Gillian Bowen, Host: Hello, my name is Gillian Bowen and this is Small Firm,
Gillian Bowen, Host: Big Impact.
Kayur Patel, CA: If you can help every single person in your business,
Kayur Patel, CA: say half an hour a day or 45 minutes a
Kayur Patel, CA: day or an hour a day, it might seem like
Kayur Patel, CA: a small number, but when you scale that across your
Kayur Patel, CA: entire business or your entire team, that dramatically increases the
Kayur Patel, CA: efficiency of the organization. Treat your AI model or your
Kayur Patel, CA: tool like you would treat an intern or a grad.
Kayur Patel, CA: When I'm saying you can do a particular use case
Kayur Patel, CA: when you're explaining it to the model, explain it how
Kayur Patel, CA: you would explain it to an intern or grad, you're
Kayur Patel, CA: going to get a really good result.
Gillian Bowen, Host: It's the podcast giving Chartered Accountants the up to date
Gillian Bowen, Host: information they need to do their jobs. Each episode, I
Gillian Bowen, Host: share resources, tools and expert advice provided by Chartered Accountants
Gillian Bowen, Host: Australia and New Zealand and a range of people across
Gillian Bowen, Host: our profession. So get following the podcast in your favourite
Gillian Bowen, Host: podcast app. Let's start a conversation. Today. It's a big
Gillian Bowen, Host: welcome back to Kayur Patel CA for part two of our
Gillian Bowen, Host: discussion on generative AI. Now welcome back. First of all,
Gillian Bowen, Host: Kayur thanks for coming back.
Kayur Patel, CA: It's good to be back. Thank you.
Gillian Bowen, Host: Part two, as we promised, is focused on use cases
Gillian Bowen, Host: for accountants. And why you might be asking. Well, all
Gillian Bowen, Host: of that is included in part one. So go back
Gillian Bowen, Host: and listen to that first. But in summary, GenAI and
Gillian Bowen, Host: getting across it is all about efficiency and productivity and
Gillian Bowen, Host: adding value to your individual work life, but also your
Gillian Bowen, Host: business life and the life of your clients. And what
Gillian Bowen, Host: you'll learn in this discussion is that starting small now
Gillian Bowen, Host: is the key to bigger things down the track. So Kayur,
Gillian Bowen, Host: just quickly, before we dive into the specifics of the
Gillian Bowen, Host: act or, you know, action stations, as I like to
Gillian Bowen, Host: call it, um, why do that? Why focus on small
Gillian Bowen, Host: things now rather than waiting for the next big shiny
Gillian Bowen, Host: AI tool?
Kayur Patel, CA: Yeah, it's a good question. And, you know, I've been
Kayur Patel, CA: helping clients, um, understand GenAI and then implement GenAI, a safe AI
Kayur Patel, CA: in their, in their environments for the last few months
Kayur Patel, CA: and by far and away the biggest piece when it
Kayur Patel, CA: comes to helping educate organizations around AI is how do
Kayur Patel, CA: I make sure that I get efficiency now? Because everyone's
Kayur Patel, CA: waiting for the big shiny thing, the thing that's going
Kayur Patel, CA: to say one silver bullet. Um, but what it's really easy,
Kayur Patel, CA: is really easy to miss is the fact that if
Kayur Patel, CA: you can help every single person in your business, say,
Kayur Patel, CA: half an hour a day or 45 minutes a day
Kayur Patel, CA: or an hour a day, it might seem like a
Kayur Patel, CA: small number, but when you scale that across your entire
Kayur Patel, CA: business or your entire team, that dramatically increases the efficiency
Kayur Patel, CA: of the organization. And that is possible right now with
Kayur Patel, CA: tools available right now, as long as you use a safe,
Kayur Patel, CA: enterprise grade, secure what I like to call safe AI option.
Gillian Bowen, Host: Mhm mhm. Yeah that is a key part. And we'll
Gillian Bowen, Host: explore that as well. Um and if we don't explore
Gillian Bowen, Host: it we'll put information about that in the show notes.
Gillian Bowen, Host: Um so what I was thinking and you and I
Gillian Bowen, Host: have had a chat prior to this because, you know,
Gillian Bowen, Host: planning is key to a quick and good discussion. We're
Gillian Bowen, Host: going to cover three areas. So area one or part
Gillian Bowen, Host: one is going to be text based use cases. Then
Gillian Bowen, Host: we're going to have a look at data based use cases.
