Join Heather Hopkins and Alasdair Walker at Handford Aitkenhead & Walker as they explore the transformative impact of AI on financial advisory firms. Discover how industry leaders are integrating AI into their practices and preparing for the future.

In our Season 5 finale, we welcome Nick Eatock, CEO of intelliflo. Nick shares insights on how intelliflo leverages AI and his approach to integrating it within the business. Tune in for an insightful conversation on innovation and the future of AI in financial technology!

Transcript — 

Disclaimer: This transcript was produced with the assistance of AI, so it may contain errors or inaccuracies.

00:05

Heather. Hey, welcome back to NextWealth insights. My name is Heather Hopkins, Founder and Managing Director of NextWealth. I’m joined by my co host, Alistair Walker, Managing Director of optimum path financial planning and a Chartered Financial Planner. Hello, Alistair, and great to be able to introduce you with your new company name. Hi, Hera, thank you. Great to be back for episode eight, which is our final episode of this season. Bittersweet for me, because I’ve really enjoyed making it with you. And thanks for Thanks for remembering the new company name. Yeah, we just recently, recently changed, so in a bit of a transition there. And so yeah, this is the last podcast of the season, and the last companion podcast to the AI Lab membership group for now, at least along the humans. I’m really excited about speaking with today’s guest who I’m sure you’re introducing the set for us, Heather. But before we dive in, of course, none of this would be possible without our sponsors. So thank you very much to Salesforce, ssnc, Aviva and fidelity. Over to you. Heather, to introduce today’s guest. Today’s guest will be no stranger to listeners nick it talk CEO at intelliflow. And in researching this, I went back to an article, an interview I did in 2017

01:19

with Nick, and it was one of my favorite because it was such an eye opener to Nick’s background as a video game designer. So Nick, welcome to the podcast. Very nice to be Hi Heather, hi Alistair. I must admit, you posted that on LinkedIn, I think, and I had another look, and it took it took me back. It was a great it was it was good fun interview. It was fun, and we’re delighted to be speaking with you today about AI, because intelliflow is one of the larger tech providers to financial advice firms, and this podcast series is all about how financial advice firms are integrating AI into their businesses. And so just to kick things off, I’d be really interested to hear a bit about your approach within intelliflow to using AI and thinking about how you’re using it in the business, but also within the products that you’re offering in the market. Yeah, I think, like most businesses, everyone’s on their different path with AI, and they’re exploring it or using it actively in different ways. And when I think about within our own business, we use it quite extensively, all the way through the development proper position itself, you know. So our development teams use AI to help them deliver better code. Essentially, it helps them get away again, get through that process. It takes out some of the perhaps more tedious aspects of coding and gets, gets you right to the cutting edge, to the bit. Do the bits that humans make a difference on? And I think that’s a kind of an important message about AI in general. It’s not, actually, we haven’t found that it is replaced people. It’s replaced some of the jobs that are perhaps

02:55

less meaningful. And actually, humans can make a difference on top of that, rather than be relegated to the side. We use it through onboarding process as well. AI is quite an interesting one, because I think generative AI gets all the headlines, and probably rightly so. It’s probably the more the more exciting bit of the elements. But there are other bits to it as well, you know. So RPA is a big part of AI in general, in terms of the family. So robotic process automation, and you can do it an incredible number of things with rpa, using multiple different systems. And it kind of gets you, if you’re using third party solutions that don’t use that don’t have strong APIs, RPA can be quite a good way of working with with those solutions. So we tend to use it in a in a range of different different methods, and then definitely machine learning and and, you know, interrogating data and so on. Is a. Is a is a core part of of how we run the business, how we look at our our what our teams do, what our customers do, what our users do, and so on. So machine learning is pretty, pretty important in terms of optimizing the business. And then, I guess, turning to the product, we kind of have a multi strategy there, really. One is that, you know, we want to continue we’ve always been an open architecture business.

04:11

Built the first main scale sort of API and store in the marketplace. And that’s that comes from a philosophical point of view, that advice firms should be able to choose the technology partners that they want. And it’s not just one partner. It may be maybe five or six, for example, and and therefore those partners should, should provide a means by which integrated solutions are a reality. So we follow exactly the same philosophy with with AI. There are maybe eight to 10 AI specific vendors in the marketplace at the moment, and we integrate with almost all of them, I think, and you know, and want to provide a way in which those firms can and then alongside that, we have our own AI agenda too. So we’re building lots of capability working with some of the perhaps.

