WEBVTT - …will AI take all the jobs? 0:00:01.139 --> 0:00:04.290 Hey, there. I'm Maiki Lynch and I'm an accountant. And 0:00:04.290 --> 0:00:07.140 in this series from ACCA, I've been sitting down with 0:00:07.140 --> 0:00:09.898 other accountants and people who work in finance to hear 0:00:09.900 --> 0:00:12.630 about their journeys in the world of work, and bust 0:00:12.630 --> 0:00:17.129 some common myths about these careers along the way. This 0:00:17.129 --> 0:00:19.920 week is our final episode, and it's a rather special 0:00:19.920 --> 0:00:22.169 one because we are going to be squaring up one 0:00:22.170 --> 0:00:24.810 of the biggest questions facing not just those working in 0:00:24.810 --> 0:00:28.139 accounting and finance, but has the potential to change almost 0:00:28.139 --> 0:00:32.550 every area of our lives. That's right, it's artificial intelligence. 0:00:33.120 --> 0:00:36.390 These days it seems like AI is always in the news, 0:00:36.570 --> 0:00:41.070 whether it's ChatGPT helping students write essays, or big manufacturing 0:00:41.070 --> 0:00:45.930 companies changing their processes. But is AI going to have a big role to play in 0:00:46.500 --> 0:00:48.960 the future of finance? Is it going to help or 0:00:48.960 --> 0:00:51.598 be a hindrance? And what could it mean for careers 0:00:51.598 --> 0:00:56.730 in accountancy? Let's find out. This is By All Accounts. 0:01:00.990 --> 0:01:04.048 Depending on how it's discussed, the changes AI may bring 0:01:04.050 --> 0:01:06.929 to our lives can feel either like a golden opportunity 0:01:07.230 --> 0:01:10.289 or a looming threat. So when it came to careers 0:01:10.289 --> 0:01:14.010 in accounting and finance, I've gone to the experts. First 0:01:14.010 --> 0:01:18.270 up I have ACCA's own Head of Technology Research, Alistair Brisbourne, 0:01:18.690 --> 0:01:21.630 who's been digging into what AI means for the future 0:01:21.630 --> 0:01:23.520 of accountancy. Hello, Alistair. 0:01:23.520 --> 0:01:24.480 Hello, Maiki. 0:01:24.480 --> 0:01:28.799 And also Imtiaz Ahmad. Imtiaz qualified as an accountant back 0:01:28.799 --> 0:01:31.800 in 2007 and has worked in both the private and 0:01:31.800 --> 0:01:35.069 public sectors, all the way from junior roles to top 0:01:35.069 --> 0:01:38.130 executive levels. He's here to share his views on how 0:01:38.130 --> 0:01:40.980 the industry has changed over the years and is continuing 0:01:40.980 --> 0:01:42.660 to change. Hello, Imtiaz. 0:01:42.990 --> 0:01:43.350 Hi. 0:01:43.709 --> 0:01:47.400 Welcome. So Alistair, I'm going to come to you first. 0:01:47.549 --> 0:01:50.400 I know AI is everywhere these days, but it can 0:01:50.490 --> 0:01:53.070 feel a little bit of a black box to some. 0:01:53.730 --> 0:01:57.240 Can you give me a really straightforward explanation as to 0:01:57.240 --> 0:01:57.840 what AI is? 0:01:58.320 --> 0:02:03.089 Well, that's a challenge. Basically, AI is about using a 0:02:03.089 --> 0:02:06.780 computer, the strengths of computers, to do things that used 0:02:06.780 --> 0:02:10.800 to be done by human intelligence. I think something that 0:02:10.800 --> 0:02:12.960 we're also aware of that's accessible to all of us 0:02:12.960 --> 0:02:15.899 is thinking about smart playlists. Whether you're using Spotify or 0:02:15.900 --> 0:02:20.820 Apple Music, these playlists, they know what music you like 0:02:21.330 --> 0:02:24.149 and they know why you like it because they're assessing 0:02:24.150 --> 0:02:27.030 the music that you're listening to, they're assessing the music 0:02:27.030 --> 0:02:30.060 that other people listen to, in order to make suggestions 0:02:30.060 --> 0:02:32.190 as to other songs that you might like. So what 0:02:32.190 --> 0:02:35.728 it's doing is there's this algorithm that's learning from data, in 0:02:35.849 --> 0:02:39.359 this case your music choices, and then it's making suggestions 0:02:39.360 --> 0:02:42.299 as to other songs