We’re joined by a young accountant, an ex-accountant turned HR advisor, and the MD of a leading hiring firm in the audit and accounting sector, about how roles, skills and hiring practices are evolving, and what that means for the profession.
Host
Philippa Lamb
Guests
- Lola Abitogun, Fractional HR Director
- George Oliver, Audit Associate, KPMG
- Chris Lawton, Group MD, Executive Search, Robert Half
Producer
Natalie Chisholm
Transcript
Philippa Lamb: Welcome back. Today we're returning to AI, and this time, we're looking at what it's doing to skills, the talent pipeline and accountancy's brain drain. We all know that AI is already having an impact on the makeup of audit teams, and there is some evidence it's already reducing the number of junior roles. But what about the medium and longer term effects? How might it change training and career paths, and will it ultimately boost or diminish the appeal of a career in accountancy?
[Teaser Audio] Lola Abitogun: I think everybody's playing catch up to an extent. So I think the technology is developing faster than the training.
[Teaser Audio] George Oliver: It's used more competently than I expected it to be. I think because you've kind of got this world now in finance where finance where, almost like a fear of missing out from big companies, where they're all trying to get things going, get things working. I was impressed at the quality of the solutions that we've got.
[Teaser Audio] Chris Lawton: What we're seeing is there's probably a bit of a delay and a bit of a slowdown in hiring, particularly the more junior level, where companies are being more cautious on – okay, what skills are we going to need long term?
PL: I'm Philippa Lamb, and we have three guests here with us, all of whom are very invested in understanding where AI might be taking accountancy careers. Lola Abitogan has talked about the accountancy brain drain on the podcast before. She's an ex Big Four accountant, now a fractional HR director. Chris Lawton is group MD Executive Search at the specialist recruitment firm Robert Half and George Oliver, well, he's at the cutting edge of this because he's just a few years out of university and currently an Audit Associate at KPMG and part qualified ACA. Welcome everyone.
CL: Hello.
GO: Thank you.
LA: Thanks for having us.
PL: George, you're on a training programme at the moment with KPMG, as I said, why did you choose accountancy?
GO: Yeah, so I did mechanical engineering as my undergrad, and I think coming out of that, I'd always had an interest in business and finance, and I looked at the engineering market, and I just thought, the way things are going, I think I'd prefer to kind of get a bit more exposure to business and kind of move into doing a professional qualification that would give me kind of the best of both worlds, and give me the chance to work with more of the finance industry. So that was my kind of motivation going in.
PL: So the main appeal of the training was as a springboard?
GO: Yes, definitely.
PL: How much of your time is spent on broader transferable skills versus the auditing fundamentals?
GO: So, I think the good thing recently is the Big Four generally have kind of changed their approach. So a lot of the exams now are front loaded. You spend your time at college with the tuition provider, and then you go into more kind of client work later on. So actually, I'd say it's a fairly good split. Now that we've got the first 12 exams out of the way, we're now just focusing purely on client work and more of those qualitative skills.
PL: So those transferable skills are really kicking in now...
GO: Absolutely.
PL: How much AI is involved in your day to day? What are you using it for?
GO: Quite a lot, to be honest. So we've got to the point now where we've got a few AI tools that are approved for use with clients, and they kind of span quite a broad array of the audit, whether that's just simple information gathering or looking up standards. And you've also got things like AI transaction scoring, which kind of really allows you to get a bit deeper into the technical side of things, whereas before, for example, you may have just been, say, sampling transactions. Now you've almost got this, I suppose, massive net, which is your kind of AI tools that allow you to individually check every transaction and gives you a bit more quality overall with the audit process.
PL: So you're what, about a year and a half in at KPMG?
GO: Yeah a year and a half now.
PL: So is the AI used more than you expected at the outset?
GO: I think what I would say is it's used more competently than I expected it to be. I think because you've kind of got this world now in finance, where almost like a fear of missing out from big companies, where they're all trying to get things going and get things working, I was impressed at the quality of the solutions that we've got. What is, comparatively, quite an early time for the technology.