05:00

Them are more of the more the global firms of Amazon, Microsoft, people like that, in terms of putting stuff together that’s going to sit within the product and and complement what other firms are doing too. So, you know, I think it’s interesting that the whole term an AI vendor, I think eventually is just going to go away, because all software vendors will use AI in some part within their offering. At the moment, it’s quite easy just to categorize, but I think that will all just disappear anyway. Is there anything that users, if in teleflow, might be using, but has some sort of AI processing, machine learning processing, in the background that we as users may not realize? So are there ways we’re interacting with system already that are being driven by that kind of by that kind of process and programming, more in terms of the stuff we’re doing internally Alistair, it’s more about our analytics and understanding what firms are doing. So we can optimize the solution to make sure it’s better in different ways. So we, when we evolve the solution, we get, we used to get feedback just from users and customers and on, you know, they can leave that on our community and and leave ideas. And we still do do all of that, but now we complement that with information that we’re getting directly back and using AI to interrogate and get a better understanding about how people are.

06:16

And very often it’s, you know, it just reinforces what users are telling us themselves. Sometimes it identifies some different things that people haven’t told us. And that’s probably the most interesting, interesting section. And sometimes it’s a little bit contradictory to what we’re hearing. So that that bit, I don’t know what we do with, but one thing that that I get from other advisors, users of your product, because, of course, you are, I believe, the biggest sort of back office CRM provider in the UK, is a feeling that they’d really like, if only this bit of tech that I’m using would interface properly. And I think there’s a case of kind of integrations and integrations. How deeply integrated are things? Can things post and write and rewrite and edit existing data on the system?

07:02

Do you? Do you get a feeling as a business, of pressure from users to to kind of really open up all of those bits that you may be a little bit more more cagey about letting you know some random new vendor open up with, yeah. So our general approach here is to try and make sure that as much of the system can be accessed as possible, but you do also, then, when you’re looking at specific vendors, have to be sure, from our perspective, that we’re not going to be opening up an area that someone may abuse in some way, which then compromises a firm’s client data. Because obviously that’s, you know, that’s not great at all. So there’s a there’s there’s a level of due diligence we have to do with all the vendors and partners who use use our store. We got about 130 odd people using 130 firms, rather using the the store and APIs now in terms of third parties. And so it’s really important that we understand who they are, what they do, and the due diligence we go through with any, what we call vendor or partner onboarding, to understand that at the same time, ultimately, the advice firm has to make a choice here too and understand where the data is, where the data is going. I think one of the interesting things with AI vendors, but in truth, it kind of applies to any vendors. It’s just more obvious with AI vendors is that there’s a range of third party tools that those AI vendors will be using themselves in order to provide their service. And that might be, that might just be one of, one of the big main, you know, open AI, or whoever it is behind the scenes, but it might be four or five. And I think, I think advice firms have to have to understand that too. It was very interesting at your session earlier this week on that, that whole approach, really, how does, how do advice firms understand how to do due diligence on, on, on AI vendors in particular. And it is, it’s definitely challenging. You know, it’s challenging for really big firms. And when you think of the average size of an advice firm in the UK, it’s not a big they’re not big firms, so they don’t have the wherewithal, the time or the knowledge necessarily, to be asking the right questions. So I do think that there’s something that needs to happen there to make it better. That’s a really interesting point. And yeah, we had Dominica suretska McCourt, who’s a due diligence expert, Speaker The AI live event that you attended this week as we were recording Nick and, you know, she, I think, had 77 questions that a firm should be asking a potential AI software provider. And it made me think there’s an old coaching question that says, how do people buy a car? What data do they use to buy a car? You know, you might think that’s miles per gallon or it’s safety ratings or whatever, and and the coaching answer is, no, they decide they like the car and then backfill with things that sound like they make sense. And I do wonder how much of that’s going on with us as.