Gillian Bowen, Host: And then we're going to wrap up by having a
Gillian Bowen, Host: look at a couple of bespoke use cases. And as
Gillian Bowen, Host: I said we're going to try and do that in
Gillian Bowen, Host: 20 minutes or less. So first of all Kayur, how can
Gillian Bowen, Host: I use text based generative AI right now in my
Gillian Bowen, Host: accounting firm?
Kayur Patel, CA: Yeah. Okay. So the first category is a text and
Kayur Patel, CA: then some data stuff as well. And for each of
Kayur Patel, CA: these categories, um, I might just reinforce one comment from
Kayur Patel, CA: the previous episode, which is remember that these AI models,
Kayur Patel, CA: these GenAI models, you have to treat them differently to
Kayur Patel, CA: like a search engine. Right? Because they're built they're built
Kayur Patel, CA: based on neural networks. And the example we used last
Kayur Patel, CA: week was, you know, when a baby is learning how
Kayur Patel, CA: to speak, they might look at their dad and say, um, dada,
Kayur Patel, CA: and then everyone will make a huge deal about it.
Kayur Patel, CA: And so that will get reinforced. That data is that
Kayur Patel, CA: person if they say, mama, um, nobody will make a
Kayur Patel, CA: big deal about it. And so then they'll know that
Kayur Patel, CA: that's not reinforced. And so that's how these GenAI models learn.
Kayur Patel, CA: And so as I'm going through these examples, uh, with
Kayur Patel, CA: your listeners, I would encourage everyone if they take nothing
Kayur Patel, CA: away from today's podcast, but this, um, treat your AI
Kayur Patel, CA: model or your tool like you would treat an intern
Kayur Patel, CA: or a grad, right? So when I'm saying you can
Kayur Patel, CA: do a particular use case, when you're explaining it to
Kayur Patel, CA: the model, explain it how you would explain it to
Kayur Patel, CA: an intern or grad, you're going to get a really
Kayur Patel, CA: good result rather than just typing it into a search engine.
Kayur Patel, CA: And equally, you know, if you gave a piece of
Kayur Patel, CA: work to an intern or a grad, you wouldn't expect
Kayur Patel, CA: that they would give you a piece of work that was,
Kayur Patel, CA: you don't have to look at it, you just send it
Kayur Patel, CA: straight out to the client. Um, you would want to
Kayur Patel, CA: review and check because that's how that's how the process
Kayur Patel, CA: goes to make sure that we tick the boxes and
Kayur Patel, CA: that we're providing good work for our clients. The same
Kayur Patel, CA: thing with these AI models. Treat it like an intern or grad.
Gillian Bowen, Host: Such good tips. I love that such good tips. Okay, so.
Kayur Patel, CA: So with that in mind, pretty much any text based
Kayur Patel, CA: thing that you get an intern or a grade to do,
Kayur Patel, CA: you can get an AI model to do so. Here's
Kayur Patel, CA: what I is really good at from a text based thing.
Kayur Patel, CA: First category you can do is very good at creating documentation,
Kayur Patel, CA: creating text. Right. So I use it right now to
Kayur Patel, CA: draft articles for me to draft documents, to draft emails, communications. Um,
Kayur Patel, CA: I even get it to convert text that I write
Kayur Patel, CA: into my voice, like my actual voice and my video. Very,
Kayur Patel, CA: very good at doing those text based things, provided you're
Kayur Patel, CA: using specific prompts that, um, are engineered in a way,
Kayur Patel, CA: as if I was having a conversation with an intern.
Kayur Patel, CA: So I'm giving it the right background. I'm giving it, um,
Kayur Patel, CA: a conversation rather than just a one liner. Do this
Kayur Patel, CA: for me. I am providing it with other examples of
Kayur Patel, CA: documentation or email that I've done in the past, so
Kayur Patel, CA: it learns how to sound like me or how I
Kayur Patel, CA: want it to sound. Those are all things that I would, um,
Kayur Patel, CA: provide to an intern or a grad when I get
Kayur Patel, CA: it to write my emails or do text based documentation.