PL: That's the thing, isn't it? I mean, Lola, this is a challenge for all firms, isn't it, integrating AI into training and development, particularly young accountants. But the tech is advancing at a pace, isn't it? So... I mean, your clients, do they feel they're always playing catch up?
LA: I think everybody's playing catch up to an extent. So I think the technology is developing faster than the training that we're putting in place for the technology. So that is going to be a challenge. So firms are having to think, "Okay, when do we kind of pause and give people an opportunity to catch up with the AI? And when do we have to take the opportunity to use it?" So I think, yeah, I think everybody is playing a little bit of catch up. But I think the bigger firms where there's more resource to kind of build that training capability, to put the big tools in and teach, you know the... well, not even just the grads, but everybody how to use those tools, are probably in a slightly better position. Some of the mid tier and smaller firms, it's slightly harder to do where you don't have massive training teams to build and develop that kind of AI training capability.
PL: But as you say, that capability, I mean they're investing in in a big way, but it's iterating all the time, isn't it? I think at a pace that perhaps none of us really expected it to iterate.
LA: You have to take a continuous learning approach to it, like you can't put in place one training or, you know, for instance, a policy –acceptable use of AI, like, that will have to be iterated because everything is changing all the time. If you look back, it's probably two or three years ago, we had companies and firms who were just like, when ChatGPT first came in, "We can't use ChatGPT We're not using AI" because there were concerns around information security and how it would be used. And I think pretty quickly everyone realised that's just not a solution, because you'll lose out on the efficiency gains. So then we've kind of pivoted to, "Okay, we're going to use it, and these are the specific tools, approved tools that we can use, and this is how we're going to use them." So it's already progressed a long way, and I think there's still a long way for us to go.
PL: Chris, this is so new. From your point of view, talking to your clients, is it possible for them to understand how AI is changing roles yet and actually changing the skills that they are going to need?
CL: I think there's a lot of uncertainty still. What we're seeing quite a lot of is the AI in terms of what our clients are believing is coming down the line, and how they actually accommodate their staff to use it, the resources that they're going to use, and how they long term hire for future proof in the business, is a really interesting time. So ironically, what we're seeing at the moment is, although AI is seen as more efficient way of working, it's going to automate a lot of processes, because companies are really not sure completely of their own strategy, we're investing resources, the tools they're going to use, how they train people to use those tools. Actually, what we're seeing is there's probably a bit of a delay and a bit of a slowdown in hiring, particularly the more junior level, where companies are being more cautious on "Okay, what skills are we going to need long term?" What we have seen is a bit more of a demand from contract and flexible resource while companies are working out, "Okay, what is our strategy? How are we going to utilise AI? Where can we get efficiencies? What skill sets aren't going to be needed in the future?" We're seeing a bit more demand for flexible resource whilst they work out and navigate a way forward.
PL: And that's interesting, this whole thing trying to press pause, when actually it's not really possible to do that. But I'm wondering, George, is this creating an opportunity, maybe, for younger professionals who may be more accustomed to fast evolving tech? I'm not going to say they are, but, you know, maybe. Is there an opportunity for them to shape AI policies at their workplaces in a way that just wouldn't have been a thing before, but this is an area where you can really shine and flourish?
GO: Yeah, no, certainly. I think there is. I mean if you look at those kind of young professionals, they probably had three or four years of, say, university or apprentice training coming into their work, right? So they've had that time where they've had a bit more almost free time to work with AI. They've probably used it in their projects. They're probably familiar with different types of AI, which is something that more senior members of the firm just won't have had, you know. They'd have been dealing with their day to day roles, they'd have been doing more, kind of high level work. So I think you've got quite a high level of competence with the workforce coming up now into entry level roles. And I think that's quite important, because not only do you know what you're doing, but also you can then, to a certain extent, experiment more and kind of guide, perhaps some of the policy that goes in. And you are kind of out the coalface. You're given these tools to work with, and you're the ones kind of making the mistakes and just working with them and kind of understanding them. And I think that that's quite powerful. It's an extra value add that young professionals now have, which they wouldn't have done before, when they would have just been doing kind of tick and tie and basic work.