10:00

Set of financial advisors. We see a cool bit of tech, and we go, right, how do we make this fit the model? And on due diligence, and on asking 77 questions, and on it needing to get better. It’s interesting. Actually, I wonder if there might be a role in the big players, thinking about in telephone as an example, actually sharing some of their own due diligence data, you know, I kind of have this idea that if the same 77 questions are being asked by 350 different firms, there must be a way to, you know, for us to kind of share and share alike and all get better. Any thoughts on that? Would that be a would that be too much like you choosing software providers for customers? Or, I I think there is a certain danger in that, that actually everyone ends up just relying on that when we are not a,

10:48

we’re not a standards body. And there are standards bodies out there, and I think, actually, for me, that that’s probably the way in which I think this may be best sorted, you know. So if you think of some of the some of the security and process standards people like ISO, ISO 27,001

11:04

in order to pass ISO 27,001

11:07

you have to go through a heck of a lot of time and effort to demonstrate this is what we do as a business. And here’s some examples that show you this is how we work.

11:18

I think that’s probably one of the questions I would ask of any vendor out there, so the one I hear, I mean, security is a big thing, right? And the thing that slightly frustrates me that I hear all the time is people saying, Are we being told that the vendor, and this isn’t necessarily just about AI, this could be anything, or any technology supplier, is they support end to end encryption. So things must be right?

11:43

That’s just like one part of the and probably the least worrying part of the whole process is what happens when the data gets at the other end, who? What other systems are being used? What’s the data flow? Understanding that in its entirety, that’s probably the more relevant set of questions. And how do people, human beings, within those vendors then operate with the data, and what are the Securities and controls and processes around that? Those are the things that actually probably matter more than the end. Not saying end to end. Encryption is not a good thing because, of course, it is, but it’s only one element of the the the overall defense, if you like. And if you go through an ISO process, or SOC two, or any of those, then you have to answer those questions as a vendor, you can’t sort of shy away from them. So having gone through that process is probably a pretty good barometer. The for you as an advice firm in terms of your in terms of your choice, that’s really interesting to hear. And is that classic case of of knowing what what good questions to ask are, and what good looks like in terms of answers. And so I think that’s really helpful. Thank you. Our security of chief security officer tells me all the time, he says, right, these are the new threats this week.

12:59

There are new threats around every single week. So actually, you you as a, as a, as an advice firm using tech, have to rely on the fact that actually the technology vendor has got processes, procedures, people and systems in place to make sure that they keep up to date with everything that’s happening and keep addressing that. It’s not a, yeah, this was done six years ago. And I’m sure it’s still fine, because it’s not going to necessarily be you need, you know. And ultimately, I think that becomes, comes as often these things do, you know, we buy things off, people fundamentally, and people within firms, yes, but people first, and you’ve got to believe that their their attitude to security and data is kind of, you know, the prime thing that they do, and then the functionality sits on top of that, but the foundations are strong in principle. I think it’s really,

13:50

it’s such an important topic, and it’s so fraught, isn’t it? And it’s in, you know, in our, our survey that we did last week was 20% of respondents from Survey of 200 financial advice professionals across the UK, nationally representative sample, 20% say their firms using AI. And one of the main reasons why was the nervousness the you know, how? How do you select a vendor that you can trust? Is it worth the risk? And

14:21

so 40% said that they’re not at all confident in being able to assess the suitability of AI tech providers, and 25% said that they’re only slightly comfortable in their ability to assess the suitability and and if you think you can rely on big tech providers, and then hear stories about, you know, hackings at meta, and, you know, all these massive firms, it’s, it does make people quite nervous, and then they question the reasons. So it’s it, it is really challenging, but, but I think that’s a good, a good segue into, you know, where, where can AI be used in advice for.

