Is there a risk of buyer's remorse with AI?

0:12Damian Davies: Hello and welcome to the latest episode of the FT Advisor podcast with me, reporter Heriwood Mills. It would be hard to accuse the financial advice industry, or indeed FT Advisor, of speaking too little about artificial intelligence. But how does the hype of AI adoption compare to the reality? Are we witnessing a technological revolution or simply the next generation of productivity tools? And what should those in the advice business be doing to stay ahead of the curve? To help me answer those questions and more, we are joined by Damien Davies, founder and head of engagement at Outsource Power Planning Business at the Time Bank, and Peter McGahan, columnist and chief executive of Worldwide Financial Planning.

0:51Damian Davies: Thank you both for coming.

0:53Peter McGahan: Pleasure. Pleasure.

0:54Damian Davies: So Damien, we'll start with you. I know as an outsourced power planning business, you have the advantage of working with lots of different firms. What kind of AI adoption have you seen across the advice industry?

1:04Peter McGahan: I've seen a lot, actually, very widespread. It's quite encouraging how people have adopted it, definitely. I think some people are probably diving a bit headlong into some of the decisions. but what is really exciting is it's not just it's not just the sort of predictable parts of the business that people are using it for we've seen people obviously use it for you know meeting notes and things like that but also looking at their business so looking at processes looking at documentation you know kind of smaller businesses that may in the past have struggled to document their advice processes efficiently or effectively are being able to do that so yeah it's really widespread i think it's really encouraging and from a planner planner perspective where have you seen the biggest practical benefits um well being entirely selfish as a power planner i think uh meeting notes 100 because um the bit the bit that every advisor worries about is obviously if something goes wrong with a client down the line and a file gets raked over and in the past i think with client meetings where notes are taken even after the meeting um there's an element of interpretation gets put into that so it's not exactly what the client says whereas with meeting note takers number one it's not intruding into the fact finding meeting which is great you know you can sit and have a conversation a proper in-depth conversation with a client um but everything's recorded in their own words and for a power planner that's um that's massive because we're not trying to interpret what an advisor thinks a client said or anything like that so yeah for me meeting notes 100 and so come to you now peter are you seeing similar things and obviously on the advice side well i took a different view on ai

3:10Hereward Mills: and we started looking at the direct-to-consumer option for certain aspects of AI about five years ago. And more recently, about two years ago, when we looked at what we considered to be a kind of a staccato process, where instead of an end-to-end process, we had AI being plugged into different aspects of it, and we were of the view that that wouldn't work. And so we can see the AI note takers, and there's plenty of AI note takers there, and most of them won't survive because there's probably about 108 of them. And they won't survive, but also the cost of those will ramp up shortly. So we took a view to step back from that, and amazingly, we're going live in a couple of weeks' time with the end-to-end process because our view was it had to be built through native AI, and so that way by building it through native AI you could build a complete end-to-end process for every single decision that needs to be made and then of course every part of every process thereafter if you own the tech and you own the AI you can build any process for anything that you need to get done inside the business So back to you Damien

4:28Damian Davies: so when we spoke I think it was a couple months ago you said you saw one of the potential ways of these artificial intelligence developing was people using existing tools, ChatGPT, Claude, Copilot, maybe in preference to advisor-developed models.

4:49Peter McGahan: Is that still your view? Yeah, definitely. It's interesting what Peter says because I think when you're buying a product off the shelf, like AI agents, It feels like they're the kind of the method by which the old-fashioned kind of SaaS models of, you know, bits of kit that an advice firm might pay a license for and only use 10 % of its functionality. If you can build your own tool, it's quite easy to build some of these agents. If you can build your own tool and make it do exactly what you want it to do, which is based on your business specifically, then, yeah, I mean, that's a massive advantage for smaller firms.

5:38Peter McGahan: Yeah, it's definitely, I mean, I can't see any other way of it panning out. What Peter was saying there about, you know, the 108 note-taker tools, you know, there are. and if you adopt a note taker tool, you're restricted by however that company decides to teach its tool to format the notes. So, yeah, yeah.

6:03Damian Davies: And so is your view then slightly different, Peter? You want to, as you develop your own tool, do you see it more as companies developing their own tools, companies using tools that other advice firms have developed or using kind of widespread available models?