PL: You can demonstrate expertise at much earlier phases it seems to me. Chris, do you see this changing career progression and the pace of progression? Because, you know, people like George at his stage in the profession, they are more valuable than they might have been even five years ago.
CL: Yeah, absolutely. I think there's also a consideration around companies using AI to automate processes. There is a risk that the pipeline of talent for the future and giving people the skills long term to be able to be competent in their jobs, there is some risk there. So if we're taking away or we're automating some of the more, I guess, less technical areas, or what would be seen as more junior tasks, people are entering businesses in the more mid level range. They're not really picking up the skills to really understand the whole picture for future leadership, or understanding the bigger picture, which could be a bit of a risk.
PL: So what age do people tend to come to you to make the move?
CL: There's no particular age, I guess it depends on what career choices you're making. So we will have straight graduates come to us who don't want to go via Big Four, who want to get straight into industry, right through to the classic ACA qualified coming out of Big Four after training three, four years, feeling like they now want to take a move into industry to broaden their skill set and elevate their career.
PL: In the past, would they maybe have stayed on a couple of years more to gain more skills and experience before they look to move?
CL: That's not a trend we've seen. I think it's a pretty classic move for most people to feel like "I'm going to get my ACA qualification. Once I've done that, I'll then look into industry to make the move." The question really is: what am I gaining by staying the extra one or two years in the Big Four? Once I've done my training, I'm probably at a premium in the marketplace in terms of the skill set I've got, the experience I've got, the education background. It's a given when you come out of the Big Four, you then stay a year or two more, you might get some more exposure, people management, running bigger audits, for example. The question is, are you really getting many more skills that justify clients saying "we're going to pay the extra salary. We'd prefer to maybe go for someone straight out of practice, newly qualified and we'll train them up"?
PL: Lola, this kind of compression of training and the potential to move maybe a bit faster to more senior roles, it sounds great for young professionals...
LA: It does, I think, in theory and in some areas in practice. But exactly what you just said, in terms of, you know, a lot of the training that happens, especially in the Big Four context, in accountancy in general, it's learning by doing. Those really kind of fundamental, kind of "basic tasks" – they're there for a reason. They need to be done because they're, you know, part of the audit or part of the advisory work that you're doing. But the more you do them, the more you understand the fundamentals, everything is built upon those foundations. So if we're taking that work away, there's a question of, actually, yes, maybe practically, you can do the work and you can progress more quickly. But are you then... are we going to put ourselves in a position later on where some of these people don't have the fundamental skills that they would have had otherwise? So it's a challenge for firms to then think how to supplement that learning, what else they can put on top, or how else they're going to check and validate. These learners are actually getting the full extent of what they would have had, you know, before. And obviously, things are changing. We're not saying that everything has to be exactly as it was before, and maybe actually in the future, some of these skills will be less valuable, but I don't think that they're ever going to be not needed.
PL: That's an emerging story, isn't it, Chris? This idea, I think perhaps even a year ago, firms were loving the idea that they could axe their graduate intake down. And now that reality that Lola and you have just described, is dawning in quite a major way.
LA: It's the pyramid, it's like, we still have one... maybe not a pyramid, sometimes it's more of a diamond now I don't know. But we need people to progress. You know, a lot of partners would have started as a grad, if not that firm, at another firm. So actually, if we're having less grads coming into the professional, coming into the firm, what happens, you know, once we will still naturally have that attrition after qualification, those 3/4/5, year leavers. Are we going to have enough people to continue to run the firm? Are we going to have enough people to maintain the balance to give us the right level of supervision that we need in order to do the work that we need to do for clients. So I think there was probably this initial, "Oh, yeah, we can have less people because we have less Junior work to be done". But now I think there definitely are some firms who are like, yeah, maybe we actually don't need them for the type of work that we're doing before as many, but we're actually going to take them, we'll give them we'll give them different types of work or think about the kind of work that we're giving them in order to maintain the kind of proportion and the ratio that we need to make sure that in 5/6/7/10 years, we still have enough people to be senior managers, partners and so on.