Gillian Bowen, Host: So my brain's ticking away already. So just quickly to
Gillian Bowen, Host: confirm, in my understanding say, for example, I paste into ChatGPT,
Gillian Bowen, Host: for example, a version that is that I've paid a
Gillian Bowen, Host: subscription for or that is just that that's legally protected. Um,
Gillian Bowen, Host: I put in some emails that I write and then say,
Gillian Bowen, Host: can you create an email that is written as if
Gillian Bowen, Host: I wrote it to blah blah about said topic, and
Gillian Bowen, Host: it would bring it up?
Kayur Patel, CA: Absolutely. And it would. If you've given it content like
Kayur Patel, CA: your previous emails, it's going to sound much more like you.
Kayur Patel, CA: And then if you were to provide it with more context,
Kayur Patel, CA: so explaining some background about who the recipient is and
Kayur Patel, CA: how much background knowledge they have, and whether you want
Kayur Patel, CA: the email to be formal or more casual or how
Kayur Patel, CA: detailed you want it to be, it's going to do
Kayur Patel, CA: even better. Just like it would be if if, um,
Kayur Patel, CA: if it was, if it was a human.
Gillian Bowen, Host: And so what you would do is you would write,
Gillian Bowen, Host: you're engaging with it, aren't you? You would say, okay,
Gillian Bowen, Host: that's a good first attempt. But, um, if I give
Gillian Bowen, Host: you this additional information, how would you rewrite that? And
Gillian Bowen, Host: then it'll produce another version.
Kayur Patel, CA: It's very much an iterative process that you hit the
Kayur Patel, CA: nail on the head. It's very much an iterative process.
Gillian Bowen, Host: Great. What else?
Kayur Patel, CA: So also in text. So um, outside of the creation bucket,
Kayur Patel, CA: it's very good at improving and transforming previously written text.
Kayur Patel, CA: So for example, you might have a piece of advice, um,
Kayur Patel, CA: to go out to a client. I think in the
Kayur Patel, CA: last episode we talked about fringe benefit tax. So maybe
Kayur Patel, CA: it's on how fringe benefit tax relates to their motor
Kayur Patel, CA: vehicle pool, for example. And you might think that the
Kayur Patel, CA: technical information is correct, but you want to craft it
Kayur Patel, CA: into a nice response. You can copy and paste in
Kayur Patel, CA: what you've written, some bullet points of the technical information,
Kayur Patel, CA: making sure you've got the right you know, the correct answer,
Kayur Patel, CA: and then get the model to be able to convert
Kayur Patel, CA: that into a nice email or notes to file or
Kayur Patel, CA: document or whatever it is that you need to send
Kayur Patel, CA: out the door to the client. I do this all
Kayur Patel, CA: the time, and it means now my emails to clients
Kayur Patel, CA: or whoever else it might be. I'm literally writing bullet points,
Kayur Patel, CA: and then I'm using AI to convert it into a
Kayur Patel, CA: nice email. And you do that for every email that
Kayur Patel, CA: you send that needs to be, you know, professionally worded, that
Kayur Patel, CA: starts to stack up into some serious time saving. Also
Kayur Patel, CA: very good at transforming text from a perspective of, you know,
Kayur Patel, CA: if you've got some generic text, get AI to convert
Kayur Patel, CA: that to a first person text. So it reads as
Kayur Patel, CA: if the recipient is it's talking to the recipient rather
Kayur Patel, CA: than talking about something um in general, it's very good at
Kayur Patel, CA: that and then also very good at taking some specific facts
Kayur Patel, CA: and then applying them to a template that you might
Kayur Patel, CA: have in your organization. If you've got a template that
Kayur Patel, CA: you use for a specific type of report for clients
Kayur Patel, CA: or whatever it might be very good at, then taking
Kayur Patel, CA: some specific details and putting them into your templates in
Kayur Patel, CA: the right way so that it reads well.
Gillian Bowen, Host: All right. So are there any other text based use
Gillian Bowen, Host: cases that you want to tell us about before we
Gillian Bowen, Host: move on?
Kayur Patel, CA: Yeah. So the other category I think is summarization. So
Kayur Patel, CA: AI is very, very good at being able to summarize
Kayur Patel, CA: massive amounts of text or documentation into an easy to
Kayur Patel, CA: understand summary. So where do I use this? Anytime I'm
Kayur Patel, CA: going to talk to a client, um, I will get
Kayur Patel, CA: documentation that is relevant to them and summarize it down
Kayur Patel, CA: so that I understand it so I can be proactive
Kayur Patel, CA: when I talk to them. So that might be recent
Kayur Patel, CA: tax alerts from Inland Revenue. That might be latest industry
Kayur Patel, CA: information or documentation. That might be documents that I found
Kayur Patel, CA: from the client's own website. But I will use it
Kayur Patel, CA: every time before I go and have a conversation with
Kayur Patel, CA: a client. And that's just one example. But its ability
Kayur Patel, CA: to summarize large documentation into something that's easy to understand
Kayur Patel, CA: is brilliant. Everyone should be doing it.