6:20Hereward Mills: I think it's very expensive to build your, because you've got a tech stack. I like to think of it as an octopus, AI is the octopus, and your tech stack is all these pieces of paper, everything that's across these desks right now, and each of those are different tasks that need to be done in an AI process. But if you own this tech, if you own an entire tech stack, and then your octopus, which is your AI with all the brains, touches each of them, you can make every single part of that tech stack talk to each other. For me to build that, that's not going to happen. That's millions. So the decision we made was to use an external provider to do that.

7:04Hereward Mills: There's a big danger in, you know, we can go on to Claude and we can ask Claude to go and build us different things and we feel great about that afterwards. But that's what I would call staccato processes. so that's just over there on its own. But what happens now when you want to put these five things into a process to get something done? I could take you through a process and say, we send an email to there, and then what happens with that when it comes back? Well, what would you do? What would you do after that? What would you do after that? Well, if you don't own the tech stack, you can't write that process out in an AI process with the prompts in between.

7:38Hereward Mills: But if you own the tech stack, you can just make sure that flows from beginning to end. but for me to ask Claude to go and build that I'd think it's very dangerous and I think a lot of

7:48Damian Davies: people find that but so so in your experience of financial advisors power planners people across the advice industry using AI do you think enough of them are using the term I hear is kind of holistic AI or do you think still people are still using you know they're using Claude here chat GPT there maybe something their firm provides and then they're kind of grouping it all together

8:09Hereward Mills: yes i think um i most of what i see is staccato but to be fair there is no end-to-end process fully in place yet so everybody has to be using the staccato process they have to be using the plugins but um it's just that's just a matter of time so to put you on the spot i mean matter

8:29Damian Davies: of time how long do you think before that starts kind of becoming a i think that's widespread i

8:34Hereward Mills: think that's i think we i could say that it's live probably within the month um i would say that that's live and because it's uh yeah i'd say it's live within the month for what we've been looking

8:46Damian Davies: at that's that's live within the month okay and so i'm always i'm always curious when i look at advice firms and everyone's speaking about ai it's all over the media um you go to any conference everyone's speaking about it's the kind of up and coming thing and some people seem to be getting really good returns from it some people maybe aren't getting the returns they see but then perhaps they feel compelled seeing other people speak so highly of it to make an effort to kind of tell people they are how much at the moment do you think we've got a kind of ai hype versus

9:18Hereward Mills: the reality of improvements um that would be a big diagonal line i'd say um but ai accentuates the user so if you know really good IFAs are just gonna just this is gonna be a party for them and because if you're very clever you'll know how to use AI to your advantage and because it accentuates the user so and creates extraordinary efficiencies not only efficiencies takes out chunks of work that shouldn't even be in there in the first place but it's a mindset AI isn't tech I don't consider it to be attack I consider it to be process I consider it to be a mindset or a paradigm. And if your paradigm is strong and you believe and understand it enough, that's mind-blowing, the time savings.

10:06Hereward Mills: I mean, mind-blowing.

10:08Damian Davies: So it's interesting you mention time savings. I think we'll come back to you, Damien. You know, when people speak about they've made productivity gains, how are you measuring that? Is there some sort of metric? How are you calculating hours? Or are you relying on kind of anecdotal body of evidence? Yeah, I mean, I haven't actually seen any evidence of or anything kind of concrete that demonstrates how people are using.

10:37Peter McGahan: I think the risk is a lot of people, like you just said, a lot of people look at the shiny and they get excited and they get some tools in because they think that they need to and they're worried everyone else is doing it. And they're doing it without actually working out what problem they want to solve first. so I think if you know what the problem is that you're trying to solve then you can measure how effective the tool is at actually achieving that which is all part of the process of of you know putting a piece of tech in place so I think yeah the clever firms that know what they're trying to achieve with a piece of tech will be able to measure that because they know where the problem is and what it needs to change to but there's a lot of hype i mean there's there's definitely a lot of hype on it and it's we're seeing a lot of um sort of buyers regret where people are buying into tools and being committed for a certain period of time and then thinking well it's not quite doing what i wanted it to do um because they probably didn't really know what they specifically wanted it to do just generically where they wanted to get to so yeah i'm not sure I'm not sure I'm seeing any measurable productivity gains, but I am seeing a lot of people with a sort of a wide-ranging satisfaction that let's say they want to put their processes through and map it or they want to put their CIP through and map it and have it in an easy format and something that would have taken 20 hours to do takes 10.