CL: We're definitely seeing different skill sets being used. So a good example would be, I know of a client recently who are retraining their SEO engineers to be prompt
PL: Really?
CL: So it's an older SEO, not exactly an old industry, but SEO engineers are now, "Okay, we don't need that, but we can retrain you to make you prompt engineers to really start to understand what is the AI. How can we use the AI to move ourselves up the search engine list".
GO: I think it's interesting, because a lot of the counter argument to this whole kind of AI disruption thing is that, we had spreadsheets come along before, right? And spreadsheets over the time, everyone thought, "Oh, that's it. That's the end of accountants". And that's interesting in the sense that a spreadsheet is ultimately just doing calculations, right? Whereas now you've got more judgmental work getting on that AI is replacing. So this is really the first time, I think, where technology is replacing judgmental work. And I think jumping back to Lola's point there, that's quite interesting, because will you have that gap where you've got people that haven't, at an early stage worked on really judgmental work, and then is that going to affect them later on? Because I just think that's a really common counter argument. And I thought this for a while as well as, you know, I would just be like, when the spreadsheet came out, it will just increase the per worker productivity. But I don't think that will be the only effect. I think it will also almost damage people's ability to perform judgmental tasks, to an extent.
PL: What's your take on this, George?
PL: But everyone we speak to talks about the importance of human oversight, not just for regulatory and compliance reasons, and not just because we all know AI can hallucinate, but just that sense of sense testing that comes from experience, doesn't it? So really important to have the training you're having now?
GO: Yeah, I think so. I think it's definitely... you need to understand what's getting in some of these judgments, especially in this kind of audit and assurance kind of line of work. It's not as simple as writing code, or it's just not that deterministic, right? It's not one single outcome. You might have a few inputs and then one single outcome, but here you need a really strong trace where you prove that the assurance result you've got is based on repeatable evidence.
LA: And also, I think there's a point of, we're always going to be dealing with people, and even when you're speaking to clients about how you're going to do the audit, there will be some clients who are going to be really comfortable with the fact that AI tools are being used, and there'll be other clients who are less comfortable with it and still might want a little bit more oversight, or a little bit more human intervention, or a little bit more assurance on how that has been done. And you know, we're still going to have to give that to the clients regardless. So I think it's important that we are honing those judgement skills really well to be able to say the AI has judged this. I'm sure. Have never used those words, but to be able to say, Yeah, this is the approach that the AI takes, and we agree with it, and having kind of tested it, or, you know, validated it, we also agree. And this is the judgement that we have applied, because I think clients are going to need to be comfortable, at least in the kind of short to medium term. Maybe further down the line, this just becomes how everything is done, and that's fine, but definitely in this kind of transitionary period is going to be so important.
PL: But this seems quite problematic, because clients are pricing this into what they want to pay for the services they're getting up, and they're saying, "Well, if you're not using AI, why aren't you using AI?", but they don't want to pay these bills. And you're saying, actually, apart from one or the other, it's still going to be both, and it's going to be both for a long time, which is expensive, isn't it?
LA: There should be some efficiency savings, and then some... you know, you have to pay for the tools, right? But the tool should, in theory, create efficiency. So I think, hopefully it does, like there's a middle ground where it drives down the cost of the work that we're doing, but also without affecting the, I mean, the output and the assurance that you're able to give. I mean, this will be the challenge for firms, isn't it? When they're getting pressure on pricing is: this is not to drive prices through the ground. It's to make sure that we get the most efficient solution which is going to give you the best quality of assurance. I'm sure that's the conversation that loads of partners are having now anyway.