you might like. And that applies 0:02:42.299 --> 0:02:44.880 to basically all forms of artificial intelligence. It's as simple 0:02:44.880 --> 0:02:50.340 as a machine understanding patterns within data. And so as 0:02:50.340 --> 0:02:53.130 you say, it's pervasive in our lives, whether it's the 0:02:53.130 --> 0:02:55.950 mapping systems we use to get here today to understand 0:02:55.950 --> 0:03:00.209 traffic flow information, to understand route guidance, all this is 0:03:00.210 --> 0:03:04.380 infused with AI. Or the quirky questions we ask our 0:03:04.380 --> 0:03:09.480 Siri and Alexa and Google assistants, that's all AI- based. 0:03:09.480 --> 0:03:12.870 Or we had the Beatles release a song last year, 0:03:12.870 --> 0:03:16.199 for example, thanks to a machine learning tool that was 0:03:16.199 --> 0:03:19.440 able to extract data from an old hissy tape and 0:03:19.440 --> 0:03:23.250 turn it into a new track. And so AI is 0:03:23.250 --> 0:03:27.630 basically using the strengths of AI to recognize patterns within 0:03:27.630 --> 0:03:30.240 large data sets and extract that in a useful way 0:03:30.240 --> 0:03:30.809 for us. 0:03:31.799 --> 0:03:33.990 What's this got to do with accounting and finance and 0:03:34.169 --> 0:03:34.591 the roles that we have? 0:03:34.591 --> 0:03:37.980 Well, I mean, the core of our job is to look at 0:03:38.310 --> 0:03:40.950 huge amounts of financial data, as well as other forms 0:03:40.950 --> 0:03:43.470 of data these days. We're looking at more unstructured data 0:03:43.470 --> 0:03:47.819 sets like text these days and imagery and things like 0:03:47.820 --> 0:03:51.660 that. And so being able to extract insight from that 0:03:51.660 --> 0:03:55.140 data is absolutely fundamental in the accountancy role, and it 0:03:55.140 --> 0:03:58.260 will be even more so moving forward. If you think 0:03:58.260 --> 0:04:01.380 about some of these routine tasks that accountants are involved 0:04:01.380 --> 0:04:06.480 in, the data entry tasks, reconciling debits and credits, and some 0:04:06.480 --> 0:04:08.910 of these basic things that everyone has to learn along 0:04:08.910 --> 0:04:12.900 the way, AI is really useful in not just saving 0:04:12.900 --> 0:04:16.799 time, but also reducing errors and increasing accuracy in those 0:04:16.800 --> 0:04:20.970 processes, so it's fantastic. And then we can apply it 0:04:20.970 --> 0:04:25.349 to things like fraud, so identifying anomalies within data sets, 0:04:25.650 --> 0:04:29.609 improving our risk management processes. We can use it to 0:04:29.760 --> 0:04:33.360 help interpret tax law, to help fill out forms. So 0:04:33.360 --> 0:04:35.520 there are a myriad ways in which AI can help 0:04:35.520 --> 0:04:38.669 the accountancy profession, I think we're just scratching the surface 0:04:38.670 --> 0:04:39.240 at the moment. 0:04:40.050 --> 0:04:41.758 I love what you've talked about there because it sounds 0:04:41.759 --> 0:04:45.210 like we're going beyond just efficiencies that can be made, 0:04:45.210 --> 0:04:47.639 perhaps some more the entry level roles there. 0:04:48.089 --> 0:04:51.839 Yeah, absolutely, absolutely. Efficiency is the immediate go- to we 0:04:51.839 --> 0:04:54.960 think about when we think about AI and automation, but 0:04:54.960 --> 0:04:59.190 really it's about enabling better strategic advice. It's about moving 0:04:59.428 --> 0:05:04.529 beyond just the transactional aspects of the role and actually 0:05:04.740 --> 0:05:09.750 providing that business acumen, that strategic acumen, that accountants actually 0:05:09.750 --> 0:05:12.450 do have. They have a solid understanding of their organization 0:05:12.690 --> 0:05:14.430 because of the information that they're working with. 0:05:15.690 --> 0:05:17.459 Imtiaz, I'd like to come to you if I may. 0:05:17.969 --> 0:05:21.630 You've been in senior accounting roles for some time. What 0:05:21.630 --> 0:05:23.789 conversations have you been