Gillian Bowen, Host: So it's teaching you, it's upskilling you before any sort
Gillian Bowen, Host: of meetings or interactions that you're going to have with
Gillian Bowen, Host: the client.
Kayur Patel, CA: Absolutely. And to the extent that I recommend to our
Kayur Patel, CA: own graduates and interns before they look at a new
Kayur Patel, CA: technical piece or information or topic or client industry for
Kayur Patel, CA: the first time, they should be doing that for the
Kayur Patel, CA: relevant documentation, for whatever that technical thing is, or the
Kayur Patel, CA: client or the industry every single time. It will just
Kayur Patel, CA: help them be a) more proactive, but b) just understand
Kayur Patel, CA: that base level of information to help get them up
Kayur Patel, CA: the curve quicker before they get in. And then do
Kayur Patel, CA: the work.
Gillian Bowen, Host: How much time do you reckon that alone would save, um,
Gillian Bowen, Host: a person or yourself? Instead of having to go and
Gillian Bowen, Host: find everything, read it all and then write your own stuff.
Kayur Patel, CA: Oh, I mean, for me, on a weekly basis, I
Kayur Patel, CA: save hours and hours just using that one set of
Kayur Patel, CA: use cases, the summarization.
Gillian Bowen, Host: Um, wow.
Kayur Patel, CA: You know, like a recent example, um, BEPs pillar two,
Kayur Patel, CA: the big documentation. I know that I didn't need to
Kayur Patel, CA: understand every single thing, but I needed to get a
Kayur Patel, CA: general idea of what it was about and when it came
Kayur Patel, CA: into force for various balance dates. That was something that
Kayur Patel, CA: I would have had to read through and kind of
Kayur Patel, CA: sift through and take quite a bit of time on. But, um, 30 seconds,
Kayur Patel, CA: genuinely 30 seconds.
Gillian Bowen, Host: And is it safe? Are you informed enough? Like is it able
Gillian Bowen, Host: to trust? And your argument is that you can trust
Gillian Bowen, Host: what it spits out because you've put the source document
Gillian Bowen, Host: in the AI.
Kayur Patel, CA: Absolutely. And and also I'm using this to give me
Kayur Patel, CA: that base level of knowledge and understanding. I'm not using
Kayur Patel, CA: it as the final authority on the topic. Important. And
Kayur Patel, CA: so when I'm using it to give me that base knowledge,
Kayur Patel, CA: I'm far more comfortable with being able to, um, to
Kayur Patel, CA: trust what it says. The other piece, though, is I
Kayur Patel, CA: do make sure that my prompts are specific. The way
Kayur Patel, CA: you prompt for these things will heavily influence the the
Kayur Patel, CA: stuff you get out.
Gillian Bowen, Host: And that's the difference. That's the key note there between
Gillian Bowen, Host: you and I and between our listeners and yourself. You
Gillian Bowen, Host: live and breathe GenAI every single day. You lecture in it,
Gillian Bowen, Host: you teach in it, you work in it. It is
Gillian Bowen, Host: your job title. Um, that I would argue you are
Gillian Bowen, Host: very qualified to understand what prompts one should put into
Gillian Bowen, Host: the AI to get back the best result. So before
Gillian Bowen, Host: we move on then to, um, data based, what are
Gillian Bowen, Host: the risks here, um, with what you've proposed and how
Gillian Bowen, Host: do you respond to those risks?
Kayur Patel, CA: Yeah. So look like everything there are risks. Um, and
Kayur Patel, CA: those risks are a) that the AI tool you're using
Kayur Patel, CA: and this would be for all of the examples that
Kayur Patel, CA: we give in this session, um, is not safe and secure.
Kayur Patel, CA: So absolutely advocate for nobody should be put in client
Kayur Patel, CA: or their own company information in a publicly available free
Kayur Patel, CA: AI tool. And also not even in a paid AI
Kayur Patel, CA: tool unless it is, um, what we call enterprise grade.
