened, potentially overnight when you come in, is accurate and ready to go for the day. It can touch on portfolio drift. It can touch on all the transactions, which is the volume of the amount of data that you can surface to an advisor for them to look at before they even get their day started is going to be incredible, especially when they get agents involved. So, that’s what I’m most excited for, and we can’t be more than six months out from that.
Brad Johnson: Well, we’re doing a lot of work behind the scenes. Triad AI is a big thing we’re working on, and we’ve talked a lot about how does this impact that, and you’re like, well, it actually… Once we have this data, it accelerates how you can use it and how you can serve your clients, which is, at the end of the day, what our business is about. So, that’s very cool. Shannon, how about you? What are you most excited about?
Shannon McGinnis: I’m excited. Sorry. I think it’s actually going to give better output, more consistent output. People are different. People sometimes forget things. We get in a rush. If you can start using tools like this to systematize the data and the way it’s gathered every time, and it’ll also, I think, encourage firms to keep better records, update your CRM, right? So, we touched on that yesterday, too. But I think it’ll give better output, more consistent. Obviously, that presumes that you do have that human in the loop. But to Quin’s point, I think it lets a lot more people do things that they’re passionate about versus work that just takes a lot of time and can kind of be drudgery. So, I think it lets people use their unique skill set to deliver a better output to the end client.
Brad Johnson: Yeah. I think we’re approaching the point of end of manual data entry, which I don’t know too many people that get excited about that. I mean, if you think about it, if we’re speaking right now, if all of that could be captured, which obviously there’s a lot of tools out there today that do that, fed into your data, and then brought up for the use cases needed, we’re humans, we have biases, we have memories that we forget things, and now AI could truly make you a much better advisor, so you can actually do the human side of it and say, “Don’t forget to ask about Joey’s job interview that was brought up last time. That was really important.” Right?
And so, it actually, in a weird sort of way, can bring more of the human out in the actual meetings. So, that’s something we should all be excited about. Okay. Well, this has been fun. By the way, if you’re watching this out on YouTube, listening on audio, this is kind of the first time we’ve done a hot take on a… It’s kind of like the new iPhone 18 dropped. We’re doing our hot take in Finance Claude for financial advisors. So, if you like this, if you want more of it, please leave comments. Please let us know some other things you want us to take a look at, because it’s been fun. It’s been fun to geek out on tech and how it’s changing in finance. So, appreciate it, Quin.
Quin Kilgore: Yep.
Brad Johnson: Appreciate it, Shannon.
Shannon McGinnis: Yeah. Thank you.
Brad Johnson: All right.