12:10Peter McGahan: That's great. That's fantastic. but yeah not not widespread at the moment definitely and so back to you Peter do you

12:17Damian Davies: have a way you measure productivity gains through AI and do you have a plan moving forward for

12:21Hereward Mills: kind of quantifying how you're making those gains yeah I've we have the implementation team in the company one of them is an actual project manager himself the other one is a lean management so there's three lean there's a lean management consultant inside there as well and as they've looked at what we're actually implementing right now, they're comfortable. In fact, Richard's view was, he said, I've got 75 % of my week back. Okay. And he doesn't miss anything.

12:56Damian Davies: It's funny you say that because I interview a lot of people who are launching their own tools and they seem to say 80%. I don't quite know how they've got to that.

13:06Hereward Mills: I think it could be closer to 90. Because when you understand it enough, you can then see it can do lots of other different things. But when Richard's telling me 75, I'll accept that.

13:19Damian Davies: And so obviously a lot of that time back is in administration. It's in tasks that you can effectively now automate. What's the next step for AI? What could be the thing that goes beyond that automation? Oh, now you get really excited.

13:37Hereward Mills: I think if you look at how an advisor adds value to a customer, we would be specialists in terms of our investment director is very skilled at investment research. So the speed at which he can get to customers now has just rocketed. And using good processes and a good RAP platform, the speed at which you can actually manage your customers' money, making sure everybody's in the right funds, making sure any changes that you need to make to a portfolio are done. I mean, that's a paradigm that you just wouldn't be able to have thought would have been done a couple of years ago. Now you can look at it and think, he can actually manage thousands of customers' money very, very quickly through a process where the customer is involved and is accepting the change, you wouldn't have been able to think through that paradigm before.

14:40Hereward Mills: So it's colossal change and improvements to customers' portfolios rather than advisors having to print out a big wad of stuff to go to see to a customer and change a portfolio, maybe five hours of work to change that portfolio when actually that portfolio should have been changed sometime before. and a lot of advisors are caught in that, which is unfortunate for them. But this is a completely different, absolute game changer because the speed at which you can now manage portfolios as bulk will rocket.

15:15Damian Davies: So is that going to put a premium on a different set of skills for financial advisors? Are they going to have to adapt to a new era of advice?

15:23Hereward Mills: I think actually if everyone on the podcast goes in and says, what can a financial advisor do, what can an independent finance advisor do that AI simply cannot? And it's going to come back with some really interesting answers. I did that for our admin team. It was really fascinating. It's interpersonal skills, adding values, nuances, communication. You'll be able to speak to a lot more customers, obviously, as well. But there's going to be a lot more time able to spend on the value-adding aspect of the relationship. I think that's fantastic because customers don't really understand a lot of financial advice.

16:08Hereward Mills: This is a real ability now to handhold, to communicate more, to talk and not only communicate verbally, but also be able to communicate quickly as far as your quarterly communications are concerned as well. Interesting.

16:24Peter McGahan: I've got to be honest, I couldn't agree more. I think it takes us back to the old skills rather than having to adapt new skills because what clients want is FaceTime. That's literally, when you look at all of the studies of what clients actually want, it's FaceTime with an advisor, it's reassurance. And, you know, how many advisors out there, the one thing that they enjoy is spending time with clients. So it seems nuts to me that these two things, there's so much that gets in the way of these two people that want to spend time together, you know, actually doing that.

17:01Hereward Mills: Just adding to that, we're putting into, there are nine emotional needs that every human being has. And if you look, if somebody wants to look up what are the human givens, you'll see what those human givens are. And one of them is attention, which is the need to give it and the need to receive it, which is a form of nutrition. and here we have it. Here we have it. Before I couldn't spend any time with you, now I actually can give you the time. I can spend it wisely.