hearing about AI? 0:05:24.809 --> 0:05:28.890 Well, it depends on the context. Usually AI is taken 0:05:28.890 --> 0:05:32.190 as a threat. Every time, if you see the last 0:05:32.220 --> 0:05:36.089 50 to 70 years of human history where we have evolved so 0:05:36.089 --> 0:05:40.109 much technological development and everything around it, whenever there is 0:05:40.109 --> 0:05:42.720 a new technological development, new advancement, there is a new 0:05:42.720 --> 0:05:45.839 milestone, it's always taken as a threat first. And then 0:05:45.839 --> 0:05:47.790 later on people realized, " Oh, no, no, no, no. It was 0:05:47.790 --> 0:05:50.759 a mistake. It's better for us to enable us to 0:05:50.760 --> 0:05:53.849 help us to facilitate the processes." So the same thing 0:05:53.849 --> 0:05:58.498 is with AI. You see now we are, as Alistair 0:05:58.500 --> 0:06:01.320 has said, that we are more of at the initial stage 0:06:01.320 --> 0:06:05.310 of scratching the surface. There are so much more we 0:06:05.310 --> 0:06:08.190 are going to do, not only in accountancy, but in 0:06:08.190 --> 0:06:12.629 every other aspect of life. The reconciliations between one account 0:06:12.630 --> 0:06:15.630 to another account, between one organization to another organization, is 0:06:15.630 --> 0:06:18.599 going to be automated. We are going to be working 0:06:18.600 --> 0:06:22.890 more on analytical side than the data processing itself. 0:06:24.480 --> 0:06:27.150 And within your own work, has it changed your own work, has it? 0:06:27.151 --> 0:06:31.259 Oh, so much, so much, so much so. I remember when 0:06:31.259 --> 0:06:35.609 I started working right after my qualification in 2007, I 0:06:35.609 --> 0:06:40.380 was working in public sector in one of the organizations in Pakistan. And I 0:06:40.380 --> 0:06:42.748 mean, you will be surprised, it was not that old 0:06:43.020 --> 0:06:45.990 time, but still people were using the ledgers, the hardcore 0:06:45.990 --> 0:06:50.279 printed ledgers, and we were doing actual reconciliation between bank 0:06:50.279 --> 0:06:52.799 and the ledger by hand on the ledger, on the- 0:06:52.799 --> 0:06:55.859 I'm not surprised. When I learned bookkeeping, I would go out 0:06:55.860 --> 0:06:59.190 and bookkeeping was in books, if you could imagine - books! 0:06:59.490 --> 0:06:59.940 Exactly. 0:07:00.270 --> 0:07:03.059 Yes. And that T- account that you learn about in 0:07:03.059 --> 0:07:06.118 college, that is the spine of the book. That's where 0:07:06.120 --> 0:07:06.960 the T- account comes from. 0:07:06.960 --> 0:07:12.510 True, true. I mean, it's like 14, 15 years ago only, 0:07:12.840 --> 0:07:15.179 and now, a few years back, I was working with 0:07:15.180 --> 0:07:17.970 one of the Big Four consulting firms, and one of 0:07:17.970 --> 0:07:20.700 the assignments we were working ... One of the Sovereign Wealth 0:07:20.700 --> 0:07:24.660 Fund for preparing their financial policies and procedures, and took 0:07:24.660 --> 0:07:28.950 us at least two to three months to first prepare 0:07:29.010 --> 0:07:33.720 the data process flow diagrams, and then explain them into 0:07:33.720 --> 0:07:36.900 the policies and procedures. And that was so much manual 0:07:36.900 --> 0:07:40.229 work. We were writing from our own heads, " Okay, the data is 0:07:40.230 --> 0:07:43.560 moving here," and there is approval and everything. Now you'll 0:07:43.679 --> 0:07:46.289 surprised to know that you can take the picture of 0:07:46.289 --> 0:07:49.500 the data flow diagram and give it to ChatGPT or 0:07:49.500 --> 0:07:52.590 any other relevant AI, and then it will write you 0:07:52.740 --> 0:07:54.870 just like that, give it in two minutes. 0:07:55.350 --> 0:07:56.940 Wow. Such a time saving. 