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The Advisor Delta™ is your essential guide to mastering the wealth management industry. Hosted by Worldsource Wealth Management, this podcast delivers expert advice, actionable insights, and innovative strategies to grow and elevate your practice.
Join industry leaders for interviews, thought-provoking roundtables, and quick-fire 'Ask Me Anything' Q&A sessions, as we cover everything from emerging trends to leadership development. The Advisor Delta™ is more than just a podcast—it's a partner in your success. We aim to provide high-value industry insights while building a community of like-minded professionals who can learn from each other’s’ experiences.
Start listening today and unlock the tools, strategies, and inspiration you need to elevate your wealth practice with The Advisor Delta™. For more episodes and insights, don’t forget to subscribe and visit us at www.worldsourcewealth.com. And remember, together, we can take your practice to the NextLevel™.
Narrator: Welcome to The Advisor Delta™, the practice management podcast dedicated to helping investment advisors grow their business and reach their goals. Whether you’re looking to scale your practice, streamline operations, adapt to emerging technology, or deliver value to clients - this is the place for actionable insights, thoughtful leadership and innovative strategies. Brought to you by Worldsource Wealth Management. Let’s dive in!
Ariel: Hey everybody, I'm Ariel Magil, Vice President of Practice Growth and Intelligence at Worldsource Wealth Management, and welcome back to The Advisor Delta. Now, for some advisors, AI has become a massive competitive advantage. Now for others, it's become an everyday productivity tool.
Ariel: But I would say for most of us, it's still one giant question mark. So the questions that seem to come up all the time are, what role should it play in an advisory practice? Where are the opportunities? What are the risks? And most importantly, how can advisors embrace these capabilities while preserving the client trust and fulfilling their obligations that are central to their practices?
Ariel: That is exactly the set of questions that we're here to explore today. Joining me is Cameron Schuler, Chief Commercialization Officer and Vice President, Industry Innovation at the Vector Institute, which is one of Canada's leading artificial intelligence research organizations. Cameron has spent years helping bridge the gap between breakthrough innovation and practical adoption, working with industry, research, and government leaders to turn emerging technology into real-world impact.
Ariel: I'm also joined by the inimitable Nat Morfesis, who is of course, Worldsource's Senior Vice President of Dealer Compliance and our Chief Compliance Officer, who will bring an important compliance and regulatory perspective.
Ariel: Together, we're gonna cut through the noise to explore what advisors need to know about integrating AI into their practices responsibly, effectively, and with confidence. Welcome, Cameron and Nat.
Nat: Thank you. Yes, thank you. Good
Cameron: to be back. Thank you for having me.
Ariel: It's our pleasure. So let's jump into the questions.
Ariel: Now, artificial intelligence has quickly become one of the most talked about technologies in business, but it's also a term that often is misunderstood or used as a catch-all. Now, to help set the stage for our conversation, Cameron, I'm hoping you can define what artificial intelligence actually is, and explain in practical terms what advisors should be thinking about when they hear the term AI.
Cameron: So AI, the meaning of it has changed over the years, so it is a very broad field. It is something that you would look at that is a learning system, so a system that is able to observe and then reiterate to get better over time without it being programmed explicitly to do so.
it is a broad suite of many different types of learning systems. And so when you think about AI, it is not any one particular methodology.
Cameron: Just think of it as a system that can learn or interact without it being specifically programmed to do so.
Ariel: Excellent. Now, Nat, if we look at from a regulatory perspective, and I know your team is all over this topic, would you say you would view it sort of in the same terms from a business standpoint?
Nat: I would...
Nat: It's a little different with a regulator. No one's gonna replace the sound investment advice from an actual advisor. AI is there as a tool, and the regulator has acknowledged and embraced artificial intelligence in a practice, but it comes with rules and guidelines. And one thing that we all wanna know: Is it the wave of the future?
Nat: Is it gonna replace the advisor? And I am very confident it will never replace an advisor. Just like self-serve online trading platforms. Mm-hmm. They were gonna take over. They didn't.
