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SPEAKERS
James Berridge, Becca Durrant, Neil Johnson, Fahad Riaz
Neil Johnson (00:08)
Hi, I'm Neil Johnson, ACCA Careers Editor, and I'll be hosting this new regular series for the ACCA Careerwise. I'll be getting top tips from recruiters and other professionals, and real-world advice for successfully launching your career.
Neil Johnson (00:22)
Hi, this week, we're talking all things AI and other new technology in accounting, and what this means for future roles and skill sets. From the UK based accounting firm Saffery, I'm joined by director, James Berridge, and cloud accounting specialist, Becca Durrant, and from the UAE, ACCA member and business intelligence expert, Fahad Riaz. First, could the guests please introduce themselves, starting with Becca.
Becca Durrant (00:45)
Hi, I'm Becca. So as mentioned, I'm from Saffery, I joined there a year ago. I have been working in accountancy for about ten years now, but recently moved over to a slightly different role. It's very cloud focused, looking at technologies for our clients and how to make things more efficient.
Neil Johnson (01:01)
Thank you. And James,
James Berridge (01:03)
Hi, I'm James Berridge. I'm a director of data analytics at Saffery. I've been in particularly the audit technology space for about six years, being in the accounting space closer to 13.
Neil Johnson (01:15)
And over to you, Fahad.
Fahad Riaz (01:15)
Hi. My name is Fahad. I'm from the Middle East, and I am a Senior Finance Specialist working in a role that is intercepting technology, analytics, data, and accounting. So I used to be an external auditor, I moved into data science and now helping the company grow with data and helping the accounting team to become more efficient through different AI integrations.
Neil Johnson (01:40)
Thank you very much. I think the first question I'd like to ask is a quick 101 into AI in accountancy. How is AI currently affecting accountancy?
Fahad Riaz (01:52)
Speaking from the Middle East, I believe this region is a bit different, bit slower, compared to all the other regions that we speak to. So what we're seeing here in accountancy- robotic process automation, that's the buzz that everybody's getting into, and I believe it's understandable, because the application of automation is really simple. People are really able to understand the impact of it and the use of it. As well as how we can integrate into daily life, it's really useful, and it's really easy for people to understand. Whereas AI, it's a notion of different sort of areas of expertise. So when people look at that, it's really scary, but when they talk about automation, it's more simple. That's what I'm seeing here really being utilised. So everybody is talking about, 'how can I automate this process that I'm spending so much time on?
Neil Johnson (02:45)
And perhaps talking to you, James, could you build on that? Is it a RPA, is it also machine-learning as other areas that you're noticing?
James Berridge (02:53)
So trying to build on it, as opposed to contrasting it - RPA has been popular for quite a few firms in UK, speaking to peers at other firms for numerous years. And it is largely about just, of course, automating the human process. Historically that involved little to no judgment, everything was hard coded in. Increasingly, we can use, hesitantly, AI in this context, but elements of AI, whether it's machine-learning, etc, to start to make not overly important judgments for you. So instead of the RPA just doing very strict process and then alerting the human every time, there is potential there where it can make some simple judgements itself. I think what's sticking with the more hype-driven GenAI, where I think a lot of firms are using this to some extent already, and it tends to be using either ChatGPT, or, more commonly, the Bing version of it, because it can be kind of locked down in a enterprise environment so you're not worried about your client data disappearing somewhere. People are using that a reasonable amount, and it tends to be for stuff like redrafting emails or writing initial drafts of stuff, sometimes research, whether that's tax legislation or audit standards or whatever it is, trying to do that first layer of research. What it isn't doing is your entire audit for you at this stage, despite what the media may sometimes have you believe, but I am certainly aware of quite a lot of use cases, more in the cloud systems that Becca can probably expand on better than I can.
Neil Johnson (04:38)
Yeah, that'd be great, Becca.