GO: I suppose adding value isn't it as well? Beyond just the assurance you're also saying to the client, actually, this is what we observed in your accounts. This is something that you probably weren't aware of, but after having sifted through, you know, a few million transactions we've kind of learned this. And I think that is probably the best rebuttal a company can come along with. So you know, we can not only act as an auditor, but now also kind of an assurance provider, and in some ways almost a consultant.
GO: In ways that manpower would have never... it would have been impossible before.
PL: Yeah, I think so.
CL: Yeah. I was gonna say that the cost element won't change. I think the value you get is going to increase.
PL: Right now, you talked about hesitancy on the part of clients around hiring. Jobs are harder to design, aren't they, for them? And there's just this whole sense of: we're in a place and we don't know where it's going. We'll wait and see. But actually, this is the new normal, isn't it? It's not like there's an end point.
CL: No, and we are seeing change. I think at the junior level, as we've talked about, there is definitely a move away from demand in those skill sets. There's a lot more automation. We're seeing teams reducing size at the transactional end of the market, for sure, because of AI, there's no question of that. In the midpoint, so newly qualified, or sort of, couple of years post qualified, what we're seeing is the demand for the scale is different. So before, it would have been more technical, reporting led. Now it's very data led. Can you interpret data? Can you use the tools that we've got? Are you able to add insight? Can you be a true business partner? And then at the senior end, as a C-suite, when you're thinking AI, there's different elements to it. So it's investment: what investments do we make in AI? How do we transform our business digitally? You've then got the commercial element, how are we going to utilise it to generate the most effective outcome, to give us the best commercial edge against our competitors? And then you've got the risk and governance of making sure that you're using it in the right way.
PL: Does that chime with your experience, Lola?
LA: Yeah, I think so. Especially from a risk and governance perspective, even just from an HR perspective, we're seeing a lot more, kind of, employee relations issues that are coming out of the use of AI, or unacceptable use of AI.
PL: What sort of things?
LA: People using it in the wrong way and impacting client work, or even as simple as using it to draft emails in a way that doesn't feel particularly human, and then the client is now thinking, "Okay, well, I'm clearly speaking to AI – that's not what I'm paying for". Or, you know, having things that have been kind of run through AI tools and then not properly been checked, and then that kind of going out and not having the right level of oversight. So things like that are starting to crop up. And if you have good governance in place, that shouldn't happen. You can get into a situation where you want to use the tools in order to get the efficiencies, but maybe you haven't done the kind of preparatory work to make sure this kind of stuff doesn't happen. So there's a lot of risk involved, especially when it comes to governance, and you need those kind of senior people to kind of set the set the tone of what that looks like in the organisation.
PL: Are you very aware of this, George, in your day to day?
GO: Yeah, certainly. It's quite interesting, to the point there of kind of communicating with clients using AI? AI can feel very unnatural when you're on the company receiving it, and I think everyone's probably aware of this, but if you look on LinkedIn nowadays, you can see about half of the content seems to be written with AI, and you almost get into this AI echo chamber where AI is being used to train other AI. And if you've got quite a narrow context window for some of the some of the inputs you're giving it, you can end up with this, these sentences that just sound so obviously written by AI. It's really, I suppose, quite damaging, and just results in really bad quality content coming out. I wouldn't say that's happening necessarily in the industry, but I think it's something to be aware of. You can certainly see it on professional networking platforms and such, where people have just not really thought of the human side of what it is they're trying to say. They've just put it into an AI.
LA: You must see a lot with recruitment, because, for instance, like Heidi recruitment – I can see some of the... even if it's just like a personal statement or a cover letter, and not every client will ask for one, but when they cut and paste, it's so obviously written, and some clients are now checking them because... there's nothing wrong with using AI to supplement what you're doing, but essentially, we want to know what's in your head, and that's hard to see now.