0:07:57.030 --> 0:07:59.339 Of course. And then what we are going to do 0:07:59.340 --> 0:08:02.190 with that, we are going to purify that, we are 0:08:02.190 --> 0:08:06.029 going to add value to that. It doesn't mean that we are going 0:08:06.029 --> 0:08:08.280 to be out of job because AI has replaced that 0:08:08.280 --> 0:08:11.520 processing of the data, that writing down the policies and procedures 0:08:11.520 --> 0:08:14.490 manually. No, we are going to work on much higher 0:08:14.490 --> 0:08:17.460 level quality. So output is going to be a niche 0:08:17.460 --> 0:08:19.770 level of the quality actually in the coming time. 0:08:20.099 --> 0:08:21.541 So we're freeing up our time- 0:08:21.541 --> 0:08:21.542 Of course. 0:08:21.542 --> 0:08:24.900 ... to add value to the business, rather than having to 0:08:25.500 --> 0:08:27.179 be involved in such labor- intensive tasks. 0:08:27.180 --> 0:08:28.470 Exactly, exactly. 0:08:28.590 --> 0:08:30.750 I love that. Alistair, I want to come back to 0:08:30.750 --> 0:08:33.900 you. You've done some research on how potential students feel 0:08:33.900 --> 0:08:36.150 about AI. Just wondering what have you found? 0:08:37.950 --> 0:08:40.348 It's interesting, and it's interesting, I'm listening to what Imtiaz was saying as 0:08:40.349 --> 0:08:44.280 well because there are obviously a few different challenges here. To answer 0:08:44.280 --> 0:08:48.088 the question directly, Generation Z does seem to be slightly 0:08:48.090 --> 0:08:51.599 more concerned about the impact of AI than other generations. We 0:08:51.599 --> 0:08:53.790 look at our talent trends work, in the last two 0:08:53.790 --> 0:08:57.600 years it's that generation that expresses the most concern about 0:08:57.960 --> 0:09:02.700 technological development in general, but AI specifically. And that's slightly counterintuitive- 0:09:02.970 --> 0:09:02.971 I agree. 0:09:02.971 --> 0:09:06.150 ... because we tend to think they're coming in with a 0:09:06.150 --> 0:09:10.410 skillset or an awareness of these technologies that maybe older 0:09:10.410 --> 0:09:13.530 generations don't have, so we are surprised to see that. 0:09:13.679 --> 0:09:17.129 And when we dig into it and ask the questions and 0:09:17.129 --> 0:09:19.890 we get into the discussions, it does seem that there 0:09:19.890 --> 0:09:23.578 are a couple different reasons for that. One is that 0:09:23.580 --> 0:09:26.460 there is a concern that their career path is going 0:09:26.460 --> 0:09:29.460 to be disrupted by automation or AI. That there's a 0:09:29.460 --> 0:09:32.009 lot of talk about those entry- level jobs being affected, 0:09:32.009 --> 0:09:34.649 and they're very aware that that could mean them. And 0:09:34.649 --> 0:09:37.620 so what does their career look like in the future 0:09:37.620 --> 0:09:39.780 is a challenge. Then the other side of it's the 0:09:39.780 --> 0:09:44.490 skill side. There is this impetus to be more tech- 0:09:45.120 --> 0:09:48.660 aware, to have that tech skillset. That's exciting for some 0:09:48.660 --> 0:09:52.109 people, but it's not exciting for everyone. And so I 0:09:52.109 --> 0:09:54.780 think part of it is the messaging and the communication 0:09:54.990 --> 0:09:58.320 in that there's actually a huge opportunity and this next 0:09:58.320 --> 0:10:01.470 generation is going to be really, really important to how 0:10:01.470 --> 0:10:04.500 AI is adopted. And we've already discussed how AI is 0:10:04.500 --> 0:10:08.039 really fundamental to the evolution of the accountancy profession, but 0:10:08.040 --> 0:10:10.379 they're going to be at the heart of devising the 0:10:10.379 --> 0:10:14.610 solutions, the new ways of working, but also in leveraging 0:10:14.610 --> 0:10:17.429 those new insights, as Imtiaz was saying. So they are 0:10:17.429 --> 0:10:20.309 going to have an opportunity earlier in their career to 0:10:20.309 --> 0:10:24.540 actually take on more strategic roles, not to be bogged 0:10:24.540 --> 0:10:26.578 down in some of the more manual tasks that a 0:10:26.580 --> 0:10:30.060 lot of people who qualified earlier were in their careers. 