Becca Durrant (04:39)
Yeah, sure. I think it's probably important firstly to say that AI has been in cloud software for a long time. It just hasn't always been as obvious as it perhaps is now. So doing things like recognising receipts, reading bank statements and giving you suggestions of where things should go, try to make processes more efficient - that's been around for quite a long time now, not necessarily used by everyone, but it's been there and quite widely used. And one of the big features that probably cloud platforms have pushed over the last few years - optical recognition and things and suggestions of how to do things better - that's just constantly developing, it's getting better. So if you went on one of those platforms five years ago, it might have recognised two receipts and one of those was probably wrong. Whereas now, the same platform would pick up every single receipt and, I would say 99% of time, they'd be right, and it's in the right place. So actually, the machine learning from that side of things is much better than it was. And then the cloud accounting platforms are now trying to join all the other co-pilots in the functions with that, they're all bringing out their own assistants and bots and things to use within the cloud accounting platforms themselves. So being able to use WhatsApp and talk to an AI assistant now, but that is very new. And I suppose the other side of things is people talk about apps in the cloud, or different applications that you can have, and they are very heavily AI driven for probably the last two or three years now. And you find their main selling point most of the time, is - we can do this, we can tell your clients this, mainly for a push towards that advisory side that I think a lot of accountants, particularly smaller firms, have been really trying to grow their advisory services, and these AI driven insights can help with that. So I think it's been going on in cloud for a long time, but it's it's more of a buzzword now, over the last year.
Neil Johnson (06:36)
Yeah, you mentioned how things are coming out, it leads us on to the next question, or the next point I'd like to talk about - the future. It's important for if you're a young professional, you need to keep abreast of this. There's a lot of moving, a lot of innovation. Looking ahead, what's the key development that you've got your eye on?
Fahad Riaz (06:53)
So building on what James was saying earlier - it doesn't do the whole audit for you now, but it will become a very real possibility that with a good amount of human intervention, interception, and supervision, AI audits will be a possibility on a lot of the work that we see now, which is only the repetitive and mundane parts being done by microprocessors, we will be seeing AI take control of many things on a more wholesome level. But quite specifically, things like fraud and internal audits, that's where I see a big game changer happening, because those are things that we as humans might not be able to connect so many dots. As you know, the thieves get more creative. We might not be able to keep up with the same speed. So that's where the machine learning and the AI sophistication comes into play, because they will be able to detect anomalies and do the fraud prevention part much better than we can. But of course, that comes with its own challenges.
Neil Johnson (07:53)
Thank you, Fahad. And James?
James Berridge (07:56)
There's a lot of doom and gloom in some media that, for example, AI is going to replace the job of all accountants. It may replace some jobs eventually. But in the same way that they've been developing driverless cars for years, and one of the huge problems is, if a driverless car gets into an accident, who can you sue? When your audit goes wrong, people want a pound of flesh. I don't think, at the moment, any software firm is going to allow themselves to be sued if their AI program didn't pick something up. And so it's still going to be the humans at the audit firms signing off audit reports. And so the humans are going to want absolute certainty, as far as saying, there's going to be a lot of checking in with the humans. So what does that mean in day-to-day life? Well, it means that hopefully the computers will do all of the grunt work, they'll do the awkward bits, and they'll present to you what they found, and then it will be up to us to do the judgemental bit. Well, that's always been the most interesting bit anyway, so hopefully audit will actually become more interesting than it is today. And I don't mean to say that it's not interesting today, speaking to clients is actually genuinely interesting, but it will you'll have more of that and less of tying through hundreds of invoices to all the other bits. So I'm very positive about how it may move. I'm not too worried about auditors losing their jobs to AI in particular.
Neil Johnson (09:22)
And up to you, Becca, what would you say? What have you got your eye on over the next coming years?