15:00

So I’d really, I’d really love your thoughts on this. You had a really interesting piece of research on your website, and I’ll include a link to it in the show notes, but it highlights some of the challenges of adopting AI. You mentioned the skills that you know, it’s not, it’s not the firm’s fault. You know, no one’s gonna have a CTO if they’ve got five people in the business right next to us, we don’t have a CTO. We’ve got 12 people in the firm. It’s, it’s just, it’s just, we don’t need that resource. But you know, in terms of the the opportunities for firms you mentioned in that article, efficiency, client journeys and data analytics, I just love to hear your thoughts about, you know what? What’s, what’s the problem we’re trying to solve? What’s the opportunity for advice firms with this technology? I think the opportunity is huge. And I think, yeah, I’m always excited the beginning of every new year in terms of what’s going to happen, what’s going to change. And I think, but over the last couple of years, AI promises probably more of a leap ahead than almost anything we’ve seen in the last 1015, years or or so, you know, you probably say the internet itself was the last big leap ahead, or the previous to that. And at the moment, I think if you look at what’s being used, there’s, there’s real value being applied to a small set of use cases in the marketplace by various technology vendors, and they’re doing a great job, you know, so that that’s good. But I think what we will see is we will start seeing AI enhanced capabilities, rather than just AI itself. AI enhanced capabilities flex their muscles and cover far more of the advice and advice process as a whole, you know, and that’s really important from a from a compliance process, you know, the more that is covered through a unified journey, the more likely you are to be able to demonstrate consistency. You know, health checks, audit, all of the kind of stuff you expect to do from a compliance process, which is just as important in a small business as it is in a large business, obviously, but then enhanced by elements of the AI to make it actually work more effectively. So I think that’s the some of the and I think some of that is about bringing some of the bits that we’ve seen various vendors do today, but into more of a cohesive journey. And some of it’s about additional stuff. So I think that’s really exciting. A lot of people have said, and rightly said, how important it is if you’re going to get good AI, you need good data first, because that, you know, one sort of is a dependency for the other, and that’s absolutely right. What I think is interesting is that actually there’s also the potential for systems, and we’re doing some great work with Amazon at the moment, with

17:35

a capability there’s called Amazon Q, which will release shortly to the marketplace is a capability that not only provides you with the ability to see dashboards and create dashboards and all of that kind of stuff, but also uses AI to help start interrogating them and asking you, enabling you to answer the questions in natural language that say, well, actually, okay, this is what the dashboard says. But I’d be quite interested to understand if this this and this is the case, or what can you tell me about this? And getting the tool sets to actually work as almost as your expert assistant sat behind you or beside you, with ultimate ability to do to respond to your question and actually do it pretty quickly as well. I think you’ve touched on something that that I’ve really started picking up on recently, which is that there is that magic moment where you realize that your life has been made easier with a piece of AI talking about having, you know, natural language conversations. A couple of weekends ago, as a project, I decided to enable chat GPT on my smart home equipment. So rather than, you know, asking Alexa to switch the light on, which is just really turning ourselves into the switch, right, your voice becomes a switch, rather than the light switch on the wall, what I can now say is, it’s a bit dark in here. And then it will say, Oh, I’ve switched a couple of lights on for you. Is that better? And then you’ll say, Oh, actually, it’s a bit too bright now, and so they’ll switch one light on, or take the brightness down to 50% and then, and it’s a conversation, and it’s weird, you’re talking to your home, but it’s, it is like, Oh, this is what the promise is when it works anyway. And that’s it. Every year, Alistair or not, every year, even every month that goes by, it has this continual because the Pro, because AI as a whole, is moving so rapidly, there’s something new that you discover, and you go, Oh my gosh, it can do that. It can do that, and that’s going to continue. And this, yeah, technology as a whole, in general, across, you know, across the planet, for the last 150 years or so. And when I say that, I don’t mean just IT technology, as we kind of refer it to today, but technology in its wider sense, has continually flourished and amazed people and enabled us to do things and continues to move faster than it did the decade before. And that’s we’re absolutely going to see that with AI now you don’t need a.

20:00

Fantastic data set, to be able to turn the lights up or down, but to be able to get a view in your business about, you know, the health of the of the business risks, etc, you need a really good set of data. And one of the challenges in our market is the quality of data within advice firms. And I met with the with somebody in a in a one of the bigger consolidators last week, who was absolutely delighted, because they’ve got 85% coverage on valuation and transaction level data for clients. And some would say, Well, you know, why? Why do you need that, really? But, but, you know, they’re owned by a PE firm, so they need to report to clients the the overall view of their relationship, their financial picture, right? So, so there’s that piece of it, there’s the client piece, which is critical, but there’s also they need to know, as a business, how much have we grown that’s organic versus market growth, versus existing clients, adding money so that they can report to their owners some of the key financial metrics, but with 85% coverage, which is fantastic. It’s still not giving them the full picture. And so, Nick, do you think that that providers in the market are doing enough to share data? Do you see progress there? Should they be doing more? Is there something that we can do to make that better? Yes, and I think, and I think it’s a kind of a wider subject than just the providers, actually, but yet, firstly, if we think, think about providers and the data that sits on platforms and so on, getting that data populated into, in our world, into practice management systems, because for an advisor, that’s where most of their data sits. So that creates a better environment for that to happen. There are APIs to support that, and we wholly, wholly support more and more data going through. We’ve addressed it in a slightly different way as well, with a partnership we created with a business called snowflake. Snowflakes, a global leader in data warehousing in general, one that we had probably, probably the best known company on the planet in that space, and what we do is we provide our data into there and allow firms to have access to that data, but also combine it with other third party data. So that might be that as you’ve got five data sets from different different places coming together, but you’ve got one place that you could put them into, and then have either a BI tool, or, if you’re really technical, just SQL queries applying against that, what effectively then becomes a single data set. So that’s another way of thinking about that. I think what the bit that often, and I was with a customer yesterday who echoed pretty much the same kind of thing you were saying, Heather there, but also reinforced it by just core data that they would expect to be in the practice management system. So salutes. So our solution, and it turned out that part of the reason why it wasn’t was because they were using some third parties for doing some stuff who just weren’t passing the data back as part of that. So actually, if you’re going to use third party solutions, make sure that the outputs of that, not just documents, but data too, are passed back into the solution, so that integration is really, really important.