Ariel: That's right. I think, uh, there's room within the industry for everything, and certainly if we look at it that way, it's a benefit.
Ariel: Now, before we get further into the opportunities that AI presents, and I'm gonna not use artificial intelligence anymore 'cause I will for sure trip on it many times, let's start with trust, because that's something Nat just talked about. Advisors obviously handle highly sensitive information from clients every single day.
Ariel: What do they need to understand about transparency and client confidentiality when using AI?
Cameron: So it really depends what type of products they're going to be using. Mm. So you're gonna have products that are approved for your organization. Those are ones you should use within the guidelines that are set out.
Cameron: But if you take some of the available models, they actually will use your data for training. So what you put in there, somebody could actually extract at some point in the future. So it's pretty important not to put in any personally identifiable information or things that you could actually lead to a conclusion.
Cameron: So let's say somebody knew Cameron Schuler used a particular model. They could actually go in there and ask things like, "Is Cameron Schuler part of a member of something?" And actually look for my password and username. If I've ever put it in there, potentially they can get it out. So these are publicly available models.
Cameron: And so it's very important to make sure you do not put personal information in there.
Ariel: I don't know if you saw the look of terror in my eyes when you were talking there, but that's important information. Nat, what have you seen when it comes to that? I know you have a front row seat to how advisors are using that, and how critical privacy and all these other aspects are.
Nat: Cameron's after my heart, telling people not to put identifying information into an AI tool, and that is our greatest concern right now. So as a corporation, we've embraced AI. I won't say the name of the system we use. Oh. But we do use a very well-branded product out there. But as Cameron noted, it's private, it's confined.
Nat: It doesn't share our searches on the general web. So it learns only from the information that we put in it as a firm or as a very limited group of people.
Nat: Unfortunately, many advisors out there who use an AI tool will use your very basic web version, OpenAI. I'm afraid that what advisors are gonna do is put very private information out there or very client-identifying information, and that's what we don't allow.
Nat: You can change the client name to John. You can put what their holdings are. Don't put the account number associated with those holdings, and ask based on just the name and the holdings and your methodology of, for argument's sake, a 50/50 equity income split, what does AI recommend? That is okay 'cause you're not putting identifying information out into the world where hackers far more sophisticated than you are gonna exploit that information or identify clients.
Nat: So the biggest fear right now is understanding that any information you put into an AI module, it's accessible by everyone in the world when it's your general, I'm, I'm gonna throw out ChatGPT, Copilot, Claude, and God knows how many others that are available now. So don't do it unless you're putting very limited information.
Cameron: Let me add to that, actually. Please. So if you think about the value of a target, you're dealing with financial things. You're dealing with people's net worth. So there's an opportunity that somebody really wants that data. So there's some data you don't care about, but there's other data where, hey, this could be a multimillion-dollar account that's worth spending some time on trying to get our hands on it.
Cameron: And so there, it's really balances out that reward. And even if you see with traditional hacking methodologies— If there is a big enough prize, somebody will actually pursue it, and it might be the only attack that looks like that, but they build it specifically for that event. So don't make it easy, best practice is you have no control over it, so deal with it accordingly.
Ariel: I think we've all heard about the scams that are taking place on the phone, and so you know that some people are up to some really bad things, and they're very sophisticated, as you said. So this is something we should all be mindful of is who is on the other end of that discussion. Now, I would say there's quite a bit of pressure, certainly within the business community, I feel it, to embrace AI, to really avoid being left behind.
Ariel: Now, as advisors are looking at the different tools that are available to them, so whether it's this well-branded one that we have or any other one that we hear about, what are the most important questions that they should be asking about that tool to adopt it?
Cameron: So I think, so number one, we talked about things that are approved by the organization.
Cameron: That's your starting point. What can I use? And then the second part is why are you using it? So when you think about your objectives and what is the outcome you want, right technology for right outcome, and it really should be focused on what problem am I trying to solve? Why is this going to be better than existing methodologies?