0:10:30.240 --> 0:10:34.920 So actually we need to communicate more the exciting opportunity that exists 0:10:34.920 --> 0:10:37.439 for people that are coming into the profession now because 0:10:37.440 --> 0:10:40.170 it does seem like job security and skills challenges are 0:10:40.170 --> 0:10:42.780 the major concerns that Gen Z are expressing when they 0:10:42.780 --> 0:10:43.980 think about AI. 0:10:44.730 --> 0:10:47.429 And I don't know if your research touches on this, 0:10:47.429 --> 0:10:49.979 but does this compare to what we're seeing in other 0:10:49.979 --> 0:10:52.169 industries outside of accounting and finance? 0:10:52.259 --> 0:10:55.650 I mean, I think a really, really good comparison is 0:10:55.650 --> 0:10:58.920 the legal profession. It's similar in the sense that we're 0:10:58.920 --> 0:11:00.509 at a similar stage in terms of the adoption of 0:11:00.509 --> 0:11:03.000 AI, but also some of the ways in which AI 0:11:03.000 --> 0:11:05.098 is starting to make a difference is similar. So we 0:11:05.100 --> 0:11:08.458 think about routine tasks in the legal profession, there's a 0:11:08.460 --> 0:11:11.610 lot of contract or document review that has to take 0:11:11.610 --> 0:11:17.189 place. While we're reconciling data, entering data, they're doing what 0:11:17.190 --> 0:11:22.769 are very manual, time- intensive review tasks. They're also more 0:11:23.369 --> 0:11:27.840 heavily involved in compliance and risk management. And so there 0:11:27.840 --> 0:11:30.120 are big similarities in terms of the way the professions 0:11:30.120 --> 0:11:32.578 are going. And most law firms used to have big 0:11:32.580 --> 0:11:35.219 libraries at the heart of them, and then they moved 0:11:35.219 --> 0:11:38.819 online to things like LexisNexis and databases, and now they're 0:11:38.820 --> 0:11:41.369 adopting things like generative AI in order to help them 0:11:41.369 --> 0:11:45.480 extract information from those databases more efficiently or more effectively. 0:11:45.840 --> 0:11:49.080 And so it's very similar to what accounting and finance 0:11:49.080 --> 0:11:53.190 professionals are trying to do right now, so I wonder 0:11:53.190 --> 0:11:56.490 if these two will evolve together. We could learn a 0:11:56.490 --> 0:11:58.409 lot from each other probably in the way we're moving. 0:11:58.919 --> 0:12:00.689 How do you think things are likely to change, if 0:12:00.689 --> 0:12:03.060 you can perhaps look forward? 0:12:03.240 --> 0:12:07.590 Yeah. Imtiaz has already pointed to some really important changes 0:12:07.590 --> 0:12:10.500 that are starting to happen, AI is really going to 0:12:10.500 --> 0:12:15.750 enable that, and that is using AI- generated insights in order to 0:12:15.750 --> 0:12:19.860 provide greater value. The big challenge we have is that, 0:12:19.860 --> 0:12:22.290 as I said at the beginning, we're faced with huge 0:12:22.290 --> 0:12:24.780 amounts of data, and getting our heads around it and 0:12:24.780 --> 0:12:28.889 extracting the most useful insights for our organization is really 0:12:28.889 --> 0:12:32.099 difficult and really time- consuming at the very least, and 0:12:32.099 --> 0:12:35.579 impossible in some cases because there's too much information. And 0:12:35.580 --> 0:12:40.770 so AI is really a huge step- up in our 0:12:40.770 --> 0:12:45.450 ability to actually guide organizations to provide a trusted source 0:12:45.450 --> 0:12:49.530 of advice, and also to provide greater value out of 0:12:49.530 --> 0:12:53.669 the proprietary data that organizations have access to. And without 0:12:53.670 --> 0:12:56.970 AI, we can't do that. So it's actually a really, 0:12:57.030 --> 0:12:59.850 really important thing that we need to learn how to 0:12:59.850 --> 0:13:00.870 use more effectively. 