23:11

And if you don’t do it that way, start using the inbuilt tools. You know, certainly, as you know, we’ve got a cash flow planning tool and just got 5000 users there now utilizing that solution all the time, and that means the data is there. So you’ve got two different routes about that kind of a best of breed and integrated parties, or doing more of it all in one system. And there’s no right or wrong answer in that. It’s a subjective choice based on beaches and functionality. But also integration is the key thing that you can’t forget, because if you don’t do that, you can’t empower the AI. That’s quite a nice opportunity to segue into an area where we perceive, at least in the UK, most of the AI and sort of tech development is happening. First, we know you’ve been spending quite a bit of time in the US, with us, advice firms, and I think there’s quite a common sort of consideration to look west when we’re thinking about how we might be adopting certain new tech trends. To be really interested to hear from your experiences. How do things compare? Ai wise, in the US or the UK? Is there anything that we could be learning to get a bit of an edge over our sort of other UK advice firms. Um, I think, I think the trends Alistair are fairly similar. And I would also say that the status is fairly similar in both countries. So I guess the key difference in the US is it naturally a much bigger place. And because of that, there are many, many more suppliers of technology. And those suppliers tend to do a niche element of the advice process. So when you look at the average US advice business, they tend to use technology for many more vendors than we might see here in the UK, and that’s because the technology that those vendors provide tends to do a smaller part of.

25:00

For the overall process. But what that means is that integration is really, really important, but doesn’t always apply. And so the integration levels aren’t necessarily way ahead of the UK by any by any stretch of the imagination, and I think that has created a challenge for the adoption of some of these AI solutions. So when I look at the AI solutions in the US, they are very targeted at the moment, at least around a specific need and a specific area of the advice process. And I think that’s good, because there’s loads of value that can be provided there, and those solutions are being adopted. But I think where it would have a maximum impact, and it’s the kind of thing I was referring to earlier, is when you think about the entire journey, that entire onboarding, advice and implementation journey, when you can get solutions empowered by AI to cover that whole piece, then you are in a really great place. That’s how, as a nation, turning back to the UK now. That’s how, in a UK sense, we do widen access to advice, because then we make the process much more efficient for a relatively small number of advisors, as we have here in the UK, which is hopefully growing, but not growing dramatically, to service a wider range of people. And I think that’s really super important. Ultimately, for me, that’s one of the promises that AI should help us deliver on. Yeah, I think that’s a really interesting point, and particularly interesting to hear that the firms in the US are using perhaps even more different pieces of software that we are the biggest piece of complaint I have, both within my own business, from employees and from other advisors I speak to is that, oh gosh, if only we didn’t have seven places we had to go to get this piece of information, and then we go to hear, you know, some stuff stored in one note, and some things are in Excel spreadsheets, and others are on a back office software and, and, and if only we could draw it all together. And for me, almost the promise is something that can, can, can do that using screen reading, machine learning. I think, I think Claude has just released a big update that promises to do some of that. But again, it’s the promise versus the delivery.