Kayur Patel, CA: So make sure that you have safe enterprise AI. Um,
Kayur Patel, CA: the second thing is you got to make sure that
Kayur Patel, CA: the information you get out is accurate and reads correctly
Kayur Patel, CA: and well. Now, I actually think accountants are best placed
Kayur Patel, CA: to make sure that that happens because we've already got
Kayur Patel, CA: the review structures in place. Right? So if a grad
Kayur Patel, CA: does a piece of work, normally they're not just going
Kayur Patel, CA: to send it out to the client without a review. Right?
Kayur Patel, CA: It'll get reviewed by the manager or the partner. We've
Kayur Patel, CA: already got a review structure. So keep the same review
Kayur Patel, CA: structure that you've got in place in place. It's just
Kayur Patel, CA: that the first cut is being assisted by these models. Um,
Kayur Patel, CA: and then the other piece is you can massively reduce
Kayur Patel, CA: the risk if you understand how to prompt well. And a
Kayur Patel, CA: big part of the training we provide to clients is
Kayur Patel, CA: helping them understand how to curate good prompts to get
Kayur Patel, CA: the right answer and the right tone of voice and
Kayur Patel, CA: all of those types of things. Yeah.
Gillian Bowen, Host: That sounds like a key piece of learning for everyone
Gillian Bowen, Host: that's listening. How to prompt well, how to engage effectively
Gillian Bowen, Host: with the AI to make it produce the best result.
Gillian Bowen, Host: We'll see if we can find some suitable reading or
Gillian Bowen, Host: information for that. Or heck, we may even do an
Gillian Bowen, Host: episode literally just on that. But a little bit further
Gillian Bowen, Host: down the track. There's so much to talk about in
Gillian Bowen, Host: this space, and I know that our members really, really,
Gillian Bowen, Host: really want the information. Let's move on to data. Um,
Gillian Bowen, Host: it's key to the life of an accountant. Um, what
Gillian Bowen, Host: can a small or medium sized practice use right now
Gillian Bowen, Host: to be more efficient, uh, more productive to add value?
Kayur Patel, CA: Yeah. So there's probably a few examples that, um, that
Kayur Patel, CA: you can jump into straight away. So if you use
Kayur Patel, CA: Excel and I'm assuming that, that everyone listening to this does, um,
Kayur Patel, CA: you can get these large language models to do two
Kayur Patel, CA: things with Excel. One, you can get them to help
Kayur Patel, CA: you either create or troubleshoot your formulas. So if you've
Kayur Patel, CA: got a massive workbook for forecasting or budgeting and you're
Kayur Patel, CA: trying to get you're trying to figure out why something's breaking,
Kayur Patel, CA: it's very good at helping you to either troubleshoot or
Kayur Patel, CA: create the right formulas for you. So that's that's probably
Kayur Patel, CA: one use case. The second thing that some of these
Kayur Patel, CA: models can do, though, is you can upload Excel files
Kayur Patel, CA: to them and just say in its simplest form, just say,
Kayur Patel, CA: I've got, um, sales data for the first seven months
Kayur Patel, CA: of the year. Um, in an Excel file, you could
Kayur Patel, CA: then get the model to create columns for each month
Kayur Patel, CA: for the rest of the year, and then predict out, um,
Kayur Patel, CA: sales volumes for each month for the rest of the year, um,
Kayur Patel, CA: based on some parameters. So you could say a 10%
Kayur Patel, CA: uplift in this or a change in this variable or
Kayur Patel, CA: whatever it might be, and it will then go and
Kayur Patel, CA: create the file, sorry, create the extra columns, create the
Kayur Patel, CA: data in those columns and allow you to download that
Kayur Patel, CA: file as well. And, and some of these newer tools
Kayur Patel, CA: like Microsoft Copilot, um, you won't even need to upload
Kayur Patel, CA: them and it'll just it just already is able to
Kayur Patel, CA: access your Excel files and just, um, and provide you
Kayur Patel, CA: with those changes on the fly as well. Um.
Gillian Bowen, Host: How many accountants do you think are across the use
Gillian Bowen, Host: or the availability of of that to them?