Cameron: What are my outcomes going to be? And that's the focus. So if you think about it from a business planning perspective, it really is what is the outcome I want to get to and what is the technology that will facilitate that? That's what you need to care about. It's not AI is cool. It is. You can do fun things with it.
Cameron: I use it for lots of different things. When I'm writing code, it'll actually be my partner that I speak to 'cause I'll forget stuff, and so that is something that I find very helpful. So they're helpful tools. So you still, you still step back with what am I trying to accomplish? What is my outcome? And back to your comment earlier, Matt, about you don't think that advisors will be replaced by AI.
Cameron: I can agree with that because why do people actually give you money as an advisor? It is relationship based. It's the service you give people. It is the attention you give people. When something tragic happens and they need help, are you there for them? When something good happens, are you there for them?
Cameron: The relationship piece matters. So AI should be a tool to help enhance the things that we do to do them better, but ultimately it comes back to people deal with you because they like you.
Nat: I agree with you. I do wanna touch on one comment you made, and I think a lot of advisors do use it as a communication tool.
Nat: Write me a beautiful letter talking about the summer and send it to every one of my clients using the first names. They're gonna write this beautiful letter, and then they're inadvertently gonna allow AI 'cause it's quicker, it's easier to pre-print their 300 client letters addressed to each client individually, and they're gonna include the client's address.
Nat: And you're going, "Whoa, think about that." You've just exposed Cameron and Ariel and Nat and their address out to the world. It's just another hacking point, and I know it's public data. Like we all know Canada 411's on the internet Don't make it easier. You have a duty to protect that information. Protect it.
Nat: Let AI write the letter, but then export that letter into your own Word program that is protected on your computer. So just little things that people won't think about when they're doing it, and I love it. I also wanna bring up another point of the errors of AI, and you'll probably eventually ask about this, but I use it sometimes.
Nat: I'm not tech-savvy by any means. I needed some help writing a letter. I thought, "Eh, let's use this new thing that they've given me at work."
So I encourage advisors or anyone that uses AI not to always believe the results you're getting. I believe there's a term for that.
Cameron: Cameron? Yeah, so the models are actually designed to give you hallucinations. Let me explain what I mean by that. It is designed to give you a good answer, not a right answer, and that's not necessarily a bad thing.
Cameron: It's how they're wired and how they're created.
Ariel: I wanna dive into not just hallucinations, but we talked a little bit about the inaccuracies, but also bias. I've read at various points, like there's one AI tool that's promoted by one of the big tech names in the world, maybe the richest man in the world, whose AI tool seems to have a very peculiar approach to history.
Ariel: Are there other examples of that, and is that something that people who are using AI should be aware of, is inherent biases that are built into various AI tools?
Cameron: Yeah. So let me expand on that a bit. So the models themselves are not biased. The data that you use is biased, therefore it accentuates and actually magnifies the bias.
Cameron: That's the problem.
Ariel: Okay.
Cameron: So there was an example around hiring, and it was hiring programmers, and it popped up that they were hiring men because that's what they'd hired most of the time. So that is absolutely a bias because there's no magic of male, female, wherever you're from, that would make you a better programmer.
Cameron: And so as these tools become more sophisticated, there are methodologies to deal with these things, and so it really comes back to that human in the loop matters. And so you can't exclude yourself from the quality control that comes out of here. So that's why domain expertise still matters too.
Cameron: So you have probabilistic models. They're going to give you the most likely answer. So what's going on in the world today? And it also depends as time goes on. So it's not just what they're trained on, it's when they're a tuned model for a specific purpose, then what is it also trained on? So you start out with a model, you take any one of the foundation models, and it's trained on the universe of data that's available.
Cameron: From there, then you might say, "Okay, I want one that's specifically trained around a call center." So you then use something called retrieval-augmented generation, also known as RAG, that then informs that model as to the type of context you really want to extract it from. So there's different layers of, of proof and expertise you can bring into them that help you with that.