27:15

Also worry about things like terms of business being broken and, you know, those sorts of things, if you are using readers and any thoughts on that, have you had people using that sort of technology on in telephone? Has that caused an issue by definition? I think if you think about it, all of our users use data that has come from multiple places and interrogate it through through that. The question is, is, can you actually access, rather than get the data all to come into one place and then interrogate do you turn it, turn it on its head and say, Don’t bother bringing all the data into one place, but provide tools that can interrogate it whilst it’s in numerous places? And I think that’s possible. I definitely think that’s possible. The biggest worry I would have over that is how you get around the security and authentication to actually make it happen, and that’s pretty important. So I mean, I use, as we all do, I’m sure now use things like co pilot on a regular basis, if nothing else, just to help me browse more easily and find information more more quickly. But it’s doing that from the public web and and that’s great, and it works. Works really well when you’ve got your data in lots of private and secure and protected data stores, as indeed they have to be. How do you use the technology to to deal with that in a way which you feel comfortable with, in terms of tokens or security or authentication, huge amounts of challenges, but opportunity, as you say, and it’s going to change so quickly. I was looking back at some screen grabs of responses to prompts from, you know, two years ago, and it was just my prompts were quite basic then, but also the results have moved on significantly, and we wrap up are conversations with a few rapid fire questions, after which Alistair and I’ll just reflect on some of the things we’ve talked about today. To get to the rapid fire around Nick one, AI application that’s made a big difference to your day to day, in a work sense, actually the one that I’m using, so I mentioned copilot, and I think copilot is amazing, but the one I’m probably using now more is, is the Amazon queue capability to help me interrogate data in a way that I wasn’t before. So we actually, you know, I use that internally to make a better I think we’ve already always been pretty good in our business about dashboarding within our business to understand what’s going on with our users, our customers, other elements of our business. You know just how it operates. But Amazon queue has just taken it to a different level. It’s it’s absolutely incredible. It’s enabled me to get, to get the answers much more quickly, and in a way, that means I don’t need to be as as as big an egghead about data query.

30:00

As I used to be

30:02

some my wife would say, I still am. But you know, that’s that’s another topic that’s great to hear, and not one I think we’ve, we’ve heard before on this podcast. So thank you. The next question I was asked is, do you have a podcast or book or the resource recommendation for listeners to check out?

30:20

Oh, I love my books, and I’m a voracious reader. Always happy, but I probably recommend a podcast at the moment, because I recently, relatively recently, fallen in love with a podcast called acquired.com

30:32

and I don’t know if you a listener looking at Heather’s reaction there, it sounds like you might like it too Heather, but for listeners that haven’t seen it or aren’t aware of it. It’s absolutely fantastic. Been stretching for some 14 seasons or something now. So there’s a lot of back catalog, if you’re going to go into it, and essentially, it’s an investigation, company by company, into some of the world’s greatest companies about their history. And you know, how they started, the mistakes they made, the good decisions they made in the early days, what when they maybe always went bust 10 years in and stuff. The Nvidia story in particular is a fact given, given where Nvidia is right at the time of us recording this in terms of their share price, doing, you know, it’s been a fantastic and fascinating story. So I highly recommend acquired.com I’d be sure to check it out. It’s not on my list. It wasn’t on my list, but it is now my favorite podcast they’ve done was on Costco. It was so great, and it’s and it’s so relatable for our industry, because it’s, it’s a great story of vertical integration gone, right. Biggest AI fail neck. Oh gosh, that’s a difficult one.

31:45

Well, that I’ve seen out there, because, I mean, we’ve certainly had some internally where we hoped for stuff that a capability for internal use is going to work, and it hasn’t really delivered on that. So we’ve got, we’ve got a few, a few scars, to be honest at the moment, and the jury’s out on whether it’s actually a fail, and it might work out okay, but I think Apple’s speed of response and reaction to AI has been surprisingly late to the party. Stroke slow. I think that they had, for my money, they had probably the best, almost the best opportunity out there, given that most of us are carrying around devices that well is either one of theirs or an Android and so so much data, I thought that was a I thought that was a gimme, and it feels like they missed the boats a little. Oh, I am absolutely with you there, Nick, as someone who got onto the iOS beta, changed my location to be in the US just to try out Apple intelligence, to turn out that it wasn’t at all intelligent. And now the action button on my phone takes me to the chat, GPT chat, because it’s so much better. So yeah, no, definitely agree with you there.

32:58

Well, that’s a pretty much all we got time for today. So thank you so much, Nick for your time this morning. It’s been really, really interesting, really helpful.