0:13:01.410 --> 0:13:03.450 Where can people go to find out more about this? 0:13:03.840 --> 0:13:08.309 Well, we've recently released an ACCA guide to AI in 0:13:08.309 --> 0:13:11.218 finance, I believe that was released in August last year, 0:13:11.219 --> 0:13:13.230 which covers some of the ways in which we think 0:13:13.230 --> 0:13:16.348 AI is going to change the profession, but also some 0:13:16.350 --> 0:13:20.820 of our principles as an organization towards the adoption of 0:13:20.820 --> 0:13:22.649 AI and what we think needs to happen in order 0:13:22.650 --> 0:13:25.349 to take advantage of it. There's also the Digital Horizons 0:13:25.349 --> 0:13:28.379 report, which was released in September, which touches on some 0:13:28.379 --> 0:13:31.110 of the practical ways in which AI is likely to 0:13:31.110 --> 0:13:33.179 impact the profession, as well as some of the different 0:13:33.179 --> 0:13:36.690 characteristics in terms of organizations that are leading the way 0:13:36.750 --> 0:13:39.660 in that regard. And it also touches on generative AI, 0:13:39.660 --> 0:13:41.969 the hot topic at the time, as to why is 0:13:41.969 --> 0:13:44.520 it exciting, why should we pay attention to it? Is 0:13:44.520 --> 0:13:47.250 the hype real or is there substance behind it? And so 0:13:47.250 --> 0:13:50.070 this is available on the ACCA website and the P&I, the 0:13:50.070 --> 0:13:53.218 policy and insights pages, and we have more work upcoming 0:13:53.220 --> 0:13:55.348 this year certainly that's going to cover AI in much 0:13:55.350 --> 0:13:56.040 greater depth. 0:13:56.520 --> 0:13:58.469 Imtiaz, I want to come back to you. What do 0:13:58.470 --> 0:14:00.389 you think about these coming changes? 0:14:00.599 --> 0:14:03.690 In coming years of time, there will be more work 0:14:03.690 --> 0:14:07.410 on the analytical side. You are going to see where are 0:14:07.410 --> 0:14:11.250 the gaps, where are the inefficiencies, where are the improvement areas. 0:14:12.090 --> 0:14:16.950 And then work on those rather than doing the hardcore 0:14:17.130 --> 0:14:18.750 laborious work on your own. 0:14:19.170 --> 0:14:20.910 What do you hope for the future of AI? 0:14:21.360 --> 0:14:24.270 As I mentioned earlier, I mean, AI is going to 0:14:24.270 --> 0:14:27.210 be one side. I mean, in the coming days you 0:14:27.210 --> 0:14:33.330 will seeing ChatGPT stores coming just like App Store and 0:14:33.330 --> 0:14:35.789 those kind of plugins are going to be integrated with 0:14:35.790 --> 0:14:40.619 the ChatGPT and other AI platforms. It is going to 0:14:40.619 --> 0:14:44.760 be integrated in every process. It's going to touch accounting 0:14:44.760 --> 0:14:49.080 side, finance side, analysis side, budgeting side. It's going to 0:14:49.230 --> 0:14:53.670 touch every aspect within our profession. We have multiple lines 0:14:53.670 --> 0:14:57.059 within our profession. We have taxation, we have the accounting, we 0:14:57.059 --> 0:15:00.090 have audit. Within audit, we have internal audit, external audit. 0:15:00.660 --> 0:15:02.640 I mean, you name it. It's not going to be 0:15:02.640 --> 0:15:05.610 restricted on one pillar of the profession, it's going to 0:15:05.610 --> 0:15:08.849 affect all. How? I'm sure it is going to be 0:15:08.849 --> 0:15:12.930 a positive change and that will be a very pleasant 0:15:13.440 --> 0:15:17.460 and welcoming towards the new generation who are aspiring to 0:15:17.760 --> 0:15:19.140 join the profession actually. 0:15:20.070 --> 0:15:22.650 Thank you so much. Just from what you've both said, 0:15:22.650 --> 0:15:25.890 it makes me think that perhaps each generation we need 0:15:25.890 --> 0:15:29.430 to be thinking about becoming that purple person, having that 0:15:29.639 --> 0:15:32.549 balance between our accounting and finance skills, and also an 0:15:32.549 --> 0:15:37.890 awareness and ability within technology and that space as well. 0:15:38.880 --> 0:15:41.070 Just want to come to you both and ask, is 0:15:41.070 --> 0:15:44.550 AI going to take all of the accountancy jobs? Imtiaz, 0:15:44.550 --> 0:15:45.720 can I come to you first? 