Cameron: Over time, these models will get better and better. They will never stop hallucinating, so you create a bunch of pieces in there that will help you deal with hallucinations. I know we'll talk about agents in a bit, but an example would be an agent that will actually go and check sources. As the technology becomes more sophisticated, a bunch of these things will go away, only because you create other things to deal with the problems.
Nat: That's where the fact that an advisor will never be replaced is reinforced for me because The vast majority of the human race out there is not as intelligent as Cameron is with AI— ...and won't be able to deploy these agents— No ...and fact check and they're just not that sophisticated. They're gonna rely on the human being—
Ariel: Absolutely
Nat: behind the keystrokes.
Cameron: Thank you for the flattering words.
Ariel: So we've talked about the promise of AI and greater efficiency. I think that's really, we can all agree that's how, in our industry, people have been viewing it. But in a regulated industry like ours is heavily regulated, speed obviously can't come at the expense of due diligence and taking good care.
Ariel: What does effective governance and oversight look like when selecting and using AI tools?
Nat: AI is complementary. I don't think it replaces. It complements your business. I don't think it increases efficiency by replacing the advisor. So there are several things that, uh, you need to keep in mind all the time.
Nat: You are the registrant. You can use AI to gather some information, fact gathering, if you wanna employ agents and verify that it's factual as opposed to hallucinations and the like, but you're still responsible to know your client. You're still responsible to know the product that is being recommended.
Nat: You can't just rely on AI to tell you that this fund or this stock is the next best thing, and here are 17 reasons why it is, which may or may not be accurate. You have to apply professional judgment. In many cases, you have a fiduciary responsibility to do so. You have to retain all your AI-generated communications for seven years, and your AI has to be supervised.
Nat: So there are several regulatory factors that you have to take into consideration, but going back to the first two, which are the most important factors, is AI doesn't know your client. You can feed it some basic information, but they don't know the person. They don't know their likes and dislikes. They don't know whether or not their primary goal is truly to save for their kids' education or to take that vacation at the end of the year.
Nat: I know that's a lot of information to start plugging into an AI for the average advisor. You wouldn't do that. So you know your client, and you know how they tick, where a computer program won't. I don't believe that bots are gonna replace humans. And with respect to knowing the product, again, there's a lot of fact.
Nat: Uh, AI's not gonna read the
Nat: quarterly reports or annual reports issued by a company. It's just not gonna get into that depth. It's your responsibility as the advisor to know the product and to compare the product against other similar products. So if you're going to create a prompt that's gonna have all that information in it, almost 100% of the time, you're putting way too much personal and private client information into AI, and you should stop, 'cause that is just way too much detail to provide into an open source system. That being said, any response from your AI has to be fact-checked, validated, compared by the advisor themselves.
Nat: The liability and the responsibility still falls to the advisor, and we shouldn't forget that.
Cameron: I wanna add to that, actually, as an advisor, are you adding more value than AI can? Figure out where your value is and magnify it. You haven't built a book because you're not capable. If building a book of business is hard, you have to get people's trust.
Cameron: They're multi-decade relationships in a lot of cases. And so how do you actually ensure that you are providing more value than technology can? And that's the thing you need to leverage. So I think a good example about technology not replacing people. So a number of years ago, somewhere between 2010 and 2015, a lot of the trading houses or investment banks got rid of their fixed income desks.
Cameron: They felt, you know, we can automate this fairly well. Maybe we don't need the people. So they did, and within about 18 months they said, "Hey, wait a minute. Where did all our clients go?" And so when you start thinking about that, what is your value add? It is relationship. It is what you bring to the table, the ideas you bring, things like that.
Cameron: You certainly need to remember that it really is human to human, and I think that's a good example of where technology did not replace people. On the trading side, absolutely, but on the actual interface with clients, clearly it wasn't executed well. It didn't work.
Ariel: We talk a lot about the value of advice in practice management, and it's been quantified, and so one of the major components of that is behavioral coaching, which conceivably could be done by AI.
Ariel: But really, you're not talking about somebody who knows the individual that's sitting across from you. So you're absolutely right. There is no way that they'll be able to get that kind of value from a robot ever. So it should give everybody some comfort.