17:29Damian Davies: And do you think some of that comes back to reassurance in that not just in financial advice, but people often ask AI something and then they'll get an answer, but actually they want to look someone in the eye. They want to kind of have that conversation and if it's coming from a person, they believe it in the way that they question or doubt AI.

17:48Hereward Mills: Yeah, absolutely. I think most people should question AI. So, I mean, once again, I said it accentuates the user. And there's lots of people who thought they could manage their portfolios before. This is very dangerous for the consumer, really, really dangerous. Just as a quick example of it, 30 seconds, but I sat beside someone who was really confident and interested in using it. And I said, okay, can I just ask you a question? ChatGPT, type this in. Where did the 2 % inflation target come from? and they typed it in and they got the answer, which was Bank of England introduced it in, blah, blah, blah, blah, blah.

18:24Hereward Mills: And I said, okay, take that stage further, just turn that into a column and ask it to write in Peter McGann's style. And it did it and it looks like my style. And they said, well done. I said, right, ask it to create five different social media posts for that as well. Okay, now would you send those live? Bear in mind, you could automate all of that in an AI process. But I said, would you send that live? And he went, yes. And I said, it was invented in New Zealand, not the UK. And so you would have just exploded your business. So that's the important distinction to make. A chat GBT is not a search engine.

19:03Hereward Mills: You do need to be bright to use it, or AI per se.

19:08Damian Davies: That's a good segue, actually, because I was looking to discuss, because obviously everyone's discussing the opportunities, but when it comes to the risks, there are lots of risks. So coming to you, Damien, what do you see the risks as? Or is it all ups, guys?

19:24Peter McGahan: Well, I think the risk is always going to be, you know, the fact that you can't leave this thing unfettered. You know, it's got to be supervised. It's whatever format it takes, whatever proprietary system that's used, you know how many how many times have you you put something through it and had an output that you know is wrong and you've asked it does this look right and he goes oh no you you i can see i've made a mistake there and that oversight becomes a skill in itself um and potentially that's where that's where people people can kind of you know they say that this is going to take a load of jobs or it's actually going to create a load of jobs as well um so yeah i think i think the risk we're all aware of the data risk 100 and i think that people actually take that data risk a bit too lightly and and um probably need to look at that quite closely but just in practical terms the actual application you know the fact that it will make stuff up um it will make mistakes

20:30Damian Davies: it needs oversight could you elaborate a little more on on what you think the data security risks

20:35Peter McGahan: are oh well they're everywhere i mean it's such a deep it's such a deep well um you know these these companies uh you've got the the way they're using their data the way they're teaching their tools you know this is very very privileged information um the amount of times that you know we get engaged by a potential client and and they ask us very important questions about gdpr and and and all the rest of it but you're you you don't have that same you know people assume that because it's a piece of kit that's been packaged for a financial advice business that the the the safety is already inbuilt and um it's just not it's just it's such a huge minefield um where the data goes how it's used um it's it's it's a privilege that an advice business has to be responsible for that data so it's got to take that responsibility seriously um even even down to you know doing a data protection impact assessment every time you use a piece of a piece of this kit you've got to you've got to be considering that so it's just it's enormous it is very big one of the things that we're starting to do now is um due diligence on these so for years we've been doing you know due diligence on investment funds and platforms and all the rest of it and we're starting to do it now on these on these tools just purely because you know each firm is up to them to make their decision as to whether they use these tools and how they use them but they need to know the risks so we're doing that we're we're going out and saying look this is where the data goes this is this is how it's used you just need to be aware of it what what you do with that

22:20Damian Davies: information is up to you interesting so it's a peter we'll come back to you is it potentially another danger, I think especially among younger power planners, people who are training, is that they become more reliant on using technology and maybe they become less technically proficient.

22:36Hereward Mills: You mean that in terms of their ability to give financial advice? Yeah. They shouldn't unless you have really I'd really be uncomfortable with anyone using ChatTBT or even Claude or any of those to give financial advice. It's not accurate. I've seen it firsthand unless you've customised, because it's only really ChatGPT that allows you to customise a GPT, so you can give it the knowledge bank to communicate to, but also you can give it the instructions as to how to interact. So unless someone's customised a GPT, they shouldn't be using ChatGPT for pulling out advice because ChatGPT is a little Labrador.