0:15:45.809 --> 0:15:49.200 Yeah, sure. It's not going to replace humans at all. 0:15:49.889 --> 0:15:54.389 I am a big believer of enabling technology for helping 0:15:54.389 --> 0:15:58.350 the humans to do much more than they originally have 0:15:58.350 --> 0:16:01.890 been doing it before. It's going to be an enabler 0:16:01.890 --> 0:16:05.940 rather than destroyer. It's going to be as support towards 0:16:05.940 --> 0:16:10.980 humans rather than replacing the humans. It's going to see 0:16:10.980 --> 0:16:15.300 that wherever there is repetitive nature of works, wherever there 0:16:15.300 --> 0:16:21.120 are laborious processes, and give more of analytical side and 0:16:21.120 --> 0:16:24.600 more of that side, which AI cannot do that. No, 0:16:24.900 --> 0:16:28.920 there's so much creativity, so much things which humans can 0:16:28.920 --> 0:16:31.710 do and AI cannot do, and AI will never be able 0:16:31.710 --> 0:16:36.300 to do that side of the work. There is the 0:16:36.300 --> 0:16:38.460 gap we are going to fulfill, and that is going 0:16:38.460 --> 0:16:41.579 to be the side where we need to focus in 0:16:41.580 --> 0:16:42.210 the coming time. 0:16:43.140 --> 0:16:44.669 And, Alistair, can I come to you with the same 0:16:44.670 --> 0:16:47.999 question, is AI going to take all of the accountancy jobs? 0:16:48.059 --> 0:16:50.910 Yeah, look, I couldn't agree more. I mean, artificial intelligence 0:16:50.910 --> 0:16:54.180 is not human intelligence. They are different things and they 0:16:54.180 --> 0:16:57.630 are good at different things. AI is a huge enabler, as 0:16:57.630 --> 0:17:01.620 Imtiaz says, it's great for augmenting certain tasks or certain 0:17:01.620 --> 0:17:05.549 capabilities because it can extract insights from huge data sets 0:17:05.940 --> 0:17:08.820 that would take us ages to do. And it's great 0:17:08.820 --> 0:17:11.010 for that. It's great for other things in terms of 0:17:11.010 --> 0:17:14.070 reviewing documents, producing text now with generative AI, there are 0:17:14.070 --> 0:17:16.260 great ways in which we can employ it, but it's 0:17:16.260 --> 0:17:19.379 not the same as the problem- solving capabilities than the 0:17:19.380 --> 0:17:23.369 accountant has because of the contextual knowledge that humans can 0:17:23.369 --> 0:17:27.570 apply because of the ... There's deep domain expertise and the experience 0:17:27.570 --> 0:17:29.850 they have in seeing the way things can go wrong. 0:17:30.150 --> 0:17:34.109 So AI will actually need someone to monitor and provide 0:17:34.109 --> 0:17:36.900 oversight. And even if we think about those entry level 0:17:36.900 --> 0:17:40.380 jobs, which we could say are maybe most at risk 0:17:40.410 --> 0:17:43.590 in terms of reduction in the number that might be 0:17:43.590 --> 0:17:47.698 required, you still need someone there who understands the basic 0:17:47.700 --> 0:17:51.388 principles, how things work, and to oversee the system to 0:17:51.388 --> 0:17:54.750 make sure it's operating correctly, because machine learning AI is 0:17:54.750 --> 0:17:57.240 not perfect either. This is where you get that purple 0:17:57.240 --> 0:17:59.730 person that you were talking about, that merging of skillsets, 0:17:59.730 --> 0:18:02.609 someone that has the domain expertise in accountancy but also 0:18:02.609 --> 0:18:05.129 more of a technical side. This is a huge opportunity 0:18:05.130 --> 0:18:07.560 in that area. I think what we're going to see 0:18:07.619 --> 0:18:11.490 is actually a proliferation of specialisms. And the challenge we 0:18:11.490 --> 0:18:13.948 have right now is we can't actually see all the 0:18:13.950 --> 0:18:16.170 jobs that are going to be created, all the new 0:18:16.170 --> 0:18:20.310 areas where there will be new jobs or new roles 0:18:20.310 --> 0:18:22.560 that are required in order to better make use of 0:18:22.560 --> 0:18:26.879 this technology, to extract more value