Nat: I'll add to yours.
Ariel: Okay.
Nat: If as an advisor you're getting all your data off AI— Do you really think your clients aren't gonna get the same results by asking the same questions?
Nat: So where is your value? You're right. If your client can create a prompt that's very similar to yours about their own personal situation, and you're strictly relying on the AI output, you're not gonna look very bright when they come to the same conclusions through their own prompts. So again, your value add.
Ariel: That's a very timely piece of advice, especially with CRM3 coming down the pipe. They're gonna be like, "Am I spending $10,000 a year on something that I can just do on my own?" That's really valuable. One thing that we're starting to look at AI in the context of some of the tools that our advisors use, and one of the things I've been hearing about is where the data gets stored.
Ariel: Can you tell us a little bit more about that and why that should be a consideration when you're looking at AI tools?
Cameron: So a lot of conversation around sovereign AI, and there are certainly cases where big tech companies have said in a court of law that, "If my government asked me to divulge this information and it's in a foreign country, I will do that because I'm domiciled in the United States."
Cameron: That's a real thing. And so sovereign AI is a much broader conversation. When you think of all different facets, it's where does the data reside? Whose data is it? Because those are two different questions, right?
Cameron: So I think you should use AI, and I think you should use a lot of AI. I don't think that's surprising— Mm-hmm ...coming out of my mouth. But you can't defer your responsibility just 'cause there's an AI, and we've heard that multiple times from that. And so when you think about that, the organization that you work for or that you partner with has gone through and said, "We've evaluated these tools, and we are comfortable that you can use these."
Cameron: You've gone through a process to evaluate and say, "These are things that are acceptable for use." And that's really where that risk profile comes in. Because as soon as you accept a product, you've actually accepted their governance. And when you start getting asked by regulators, "What's your governance structure?"
Cameron: "Well, we deferred it all to somebody else," is not the right answer. The answer would be, "We spent time looking at it. We evaluated it based on these measures, and therefore we are comfortable using this product." So I think that's a pretty important piece.
Nat: And I'll, I'll expand on that be— I agree with you.
Nat: Use what's approved. Unfortunately, we can't review every single agent that's inputted into an AI system, so that's where common sense needs to come into play. Don't put multi-identifying information about clients into an AI open source system. And again, remember, everyone out there is having access to this information.
Nat: Somebody smart, I'm gonna compliment Cameron again, the Camerons of the world are gonna go out there and they're gonna know that Ariel put this agent in. Here's a list of his clients. They're gonna know where you work, and it's easy to find out where you're licensed, who you work for, and the general vicinity of your clients.
Nat: Yeah. And I'm sure there's an agent out there that's gonna say, "Here's a list of people that live at these addresses or in this province. Give me their phone numbers." 'Cause that's all information on the web.
Cameron: So I wanna expand on PII a bit, 'cause we talk about name and address, but let's talk about vocation You're a veterinarian in Sylvan Lake, Alberta.
Cameron: I have no idea if there are any there, but if there's only one or two, you now have identified that person even though you haven't used their name. So it's that convergence of data to find something. It's not just the name, it's how can you use information to find a thing, and how do you take these pieces and build a story around it?
Cameron: So again, veterinarian, Sylvan Lake, Alberta, and you start putting portfolio information in. You have a lot of information, you can probably find that person. Or it could be a lawyer, a dentist or a doctor, whatever else. And high net worth people you're dealing with are going to be business owners or whatever the case may be, or people that are professionals are gonna make up a portion of your portfolio or your book of business.
Cameron: So ultimately you can take that and assemble more information than you think you're giving.
Nat: I agree with you, and I guess that's where people also forget it's not limited. AI keeps remembering what's been asked of it. So if you're putting client first name in and their portfolio holdings, and you're asking for a rebalancing into something else, very limited, nothing identifying clients there.
Nat: A month later, you do another agent and you say, "Here's a list of my clients' first name, last name, address." There's another agent you've written. Now there's two pieces of identifying information. Actually three, if we go back to the original agent that had their holdings. Don't forget, it remembers everything.