Kayur Patel, CA: Um. To be honest, not many. So. Probably very few. Um,
Kayur Patel, CA: and look, that's not necessarily a bad thing, because the
Kayur Patel, CA: ability of these tools to be able to work well
Kayur Patel, CA: with Excel is a very recent thing. So if we were,
Kayur Patel, CA: if we were recording this 2 or 3 months ago, um,
Kayur Patel, CA: actually even more recent than that, that's not something I
Kayur Patel, CA: would be recommending people play with, because I just didn't
Kayur Patel, CA: think it was good enough at that stage. And it's
Kayur Patel, CA: still early days, don't get me wrong, but it's now
Kayur Patel, CA: got good enough for me to think, well, this is
Kayur Patel, CA: interesting and
Kayur Patel, CA: I should get it trying so that yes, yes.
Kayur Patel, CA: I'm improving with it.
Gillian Bowen, Host: I just feel like this is good. I mean, I
Gillian Bowen, Host: know that a podcast is hard to be, you know,
Gillian Bowen, Host: breaking news, but I feel like that is a breaking
Gillian Bowen, Host: news development that you can use AI that way and
Gillian Bowen, Host: excel that way together. Um, and I just think, as
Gillian Bowen, Host: you said at the top of the show, um, saving
Gillian Bowen, Host: 30 minutes a day scaling that across your business, that
Gillian Bowen, Host: to me sounds like something that is, um, day changing,
Gillian Bowen, Host: week changing, month changing.
Kayur Patel, CA: Yeah. And that's before you even get into, you know,
Kayur Patel, CA: like AWS, they have a data visualization app. If you're
Kayur Patel, CA: using that already, you can now use an AI module
Kayur Patel, CA: on top of that to be able to natural language,
Kayur Patel, CA: ask it to do things for you. So create me
Kayur Patel, CA: a graph that compares sales data for the last three
Kayur Patel, CA: months with accounts receivable and cash or whatever else it
Kayur Patel, CA: might be, and that's also extremely new. Um, and, and
Kayur Patel, CA: those are like kind of bespoke data visualization tools. Power
Kayur Patel, CA: BI is going to have that very shortly as well. So, um,
Kayur Patel, CA: the examples I've talked about is are literally using the
Kayur Patel, CA: same tools we've already got, but um, with or alongside
Kayur Patel, CA: an AI model. Um, that's before you even get to
Kayur Patel, CA: these like specifically built data visualization and manipulation tools that
Kayur Patel, CA: have got AI embedded.
Gillian Bowen, Host: So we're talking about data.
Gillian Bowen, Host: So there's two things there for data isn't there. There's
Gillian Bowen, Host: a there's programs that have an AI data tool built
Gillian Bowen, Host: on top of them, like you'd said with AWS, but
Gillian Bowen, Host: in in the sense of Excel, you are putting the
Gillian Bowen, Host: Excel into your text based AI, am I right?
Kayur Patel, CA: Yeah. This so well there's two options. So if you um.
Gillian Bowen, Host: Just that I clarify that that's what we're talking about. Right.
Gillian Bowen, Host: But you go ahead first. Yes.
Kayur Patel, CA: Well for most of the models that's exactly right. You'll
Kayur Patel, CA: upload an Excel file, um, and it will read the
Kayur Patel, CA: file and understand it. And then you'd ask it to, um,
Kayur Patel, CA: you know, in that last example, extrapolate out sales based
Kayur Patel, CA: on some variables and, um, update the Excel file so
Kayur Patel, CA: you can download it. Um, but Microsoft Copilot, as that improves, um,
Kayur Patel, CA: that will get better and better at doing that natively
Kayur Patel, CA: within Excel as well. Um, so there's there's a few
Kayur Patel, CA: different options depending on which route of safe AI you
Kayur Patel, CA: want to go down, which models you decide to choose.
Gillian Bowen, Host: Yep, that makes sense. I just wanted to make it
Gillian Bowen, Host: clear that we weren't talking about a data based AI.
Gillian Bowen, Host: We were just talking about how to use AI with
Gillian Bowen, Host: your data, and as a result, you are using the
Gillian Bowen, Host: text based AI to manipulate your data.
Kayur Patel, CA: Yes, absolutely. And the great thing about that is it's
Kayur Patel, CA: available right now, right?
Gillian Bowen, Host: Yes. Absolutely. Absolutely. Okay. All right. So we're almost out
Gillian Bowen, Host: of time. I want to have a quick look at, um,
Gillian Bowen, Host: 1 or 2 or it might just be one bespoke
Gillian Bowen, Host: option that's relevant to a particular practice, an example of
Gillian Bowen, Host: what that might look like.