Becca Durrant (09:28)
I think I've been talking for ages now about how we should be advisors. People used to go to their bank managers, and people don't have those bank managers to go to anymore. And I say this so many times, and we need to be the people that are those advisors and clients want, and that actually is the fun bit of the job. So I think for me, the future is going to be again, a positive thing, that we're not going to be having to crunch through the boring bits, the processing, the copying invoices into systems, crunching out some numbers at the end. Instead, that's going to be more automated, more client driven, I think clients are going to want to do more of that bit themselves because they can, and why not, because they've got the systems there to do it. But it's going to be more about helping those people at an earlier stage do the advisory. So where we didn't do the advisory till you hit manager level, you're actually going to get the opportunity to do that a much earlier point, and we're going to have the data to do that. So these AI tools, a lot of them will give us data to make us feel more confident in talking to our clients about what the data means and the future, rather than looking into the past, which, as accountant in the advisory side, we've done a lot of looking at 'this is what's happened, here's your statutory account filing'. But instead, we can be able to say, 'well, what are you doing right now? And how can we help you? How can we help your business grow?' So again, a bit like James, I'm quite excited. I think we can work with those growing business entrepreneurs and become their advisors, be more involved in their business, which I think is the fun bit.
Neil Johnson (10:58)
Yeah, that makes complete sense to me. You can get information at the click of a button, now. Whereas it would have taken a long time to sift through spreadsheets to find it, and you might not find some of these little connections with data, you might not find some of this insight as easily or at all. I think, with that in mind for all the talk about robots coming to take our jobs - roles will change, perhaps, but if you could talk a little bit about what that might mean, are there are any new roles that might that might pop up, or hybrid roles?
Becca Durrant (11:26)
I think it's fair to say roles have changed in the past 10 years a lot as well. So it's only going to be similar to what we've had. When I first started out, 14 years ago, I spent four days a week in accountancy firm doing the admin, doing the filing, and then I'd get to look at the accounts, but that won't be needed anymore. So at an earlier stage, the roles are going to be different, and it's going to be more involved. The role I'm doing right now, for example, a Cloud Accounting Manager didn't exist five years ago. So there is much more opportunity for roles like I'm doing, which is going out and looking at what's out there, and helping these sorts of cloud accounting platforms and technology driven things out for our clients. So I think it's really easy for the media to say 'that's it, our jobs are all going to be gone', but I know from personal experience that nothing is that quick to take off.
Neil Johnson (12:13)
That's a good point. Fahad or James, do you have anything to add?
Fahad Riaz (12:16)
What I have also seen, it's very similar. It's basically - roles are going to demand more value out of you as a person. I mean, we go through all these educational training materials, and we learn so much, but when it comes to your very bare minimum accounting roles, you just see mindless work happening, at least it was the case two years back even here in the Middle East. I mean, it's not very far back when I was doing an accountant role, I think four years back, and you come to work, you clock in, you shut your mind off, and you're just following some rules based routine tasks. So as a person, you were not giving a lot of value. So this is what's changing, because even if you just pick up job descriptions recently, even if you're an accountant, and if you're applying for a position, they ask you for some analytical skill sets, they say, 'you should be able to do something with the information that you will be working with, you should be able to do their minimum analytical reports, you should be able to have maybe Power BI or some dashboard visualisation skill sets in your arsenal now, because you having ACCA or CA might just not be enough. So we're seeing a lot of value as a person. They want to pick your brains now. So it's all about adapting and growing as a person, and making sure you're giving out more value. Because, as accountants, we were not always very open to using our values, because nobody was really hearing us. But now that's changing, with all these routine tasks being taken care of, we now have time on our hands to actually shine.
Neil Johnson (13:54)
Yeah, it can't be stressed enough, how much of a change having all these little tasks taken away. I can only imagine it frees up a vast amount of time for people to apply themselves and their skills, add value. Is this something you agree with, James?