Nat: Eventually, somebody very smart out there is gonna put all those pieces of information together, like Cameron said, and say, "Hey, identify all lawyers for me that live in northern Ontario where the population is 1,000 combined," and now you have wonderful targets for fraud and misappropriation.
Ariel: Absolutely.
Ariel: And as you referred to earlier, Cameron, the, the impact of the target, it could be so rich, just one deal can net them a lot of money. So clearly they'll put a lot of effort into that one. And so that's a really important thing to consider, is that sort of that memory and being able to piece things together over time.
Ariel: Now, the reality that we face right now is that many advisors hopefully are using AI in some capacity in their practice. From your perspective, and I think th- this would be asked of both of you, what does a well-designed compliant workflow look like? And is there an area where advisors and their teams can use these workflows that provide more value without creating unnecessary risk?
Cameron: So if you think what AI is good at, AI is good at summarizing things. AI is good at writing things So when you start thinking about communication to your client, you can put a few prompts in there to get your general piece, your paragraphs you want, and then from there you can then modify it for that client.
Cameron: So when you think about time-saving, it's a real thing. Our marketing and communications team, we adopted a product a few years ago, and they saved on average seven hours a week. That's meaningful, right? And especially in a business like this that is a volume-based business. So it's not trading dollars for hours, right?
Cameron: It is something that the bigger your book is, the better off you're going to be as an advisor.
Cameron: And so when you start thinking about how you use those things, think about what the tools are good at and then how you might use it. And certainly ask other advisors, "What are you doing with this that you're getting value out of it?" I mean, ultimately it just comes down to the common sense interviewing and the human in the loop component.
Nat: It's perfect advice. Use it to save time, use it to make yourself sound smarter, sweeter, kinder, whatever it is you wanna get in the end. You don't necessarily have to use it to its full capacity or full potential. The full potential is what could get you in trouble over the long term. So write those client greeting cards.
Nat: Write, write your position paper, but give AI the prompts with what you wanna say about a certain security or a certain fund. There are ways to incorporate AI, and we do encourage it. What I'm not encouraging is inputting sensitive data that could eventually be used for inappropriate things and exposing yourself as an advisor and your firm to liability.
Nat: You need to be very cautious with what you're putting in, and remember that it's always cumulative information. It's not a one-off agent that you're running. This beast, if I can call AI that, is gonna remember it, and it's gonna grow and get smarter and bigger. But if I leave you with anything, it's going to be that AI is not gonna replace the advisor or the personal touch that an advisor gives a client.
Nat: As Cameron said at the beginning of this episode, it's about the relationship. And with respect to the advisor, it doesn't replace your responsibility to know your client, know your product, and follow due diligence set by your firm.
Ariel: That makes sense. One of the things that crossed my mind when I asked that question, as a practice management professional, we always talk about process and workflows.
Ariel: AI could conceivably develop processes that you can use in the practice to make it run more efficiently, and I think that would probably be a fairly safe thing to do because you're not entering anything that could be used later to create harm, and it would make my job easier, too. So I encourage everybody to start doing that.
Cameron: Yeah, I think your question earlier was about workflows. So between all the information I get every day, I could spend hours a day just trying to keep up. It's a pretty good use for AI to say, "Aggregate this, give me summaries of it," and then I can determine what I wanna read more of.
Cameron: 'Cause some stuff is just interesting, so I'm going to read it 'cause it's interesting. But other stuff is going to be far more targeted to my thought process and my personal investing process. How do I focus on this thing that I am pursuing? And if I'm thinking of global macro and I want an opinion on that, it can help me actually formulate that.
Cameron: There's not a lot of risk in this in terms of there isn't PII in it. It's informing me. I'm still gonna have to do the work behind it, but it's going to make me more efficient. And so those are the types of things that you wanna focus on. How do I become more efficient? How do I actually manage my time better?
Cameron: That sort of stuff.