Kayur Patel, CA: Yeah. So this is when you start to get into
Kayur Patel, CA: a little bit more, um, I guess, um, specific models
Kayur Patel, CA: that have been altered in a way to help with
Kayur Patel, CA: a specific problem. And this is good if you've got
Kayur Patel, CA: repeatable tasks that you do in your practice all the time.
Kayur Patel, CA: So one pain point that, um, I'm assuming almost every
Kayur Patel, CA: accounting practice has is onboarding clients, right? Like we just
Kayur Patel, CA: want to get in and start doing the work. You've
Kayur Patel, CA: got to get the right information. You got to do
Kayur Patel, CA: AML checks, you got to do a whole bunch of stuff. Um,
Kayur Patel, CA: and so you could, um, build using a set of, uh,
Kayur Patel, CA: using an algorithm and, um, and a specific piece of, um,
Kayur Patel, CA: publicly available safe AI to build you an AI based
Kayur Patel, CA: automated workflow to, for example, onboard clients. So a client,
Kayur Patel, CA: you send them a link and it asks them for
Kayur Patel, CA: some basic information. And based on that information, the AI
Kayur Patel, CA: will understand what further information to ask and where to
Kayur Patel, CA: put that information and who to notify based on what
Kayur Patel, CA: type of problem they need to be solved and when
Kayur Patel, CA: based on that person's availability and their expertise. Um, and
Kayur Patel, CA: all of those other factors. You can now start to
Kayur Patel, CA: automate all of that, not based on some a small
Kayur Patel, CA: set of predefined rules, but based on AI understanding what
Kayur Patel, CA: the client wants, who they are and who's in the
Kayur Patel, CA: team and their availability and their skill set and all
Kayur Patel, CA: those other types of things. So you can start to
Kayur Patel, CA: now build some specific, um, automated AI based workflows. Um,
Kayur Patel, CA: and that makes sense when they're highly repeatable, when you've
Kayur Patel, CA: got to onboard lots of clients all the time, for example.
Gillian Bowen, Host: That's interesting. That's I'm writing that down, AI based workflows.
Gillian Bowen, Host: That's the key takeaway there. And you get, um, that
Gillian Bowen, Host: there's AI specialists that are able to help your individual
Gillian Bowen, Host: practice do that.
Kayur Patel, CA: Yeah, absolutely. The one thing I'd say with, with doing
Kayur Patel, CA: that is when you're working with, um, a team or
Kayur Patel, CA: a person to help you do that, there's lots of
Kayur Patel, CA: people that understand the technology. What you really want is
Kayur Patel, CA: someone that understands the technology and the practical applications for
Kayur Patel, CA: your business. And there's no different for you as a
Kayur Patel, CA: chartered accountant. Um, you know, the real value you add
Kayur Patel, CA: is not your understanding of the numbers or the standards,
Kayur Patel, CA: but it's your ability to relate that practically to your
Kayur Patel, CA: client's business and the decisions they need to make. Um,
Kayur Patel, CA: I would say the same thing applies here. The technology
Kayur Patel, CA: is great. And actually it's you know, there's lots of
Kayur Patel, CA: people that can get across that. But how does it
Kayur Patel, CA: specifically impact the the your business, the people in your business,
Kayur Patel, CA: the processes within your business? Um, that's the real key
Kayur Patel, CA: to making sure you implement it well.
Gillian Bowen, Host: Um, okay. Well, we're about to wrap up my final then. Um,
Gillian Bowen, Host: quick question is, after all this, is it easy to
Gillian Bowen, Host: find the reputable program, um, that you suggest, you know,
Gillian Bowen, Host: is it easy to find a reputable GenAI program that is, um,
Gillian Bowen, Host: of the suitable enterprise grade that you talk about? How
Gillian Bowen, Host: do you find it? Where do you start to find that?