James Berridge (14:09)
Touching on the point you made there. And we're seeing this already with tools that already exist, particularly in the audit market. There is a very popular tool called DataSnipper, and that's taken a lot of the repetitive checking of data from the general ledger to invoices, whatever it is you're trying to do, and it takes a lot of that away. And that's excellent. The media would have you believe that means we're going to lose our jobs to a tool like that, whereas actually there's two things happening. It is taking away those tasks, so people do have more time. And arguably, that means, in the future, we may need less people, but we're already getting less people. There has been a trend of less people coming into the profession massively. So actually, what this technology is doing, it's allowing the people we have already in the profession to actually keep up the level of productivity that we perhaps had a few years ago, when we had more bodies. This technology is not driving people out of jobs. It's it's allowing less people to do the work of more. I think that as more technologies come in and are more sophisticated, that trend will probably continue. Hopefully those tools will also make accounting, make audit more generally, slightly more attractive to go into, because a lot of the more dull aspects of the work are being eradicated, so hopefully we can change that as well.
Neil Johnson (15:27)
Well it leads on really well to the final and the large point about, if you're a young professional nowadays, how do you position yourself for this employment landscape? What skills can you learn? How do you gain the experience, and also, what sort of training and learning can you expect to receive from employers?
James Berridge (15:45)
I think most of my career movements have all been based on knowing slightly more Excel than the person I was sat next to. But back to your point on a slightly more serious note, accountants will always benefit from being fairly strong on Excel. As an auditor, you're using it mostly as a work paper entry tool, a lot of it you could probably do in Word, if you had the patience. But being able to do that fairly rapid analysis of what it is I'm looking at, what trends are there, does help you do certain bits faster and to Fahad's point before, you've got stuff like Power BI, which is actually free, you can download it. And ironically, Excel is not free, you have to pay for it. You could just download Power BI and there is endless YouTube content that will give you 'how to load data in using Power Query', 'how to create some graphs', 'how to get some visualisations to start understanding data'. Of course, there are then formal courses as well. Sometimes you need a formal course with a certificate at the end to at least prove that you have a baseline. But there's a lot of learning you can do. Does everyone need to be an expert on Power Bi? No, I don't think so. But at least being able to create a couple of bar charts and a pie chart, donut chart, whatever it is, would give you such a leg up. Having an extra few minutes and doing it in Power BI just sets you up then for being able to take it to the next level.
Neil Johnson (17:08)
Yeah, I like the point about YouTube there. I wonder if some point in the not too distant future, CVs will accept 100 hours of YouTube, on your way to being a 10,000-hour expert, because I use YouTube all the time for learning how to do things, even just putting up a picture on the wall. Fahad, in your career, how have you embraced technology?
Fahad Riaz (17:29)
So I put myself into a master’s course, I went to the UK, I studied for a year, and then I picked up on about 12 different software packages, so I was working with Ford, a simulation engineering team, so I was working on all tricks. Then I was doing Power BI. I was also doing Python. And once you get your hands on a couple of software tools. For example, if you know how to use Power BI, if I give you Google Data Studio, which is a different dashboarding tool, it'll take you a few minutes, but you would be able to set yourself up. And the key takeaway that I had, which sort of builds on what James was saying, it's a free tool, Power BI, you can download it, there's a lot of free data available, and then you can look at some YouTube videos and get that skill sorted for yourself. But what people don't do, a lot of students, they look at AI buzzwords, and they say they want to become the best, they want to go straight for the artificial intelligence. They say, 'we want to build a machine learning model'. And with a lot of no-code tools these days, it's a matter of dragging and dropping, and then you might have something in terms of a machine learning output, but validating that - how much sense it makes. There's little depth to these people. So going back to what you were referring to - how students should look into upskilling, I think they should drill, break this whole AI space down, pick things that make sense to them, and be very real, if your end goal is to work in this space, start looking at the kind of jobs that are out there, start reading their job descriptions, because then you'll be able to see what kind of things the companies are looking for, and you'll start making small improvements. Because if you start chasing predictive analytics from day one, you're going to be really lost, because there are lots of layers into getting there. And some people are not even great with their basic analytics, even in Excel, so there's no point in jumping the gun, because, again, like we've all discussed, we are going to be here for a few years before anybody becomes an expert at this. We are only uncovering so many challenges on a daily basis. So, this is just a long race. It's a marathon, so there's no need to sprint and start jumping the gun.