CL: I was just about to say that the risk, not a governance risk, but just a general risk is: AI being used to draft CV's is taking away the human element of a person, and it's not really reflective of the person that's applying for the job. Particularly in the bigger companies, when you've got AI being used internally to sift CV's, look for keywords, they're pulling CV's through to internal talent teams by sifting CV's and then recognising specific words and then popping these people up as recommendations for hiring. And I think that's where we can come in and add the human touch. I think this is where the efficiency part of AI versus the human touch, and okay, use the data we've got to add the human touch, do the in person interviews, ask the questions that you're not going to get from the CV. And that's where we can add value to clients and give them the story, the real story behind the person, rather than what the CV is saying.
CL: Well we've heard from the Big Four on this haven't we? More than one of them, I think, saying, you know, "Please stop applying to us in this way, because it's just making it impossible for us to sift through all this."
PL: But that, I mean, I guess, would be seen as very labour intensive and expensive now, except for senior roles?
CL: That's what we've always done.
PL: So you're not seeing pushback on that?
CL: No, we're not seeing pushback on that. I mean, the pushback, or the challenge for us is where clients or companies are using AI to make hiring decisions in terms of interviewing, right? So where their first choice might be "Okay, we're not going to go to a recruiter. We use our internal teams or our internal tools to identify talent." Then they get to the interview stage and actually realise that the people they've got don't have the skills that they thought they did. Slow the process right down. And then they come to us and say, "Right, this has not really worked out as we wanted it to. Can we now engage you?", because they need the human touch to complement the efficiency that they're perceived to be getting from using these AI tools.
LA: And I actually think at certain levels. So for instance, in executive search, I don't think any client would even want... you know, why you're hiring exec search firms a lot of the time is because you really need that kind of senior human level oversight. You want someone who's going to reach out to someone as a human being who maybe wouldn't have engaged otherwise. So I think it probably lends itself, the use of AI probably lends itself to a more junior type of recruitment sometimes.
CL: But actually, there's a good example there of where we can add what we talked about earlier, about where you're not paying less, but you're getting more value. A real life example of that would be in our executive search team. So previously we'd be writing resumes, job profiles, personal profiles, by hand, in Word. We all automate that now, and that's all done with AI. But what that allows our research teams to do is actually go out and find more talent. So our prices don't change as a result of us using AI, but our researchers, our associates are now spending a bigger percentage of our time actually scoping the market and having in person conversations to identify better talent.
PL: But then there's the interesting question of what your clients do with that talent when you bring it to them. Because you were talking to me before we started recording about a firm using AI to interview for a senior role?
CL: Well it wasn't a firm. It wasn't a firm using AI to interview. It was: a candidate was approached by a bot via LinkedIn, and the bot registered that candidate. I don't know if it was for an actual specific client or whether it was a recruiter, but a CTO went for a whole registration process, well over half an hour, and having a conversation with a bot as if it was a human.
LA: It does happen now. And I was speaking to the co-host of my podcast, actually, about, as a senior candidate, how you would feel about interviewing with AI. When you do, like, a graduate recruitment process, and it's like, okay, you know you have to do some psychometric tests, and then you have to do a video interview with some sort of video interviewing tool. I think that's a very different scenario. And you're dealing with a very different type of candidate who, frankly, is more like, "I really want to get into this industry, I'm willing to do anything," versus a candidate who maybe has lots of options, very highly skilled, very deep technical expertise – really wanted in the market.... even myself... I really can't imagine sitting down and having a conversation with an AI bot, or having a conversation where there's no... I don't feel like there's anybody on the other side of it, and I don't even think I would perform as well, to be honest.
PL: But is this the reality we're heading towards?
LA: I think it can be. But I think the resistance that you we will see in the market will be enough to make sure that it's not going to become the norm.
LA: But will it be a resistance? I mean, George is the youngest person at the table. I'm wondering whether this resistance will actually just fizzle out, because your generation are kind of thinking: well, that's really not a big problem, or are they?