Kayur Patel, CA: Yeah, it is available. There's a couple of I mean,
Kayur Patel, CA: the main options that, uh, the clients that I've been
Kayur Patel, CA: talking to are interested in at the moment, um, ChatGPT
Kayur Patel, CA: Enterprise and Microsoft Copilot studio. I'm not saying they're the
Kayur Patel, CA: only ones. Um, those are probably just the ones that
Kayur Patel, CA: come up in conversation more than others at this specific
Kayur Patel, CA: point in time. So, yes, um, that that is possible. Um,
Kayur Patel, CA: and in terms of doing that process and onboarding and
Kayur Patel, CA: all those things, I think it's very important that anyone
Kayur Patel, CA: that on boards, AI does it in a, in a
Kayur Patel, CA: safe manner so that they understand the parameters, um, the
Kayur Patel, CA: implications of putting various types of information and they've got
Kayur Patel, CA: some specific rules around what they can use it for,
Kayur Patel, CA: what they can't, the review process, all of those types
Kayur Patel, CA: of things. And when you get someone to help you
Kayur Patel, CA: implement AI, they will be able to provide you with
Kayur Patel, CA: a templated flow that basically ensures you're safe from woe
Kayur Patel, CA: to go and that they help you with the change management,
Kayur Patel, CA: the process, all of that stuff should be a, you know,
Kayur Patel, CA: a repeatable task for them to help you with.
Gillian Bowen, Host: All of that makes sense. If there's some specific reading that,
Gillian Bowen, Host: um, Kayur is, um, suggesting we'll whack that in the show notes.
Gillian Bowen, Host: And as a separate, um, piece of amazing reading, I've
Gillian Bowen, Host: got the, uh, the team at the CA library to
Gillian Bowen, Host: pull together a list of resources that are relevant and
Gillian Bowen, Host: specific to AI and accounting and also AI in general.
Gillian Bowen, Host: And I've put all of that in the show notes
Gillian Bowen, Host: for episode one, and I'll make sure it's also in
Gillian Bowen, Host: the show notes for part two. It is definitely action stations. Um,
Gillian Bowen, Host: there's a lot to think about. Don't feel overwhelmed though.
Gillian Bowen, Host: It is achievable, and you can see why Kayur suggests that
Gillian Bowen, Host: humans with AI will end up replacing humans without. When
Gillian Bowen, Host: you could have a look at the efficiencies and productivity.
Gillian Bowen, Host: That's what the bid is for me, saving 30 minutes
Gillian Bowen, Host: every day or even a week. And you're a step
Gillian Bowen, Host: ahead of those who aren't, am I right?
Kayur Patel, CA: Oh, absolutely. And so I think everyone right now should
Kayur Patel, CA: be using safe AI for text based use cases. Um, absolutely.
Kayur Patel, CA: I think we should have every organization. There should be
Kayur Patel, CA: at least, um, you know, a percentage of people looking
Kayur Patel, CA: at ways to use it with data. And then I
Kayur Patel, CA: think at this point in time, be aware of some
Kayur Patel, CA: of the bespoke things that you can do with it
Kayur Patel, CA: so that as it becomes more available and cost effective,
Kayur Patel, CA: you can get on top of that as well.
Gillian Bowen, Host: Mhm, mhm.
Gillian Bowen, Host: Such an interesting discussion. That is all we have time for.
Gillian Bowen, Host: And as I said I think we should touch base
Gillian Bowen, Host: again at the end of the year uh to see.
Gillian Bowen, Host: Or it may even be before that to see what
Gillian Bowen, Host: else has been developed. Um, and if you remember who
Gillian Bowen, Host: rolls out some of this um, or is using GenAI
Gillian Bowen, Host: get in touch. Let's discuss the results. Let's talk about
Gillian Bowen, Host: what it is doing for you in your firm, in
Gillian Bowen, Host: your business, for your clients. Um, have you checked out
Gillian Bowen, Host: the podcast page on the CA ANZ website? I recommend
Gillian Bowen, Host: you do that too. There's plenty of other great content experts, interviews,
Gillian Bowen, Host: and resources that are tailored just to you. It is
Gillian Bowen, Host: worth checking out, and I'll put a link in the
Gillian Bowen, Host: show notes as well to the website so it's easy
Gillian Bowen, Host: to find. And of course, you'll see a link to
Gillian Bowen, Host: the podcast in the newsletters that you receive from CA ANZ.
Gillian Bowen, Host: If you want to get in touch with me and the team,
Gillian Bowen, Host: email us at podcast@CharteredAccountantsanz.com and follow the pod in your
Gillian Bowen, Host: favourite podcast app. Let's start a conversation. Thank you Kayur Patel,
Gillian Bowen, Host: for being my guest on two epic episodes of Small Firm,
Gillian Bowen, Host: Big impact.
Kayur Patel, CA: Absolute pleasure. Thanks, Gill. Bye bye.