Cameron: You think about all those efficiencies you can get out of it. Again, it would bring me back to what other value adds would I use with that time? What other things would I do with that time? And it's either growing my business, if I was an advisor, or it'll be things like that, or more spare time or work-life balance, whatever it might be.
Cameron: But it doesn't have to be PII. It can be many, many other things. So be inventive, try a lot of stuff, and just use a few smart guardrails with it
Ariel: I like that. I like that last line especially. Now, any avid listeners of the Advisor Delta podcast, including Nat, knows that we like to close with one final thought.
Ariel: And so I'd like to ask you, Cameron, when you think about one's mindset or assumptions around AI as it relates to our industry, what is one of those that you would challenge them to reconsider?
Cameron: So one of the researchers I used to work with solved heads-up limit poker, and so he was invited to speak to a bunch of hedge funds, and these are biggest in the world.
Cameron: They would have these quarterly dinners around the world where they'd invite an interesting speaker, and everyone in the room wasn't thinking, "How do you use AI to beat everyone else in the room?" It was, "How do I not lose my job?" So let's focus on the thing you can do with it because ultimately it goes back to if AI is better than you, figure out what you're good at and continue to focus on that.
Cameron: You can look at it and be somewhat afraid of it, or you can look at it and embrace it and see how it actually makes things better, and I would encourage the latter.
Ariel: I like that. Glass half full or a variation of that. Nat?
Nat: Embrace it. Absolutely. Make it complement what you do and the services you provide.
Nat: Don't train it to think for you. Just train it to gather facts for you. And don't always believe that the facts are actual facts. They might be fiction. We talked about hallucinations. Hmm. Test it. Look it up. Do your own research. And remember, you don't wanna let it do the work for you 'cause your client might be asking the same question and get the same result, and then they might question whether or not you're the right person for them.
Nat: It's the relationship. Keep the relationship strong and use AI to just make things more efficient in your practice, not do your work for you.
Ariel: Certainly, one of the lines you just stated about using AI to complement the work that you do, I think for me is the biggest takeaway amongst many takeaways from this conversation today.
Ariel: So that is very, very valuable. Cameron, Nat, I thank you very much for sharing your thoughts on this. It's been a really interesting conversation.
Cameron: Thank you for the invite.
Nat: Thanks for having me. Look forward to the next episode.
Ariel: Excellent. Now, we've covered a lot of ground, from privacy, transparency, to governance, and of course, the realities of adopting AI in our very regulated industry.
Ariel: But if there's one takeaway, it's that AI doesn't replace any advisor. If anything, it truly raises the bar. It challenges advisors to think more critically, ask better questions, and apply even greater judgment in the service of their clients. After all, and Cameron, you stated this very eloquently, clients don't place their trust in your technology, they place it in you as the advisor, and that trust, accountability, and professional expertise remain at the heart of every client relationship, and it always will.
Ariel: Thank you very much for joining us on The Advisor Delta today, and until next time.
Narrator: Thanks for tuning into The Advisor Delta™! We hope you found today’s episode valuable to supporting your practice. For more episodes and insights, don’t forget to subscribe and visit us at www.worldsourcewealth.com. And remember, together, we can take your practice to the NextLevel™.
The views and opinions expressed in this podcast are those of the participants only. This podcast is for informational purposes only and does not constitute financial, legal, or professional advice. Listeners are encouraged to seek professional guidance for their specific needs. Worldsource Wealth Management does not endorse any products, services, or companies mentioned in this episode.
Worldsource Financial Management Inc. is a mutual fund dealer. Worldsource Wealth Management Inc. is a dual-registered firm, both as a mutual fund dealer and an investment dealer. Both Worldsource Financial Management Inc. and Worldsource Wealth Management Inc. are members of the Canadian Investor Protection Fund (CIPF) and the Canadian Investment Regulatory Organization (CIRO) and subsidiaries of Worldsource Group of Companies Inc., a wholly owned indirect subsidiary of the Fédération des caisses Desjardins du Québec (FCDQ), which is part of the Desjardins Group.