for our organization. And 0:18:26.880 --> 0:18:29.100 that's something that is just going to evolve through practice, 0:18:29.849 --> 0:18:33.539 the work that Imtiaz is doing, and other people, they're 0:18:33.540 --> 0:18:37.320 developing those roles. And we're sitting back and we're trying 0:18:37.320 --> 0:18:39.480 to figure out with our crystal balls what's going to 0:18:39.480 --> 0:18:43.740 happen. But no, absolutely, it's not going to replace accountants, 0:18:44.040 --> 0:18:46.920 it's not going to replace roles in wholesale. It will 0:18:46.920 --> 0:18:49.650 change roles, it will change what people do. 0:18:50.220 --> 0:18:54.840 Thank you both for your answer to that question. That's fantastic. If someone at home 0:18:54.840 --> 0:18:58.319 is considering a career in accounting and finance, Alistair, I 0:18:58.319 --> 0:19:00.478 want to come to you first, what advice might you 0:19:00.479 --> 0:19:02.159 give them if they're considering it? 0:19:02.580 --> 0:19:05.069 I mean, that's a really good question. It's a difficult 0:19:05.069 --> 0:19:09.809 question in the sense that the qualification, accountants do so many 0:19:09.809 --> 0:19:13.650 different roles. I think sometimes it's assumed that accountants do 0:19:14.010 --> 0:19:17.070 one thing, but actually I was sitting down with my 0:19:17.070 --> 0:19:18.690 colleagues the other day and we were trying to list 0:19:18.690 --> 0:19:21.450 all the roles that accountants do and we just kept 0:19:21.660 --> 0:19:24.359 going from page to page to page. And so I 0:19:24.359 --> 0:19:29.790 think it's really exciting. If someone wants to understand how 0:19:30.119 --> 0:19:36.540 business works or how organizations operate, what is driving value 0:19:36.600 --> 0:19:40.710 within organizations, then I think this is a great career 0:19:40.800 --> 0:19:43.679 for anyone who has that kind of mindset, who maybe 0:19:43.679 --> 0:19:47.188 has that analytical mindset, has that problem- solving mindset, who 0:19:47.190 --> 0:19:49.740 really wants to get involved and make a difference. 0:19:50.189 --> 0:19:53.580 Thank you. And, Imtiaz, can I come to you, your advice to someone 0:19:53.580 --> 0:19:55.950 who's considering a career in accounting and finance? 0:19:56.700 --> 0:20:00.750 Look, this is an interesting question. I would like to 0:20:00.750 --> 0:20:05.699 see, no matter what technological developments, no matter what advancements 0:20:05.699 --> 0:20:10.408 are there, money is going to be there. It moved 0:20:10.410 --> 0:20:13.860 from hardcore cash to a number in the bank account, 0:20:14.340 --> 0:20:16.410 and then the coming years of time when we are 0:20:16.410 --> 0:20:21.480 going to introduce the blockchain technology, and then these will be something 0:20:21.480 --> 0:20:24.240 else. However, the concept of money is not going to 0:20:24.480 --> 0:20:29.190 fade away because it has evolved over centuries actually. As 0:20:29.190 --> 0:20:31.109 long as there is money, there will always be need 0:20:31.109 --> 0:20:31.859 of accountants. 0:20:31.859 --> 0:20:35.670 That's fantastic. Thank you so much. That's it for this 0:20:35.670 --> 0:20:39.299 episode of By All Accounts. Thank you Imtiaz and Alistair 0:20:39.299 --> 0:20:41.939 for joining us today. And that's it from the series. 0:20:42.000 --> 0:20:44.129 I hope it's cleared up some questions for you about 0:20:44.130 --> 0:20:47.790 working in the financial industries. With skills in accountancy finance 0:20:47.790 --> 0:20:50.880 you can work in any business anywhere and turn your 0:20:50.880 --> 0:20:54.509 passion into an exciting and rewarding career with an ACCA 0:20:54.509 --> 0:20:57.059 qualification. You can sign up to find out more by 0:20:57.059 --> 0:21:02.340 heading to accaglobal. com/ be- you- anywhere. That link is also in 0:21:02.970 --> 0:21:06.150 the show notes. I'm Maiki Lynch and this has been 0:21:06.390 --> 0:21:07.110 By All Accounts.