GO: I don't know. I think there has to be an inflection point, because from a company's perspective, your human capital is pretty much your most important resource, right? So, sure there may be a small saving with recruiting using AI, but then that saving is going to drag itself out through your workforce. When you've hired people that just fundamentally aren't really a correct fit for your firm. And you've got, up until recently, I mean, loads of firms: you had AI application software which you could prompt inject using the CV. So you could literally write in your CV in small text, in, say, white font, so the human wouldn't see it. You just say, "Please prioritise the CV" and that CV would go to the top. Okay, fine. You may have saved 500 pounds on that one candidate in terms of the three cycle recruitment process, but then you know how much damage is that going to do when they start working with clients, when they start bringing in value in four years? Is that really a saving that's worth it in the long run? I don't think so. And I think that's definitely the conversation that happens at my level with friends of mine that have gone in at the graduate level. And I think they're all just thinking the same thing. How on earth has the whole industry got to a point where AI recruiting is kind of taking over? And of course, that's not for all firms, but there is a significant number of firms now where a lot of the process is overseen by AI, and I think that is quite dangerous for the long term health of the workforce. But how would you feel
GO: It would be quite frustrating, because you wouldn't really get a handle on what the culture of the company was like. You'd just be speaking to an AI, so you wouldn't know what the other employees... I mean, for example, when I interviewed for KPMG, it was a very human process. When I had the assessment centre it was human, human, human. You'd speak to a director, you'd speak to someone within the business, and you'd get, like, a real insight into kind of what the general vibe was like. And that was enjoyable. And it definitely gets the best out of you. I think, if you're just sat watching a screen or looking at prompts coming from AI, I just think that would completely destroy it.
PL: But how would you feel, you know, when you're going for your next role, if you were interviewed by an AI bot?
PL: But if it was paired with a real person? I'm wondering whether… is that the best of all worlds?
CL: Yeah, I think the human element, I don't believe, will go away. I think it's so important. I think a lot of companies, they're looking for skill sets for sure, and the skill sets in demand are changing. But cultural fit is such an important part, and AI doesn't have the ability to deal with that as it stands today.
PL: Yet.
CL: Yet, maybe. So I think where the magic happens for a business, is where you use the AI or what tech you choose to use for the efficiency, but you oversight it with human touch. Particularly in the back end of the process. I mean, we've got examples of people... You see a CV, It looks great. You meet them on teams. It's gone well. You meet them in person. Actually, they're not what you thought. Even that so, that's taking the journey past the CV to actually having an interaction with someone via screen. And you get in one impression, and you're getting a very different impression in person. We had a situation recently where someone interviewed on teams. We went for lunch with the client, the client was like, "That's definitely the person we want. Like, this is the just go. We'll go ahead with this one." Did the in person, and it was a... it was a no. Totally different.
PL: Interesting. Yea, so why was it a no, and what didn't emerge in the meeting?
CL: When you're on screen, you're using one of your senses, or two of your senses, your sight, and you're sound... you're missing all the other senses. You know, just that feel you get for someone... is it's hard to quantify, but you know when you sit in a room with someone and you're really feeling.
PL: Well that is why we're around a table in the studio doing this, because we find we get better conversations.
CL: Yeah exactly, and it's just a feel isn't it? Culture is so important for a business. Culture beats strategy. If you said to any business: have a great strategy or have a great culture? You'll get more return on a great culture. And it certainly comes first. You can't have a great strategy without a great culture.
LA: And I think it's a performance thing as well. So sometimes you do get candidates who are great on teams. If you think about it, you might be sitting in your own environment. You're comfortable, you're at home. You don't know how that person is going to feel once they're in an office. They're surrounded by an unfamiliar environment. They're sitting opposite the managing director or the partner that they may feel more intimidated. And actually that might give you a slightly better view of, and not to say that can't be worked on, but that might give you a slightly better view of what this person may be like with senior stakeholders or with clients. And that might change things, because actually, when they were at home in their own environment with, you know, interviewing at maybe a different level, it was absolutely fine. You need everything. I definitely think we should be using the tools as much as we can to get the best result. But also we just have to make sure as much as we can, it isn't overdoing it.