33:08

Yeah, thank you very much. Loved it. Alistair, loved it, Heather, thank you very much for inviting me and look forward to the next one.

33:20

That was a really, really fascinating conversation with Nicky talk. He’s very thoughtful, knowledgeable, and runs one of the bigger tech firms in our sector, with lots of time spent in Australia and the US recently. So great to get his thoughts. Alistair, I want to hear from you, but first two things from me. He categorized the types of AI. So generative AI gets a lot of attention, but he mentioned generative AI, rpa, robotic processing, automation and machine learning. And I thought those three categories were interesting partly because of the examples he used in each of them. So for coding that anybody can write code. Now it’s really interesting and the opportunities in his business with that rpa, the challenge of re keying, the challenge of, you know, different levels of APIs. Everyone says they have an API, but, but you will have ingested some of those APIs and know that they don’t all work as promised. And you know the opportunity for RPA to automate some of that re keying and and, and bring data from system to system, I think, is really interesting. And then machine learning about interrogating data, which takes me to my second I thought what he was saying about Amazon queue is really interesting, not necessarily because of Amazon queue, but because of that shift towards natural language queries and, and, you know, I’m somebody who struggles to get data out of systems, even though I’m a, you know, data analyst, by training and and being able to ask the question I want, rather than thinking, this is the question, this is the outcome. But where do I need to get the data? What do I need to look for? You’ll be able to ask that.

35:00

In a natural language way, I think is really, really interesting. Yeah, absolutely. I think for me, the couple of bits that stuck out from Nick The first was

35:12

kind of hearing about the due diligence that intelliflow feel they need to do, but also that they don’t feel they can then give a little gold star that says this has been this has passed our due diligence. I thought it gave a couple of really good practical ideas to advise firms on what they can do. But I’m definitely guilty as a customer of thinking, why can’t they just let me, you know, open up all my data to this, to this tool that I want to use? And so hearing, hearing sensible reason why is that’s quite interesting. I was also quite surprised to hear that the US, you know, isn’t bounding on ahead, and, you know, the US advice world hasn’t automated absolutely everything, and all the advisors are sitting on beaches in the Caribbean At this point, you know, letting the AI do the work for them. So I was, I was actually expecting to hear that there’d be a bit more of that. So that’s interesting, too. And maybe, maybe we’re not lagging behind as far as our British sensibilities make us think we are. I don’t think so. I mean, my experience of having spent a bit of time in the US with advice firms last spring was that where they’re thinking about using AI as more in customer acquisition, and a lot of those firms are really businesses rather than advice practices and and I think the UK actually could use a little bit of that um thinking to be more, not sales oriented in a negative way, but just thinking about, you know, what’s the, what’s the, having a really defined professional process for bringing in new customers, and not being shy about that. The other thing I wanted to mention was he mentioned the tire advice journey and how AI can play a role across the entire journey. And I think he’s absolutely right. But one thing I’ve been learning in a piece of work we’re doing now on advice at scale is that firms are thinking you need algorithmic advice with AI used at points in the journey that aren’t about the advice generation, because you can’t have the advice delivered in a black box that can’t be queried. You have to ensure consistency. So I think there’s some challenges there around there’s a bit of realism we need to apply to how much AI will be able to be used to automate advice. It’s not the advice that will be automated, but aspects of the process that could be speeded up, even if you can reinvent and reimagine the way advice is done with new technology, absolutely. But that’s not in full end to end, AI process, and in my view, yeah, fully agree. Fantastic. Listen. Alistair, I’ve had a huge amount of fun hosting this series with you. You’ve been an amazing co host, somebody who actually knows what they’re talking about when it comes to AI so thank you for joining me in these last eight episodes, and for joining us, me as the co host for our AI Lab. Our next meeting of AI Lab is the 29th of April. We’ve got a link in the show notes if you would like to get more information. Our sponsors for that are Aviva, fidelity, ssnc and Salesforce, so thank you to them. The next series for the podcast will be recordings of presentations from NextWealth Live or annual conference. That conference happens on the 18th of March. We have about 50 tickets left, so don’t delay if you want to be there. Thank you to Artemis Irvin, our Podcast Producer, and Alistair, thanks again. Thank you, Heather. I’ve had an absolute blast Speak to you soon.

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