23:19Hereward Mills: It just goes off and gets the ball for you. That's all it does. and it says, well done for throwing that ball, by the way, and here's your ball back. That's dangerous because if you actually understand how those large language models create their answer, you'll realise the risks in every section of the process will give you that, some people call it a hallucination, I'll just call it the wrong answer. And then you go, no, no, that's not right, and then you focus it in further, focus it in further, focus it in further. So unless you've written an outstanding prompt or you've customised the GPT, you shouldn't be relying on it.

23:53Damian Davies: so how do you protect against that in your firm do you training have you got a kind of AI lead how are you making sure that people are using it appropriately

24:01Hereward Mills: yeah so what you would this is where we talked before about what is AI and so if we think of it AI as a customisation so what I would do there is I would personally customise the GPT so I will write that I will give it the PhD papers to read and say only refer to those so I'll give it clear instructions and then therefore we can rely upon it. And we have a trained compliance module as well that talks to all the right places in order to check it. So that bit's allowed, but it has to be led by somebody who understands it. But the separate part is the AI processing we've talked about before, which has nothing to do with that.

24:42Damian Davies: So Damien, do you have an AI lead as well at the Time Bank?

24:47Peter McGahan: Yeah, well, we've got... Ours is a slightly more complicated situation because we've got our own business where we're using AI, but then we've also got our clients' businesses that we're working in where they may use different AI tools. So each of our lead power planners that are working with our clients are obviously getting familiar with their tools that those firms are using and how they're using them. And then we internally have got the different tools that we're using. So we're using them at different levels. So kind of like tactically for the work that we're doing, but then strategically as a business as well.

25:21Peter McGahan: So, yeah, it depends on we don't have an individual lead. We've got leads that are dealing with specific projects. um so our phone systems for example we're changing our phone systems and we're building ai into those to to monitor the the quality of the calls that we have with our clients and the quality of the calls that we have with with providers to make sure that we're you know asking the right questions and it's just picking up things like um you know training needs and stuff like that so yeah each individual use has got its own kind of mini lead we're quite a we're quite a sort of a heuristic business in in that sense and in terms of how ai the implementation

26:03Damian Davies: of ai is going to impact financial advice specifically who's giving financial advice is this going to help larger firms who've you've got the kind of infrastructure and the kind of manpower to to really fully go in on implementation or is it actually going to help smaller advice firms who who can now take out some of that automation or is it going to help both

26:23Hereward Mills: Yeah, both. It will help both. There will be an end-to-end direct-to-consumer option that is due to go live shortly also, and I'm comfortable with it. That bit's easy, believe it or not. The actual giving of financial advice using a piece of AI, that's the easy bit. So that will take out a lot of those customers who were afraid to go to see a financial advisor. You see some grey-haired guy with glasses and think it's intimidating. I don't want to go near him, but they can go and take themselves through a process.

27:01Hereward Mills: So it'll suit the smaller firms as well because those customers are difficult to deal with from a cost perspective. They don't want to pay those sorts of fees because they just want to do a£15 a month ISA. They don't want to pay the fee of the finance advisors or they might be intimidated in the first place. So it doesn't matter what the size of the firm is. and then the AI process that I talk about in terms of the back end, the octopus that I referred to earlier on, well, it doesn't matter the size of a firm because the efficiencies are equal. So if you were an independent financial advisor

27:36Damian Davies: or running a very small advice business, what would you be advising those advisors to do? What would you be saying they should be looking at implementing right now?

27:49Hereward Mills: Shall I give you the name of the firm? Well, I mean, Nengi is the only AI tech in the world that has the tech stack with the AI over the top of it. Didn't want to go quite to the market, so we were going to implement AI processes about 18 months ago, and we decided not to because we thought they're just, that's bulldoins, that's plugins onto a camel. you know so it's just making the camel go faster but it actually isn't the end to end process so but ningi is where i would tell people to go and have a look because it has got that end-to-end process i was very patient because i actually had to sit there and watch all these ai note tickers flying in and lots of other different bits been plugged in just been plugged in you know just add-ins into different um different things and i look at those and i think well that's a fragmented fragmented tech stack and what's going to happen is you get you're going to get used to that you're and you get a lot of material on there, and then those costs are now going to start to rise.