Neil Johnson (19:41)
That's good advice.
Becca Durrant (19:42)
Yes. James?
James Berridge (19:42)
Just jumping in on that, just to reiterate what Becca was saying. So as long as you understand what a client's data means, not how to analyse it, increasingly, a lot of the tools are building so you don't necessarily need to be able to write Python, so I mean, all the Microsoft ones are branded Copilot, but others are sort of using similar branding, for example, to get the most out of the client data, because a lot of these tools are being built into software you already know. So instead, you can ask the question of the software - please forecast my sales into next year. You don't need to know how to code that, but you need to know what's important to your client, and then you need to know how to tell the client such that they understand what you're doing, and why it is important. I think it's going to split. You're going to have the people who know the detail, and they'll be able to do more sophisticated reporting analysis, but for when you don't need that, and to Becca's point, the soft skills become more important, because you can ask Copilot for Excel, can you forecast sales into next year and show me the error bars on it? Brilliant. And you've got fancy Python doing your machine learning predictions for you. You didn't need to know any of that. You just needed to know to ask for it - totally different. I would just say, for those who have so far avoided dabbling with the hyped up AI, I would definitely play with the likes of, whether it's Bing on your home account or ChatGPT, just to be aware of what it can and cannot do. Obviously, don't put confidential information in it unless you're in a secured environment, check with IT if you're part of the firm. Be aware of what it can do, because you don't want to let everyone else take advantage of these tools when they get really good at everything. Where it can save you time, don't be afraid of it, use it. You're probably not afraid to use Google to ask it for help. Try one of these as well and see how the outputs differ.
Becca Durrant (19:42)
I was going to touch on a point in that respect. So from my background, I'm not as great at the software, I can use things, but James could tell you that I ask him lots of questions still on Excel and Power Query and things like that. So I think there's another perspective to look at this from, in terms of soft skills. Actually, you don't need to be the most technical person, it is not something we should all be scared of. Thinking we've all got to be amazing at IT, it doesn't need to be that. I think it's also thinking about those soft skills, 'what is it going to enable me to do?' And I've talked about advisory - what sort of skills do I need to have to be able to talk to clients? And a machine isn't going to replace a human in terms of empathy and building relationships. So that is something that, in my opinion, is going to be around for a long time. So I think there are always soft skills that you can work on, and something that I think is just as important as trying to obscure yourself in anything more technical. Often you'll get your job based on your soft skills, because it will be how you come across the interview - how do you speak? If you spoke to a client? Would they like you for a start? Are you able to convey what you know to a client? So I think that is something probably to focus on when you're first starting out as well.
Fahad Riaz (22:56)
No, I agree. These tools are there to help us. No need to be afraid, because there's nothing that can really go wrong, especially if you think you're worried about playing it with your own data. There's a lot of free data available online these days, lots of videos. Until you start, you're never going to really uncover what they can do. And I've seen people, peers, once they started even with Excel, they started playing around with their Visual Basic, and they learned that they can just record my steps and then play them and it does their task for them, they were really hooked.
Neil Johnson (23:16)
And over to you, Becca.
Becca Durrant (23:29)
Just echoing the others, really. It's just not to be afraid of these things, and not to listen to the media that you're going to get replaced. But more, how do we embrace it and use it to help us be better at what we're already doing? I think it's just not having the fear. Actually, it's going to make things more exciting, I think.
So that's it for today. Keep an eye out for our next episodes, where we'll be deep diving into CV and LinkedIn do's and don'ts. Thanks for listening. For more careers advice, check out the ACCA Careers website and the Student Accountant app. And if you have something in particular you'd like me to cover in the series, get in touch at studentaccountant@accaglobal.com