28:50Hereward Mills: And where are you? So I made the decision just to be patient and focus and work with Ningi to say, this is actually what I want out of the other side. So they are the only firm in the world right now with that tech stack, with the AI process written over the top of it.

29:06Damian Davies: So as part of my reporting role, I cover a lot of AI launches, and it feels like there's been basically one a week since I've joined NFT Advisor. and so it's a very fragmented market at the moment. Do you see that consolidating in the way that, I'd say, smartphones, for example, that used to be a lot, and now it's a couple of providers?

29:28Hereward Mills: I don't know how it's going to, how you could consolidate something when there was, I'd say, all those individual pieces of tech to get this customer's journey from here to here. If you look at all the different things that are involved in that.

29:45Damian Davies: my question's been poorly phrased there I'm talking more that there are a lot of providers at the moment, well eventually do you think two or three of those win out or it's not economically viable for everyone to be doing the same product

29:57Hereward Mills: I think it's a bloodbath those AI note takers, very few of them will survive, fees will go up it'll focus the advisor's mind when those fees start to go up because AI can't run at the price it currently runs at but the prices will go up and I think whenever your full end-to-end process drops in there's lots of companies just won't be able to survive through that

30:23Damian Davies: Okay, well we are running out of time in a little bit so I'll come to you finally Damien if you could get your crystal ball out how do you see to the industry power planning, financial advice developing in the next five years?

30:38Peter McGahan: well um i'm going to try not to make too much of a prediction that i can be proven wrong but i think i think i can't see it changing a huge amount in in terms of you know structurally i think the one thing that's going to come out of all of this is the client experience i i hope the one thing that comes out of it all is an improved client experience because there's a lot of people out there who don't get advice for whatever reason. And it might be that they don't have enough money or they're intimidated or they speak to their mates or whatever it ultimately is. And actually, we all know that people get a better outcome from speaking to advisors.

31:20So if more

31:22Peter McGahan: people can get access to advice, that's going to be a fantastic outcome. If that experience is a good one, then that's going to be fantastic. And also, I think that for advisors, I think perhaps the evolution that we could go through is going back in time a little bit and looking at the old skills, looking at fact-finding, you know, proper fact-finding, actually understanding clients' motivations for why they're speaking to an advisor in the first place. No client ever went to an advisor to consolidate their pensions, you know, no one says that. But they're worried about something or they want to achieve something.

31:54Peter McGahan: So that's probably what I'd like to see happen over the next five years. Thank you, Damien. I'm like a hippie though, don't I?

32:02Damian Davies: and uh peter finally for you how do you see evolving the next five years um

32:12Hereward Mills: i there are so many once your paradigm is widened and the more and the more you do something the more your paradigm widens and widens and widens then you'll be able to think here's a process where i say want to do a comparison for your pension or ISA transfer. If I break that process down, and just use that one process as an example, I break that process down, which I won't do, let's just say there's eight processes writing off to a provider, asking them for some information. Well, I'll ask the AI to send the email. I'll ask the AI to check the email when it comes back. Then I'll put a prompt in between that, and I'll ask it to run through an illustration, and then I'll put a prompt to say, when you get that, compare that to that.

32:56Hereward Mills: When I ask it to do that, in Alaska to do the suitability letter report to a customer. So what could start with an email could end up with a report on your desk for the customer, and you didn't touch it. As long as your processes were all in there, as long as your tech stack is in there, as long as your research and all your information is in there, you probably could have touched that once. And that mindset and increasing your paradigms to think that every process that you've got outside your business could be automated from beginning to end, because it should be, really, with a human view right at the end or where there needs to be.

33:30Hereward Mills: I just think that is so exciting. And I'll echo what Damien said a few seconds ago. This gives you a chance to take your time with your people and make them feel special and go through what you need to go through with them and then let all the inefficient processes just float away.

33:45Damian Davies: Well, that's a nice note to you, a nice note of agreement to end on. It's certainly given me plenty to think about and I hope it's given our listeners plenty to think about as well. Thank you both for coming in. This has been the FT Advisor podcast. Thank you for listening.

34:17Peter McGahan: Parles-tu français?

34:18Damian Davies: Hablas espanol?

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