CL: If you can find the balance between human judgement and, I guess, hard data to make a decision on a hiring, on a hire, that's that's the key. Because arguably, before AI or before the tools that we had. A lot of it was down to human judgement, and it was down to just the interview, rather than maybe using the AI to really help solidify your argument or your reason for hiring someone.
PL: Looping back to the skills, I am wondering... I mean, there's a kind of haves and haves not situation then, isn't there? Some people have this training, have this understanding, have this skill set. Others, not so much. Are we going to see kind of a dog-eat-dog poaching of people as AI integration ramps up faster than that skills shortage can be addressed?
LA: I think, to an extent. So for instance... and probably it makes sense in the contract market, but we have lots of firms right now that are rolling out AI tools. There are very limited number of people who know how to use those tools. So actually, if you are someone who has had that experience, and probably within practice, because you've had the opportunity to implement it with lots of different clients, you are probably going to be quite valuable. Eventually, there'll be a lot more people who know how to use that tool. So the market will probably settle down. But at the moment, there might be two or three people who know really well how to implement this specific tool. Those people are probably going to be more valuable.
CL: And then what that would do is drive up wages as well. Because as people get headhunted, because they've got the skills headhunted for more money, you will see a wage increase in that marketplace as a result of that, for sure.
PL: So George, it sounds like this is an unrepeatable moment for people at the career stage. If you're a smart young professional, you can make yourself very visible and very useful by working easily and creatively with AI?
GO: Yeah, I think so. It's definitely a creative opportunity. I think it also levels the playing field slightly, because historically, you've hired at university education, that you pay a lot of money for and then you incur a lot of debt for. Whereas now, I think, from a skills perspective, with AI that doesn't need to be taught at university, that can be very much be self taught by experimentation, and it's kind of a... it does change the dynamic, really, for skill sets that an employer would like to see. So I think if you take advantage of it, it can definitely be an opportunity. But I think that's not to say that a lot of people aren't struggling with finding vacancies and finding good opportunities, because there's just seems to be a real lack of opportunities.
PL: For graduates, absolutely.
CL: The skills that are in demand are definitely more the interpretation... using the AI tools, data interpretation, using those numbers to make commercial decisions. From a finance perspective, business partner with the business, there's a much more convergence between tech and finance now, like tech and finance are coming together a lot more. You will often see CFOs or FDS that not only look after the finance department, but also look after the tech department. Transformation and change is so big. So from a skills perspective, the people are really ahead of the game are the people that understand and can use the tools, can interpret the data, can then articulate that to the business to make good, commercial, strategic decisions to help long term.
PL: I mean, Lola, this strikes me. HR has already been down this road, hasn't it? This move away from transactional HR to business partnering. I mean, that happened for HR a few years ago, didn't it? And now you're seeing it in accountancy.
LA: Yeah, I mean, the parallels are very clearly there. But even now, if you think about the view that people have of HR, you'll see you have some people who understand that, you know, HR is an enabler, and you have some people that will feel like HR is still more of an administrative function or more of a tick box exercise. And that's probably the same in finance. Depending on the organisation you're in, some people think finance is really there for compliance. It's there to make sure that we do what we need to do and we don't do what we're not supposed to do. And others understand that finance can be an enabler. You've got the business partners who can give you your real time data in order to make those important business decisions. So I think it's the same. And we've kind of been moving in parallel for a while, which is why I like to kind of sit at the intersection, and it was very easy for me to move across.
PL: I think you have an excellent skill set, as you can see. But George, I mean, to wrap this up, I've got to ask you: it seems to be the landscape, even a year and a half in for you, landscape looks quite different, doesn't it? Now, to even when you started?
GO: Yeah, 100%. I think you're getting tools now that are being rolled out increasingly quickly, and you're coming into this world where every month or two, you've got a new tool to use, and you've got a new kind of set of skills to wrap your head around. And I think it's probably the fastest pace of change that we've seen in the industry for quite a while. So I think that's really exciting. As a graduate, you can come in and apply the skills that you have to a different kind of problem with AI every day. I think that does mean that, whereas traditionally, you might have had two or three years of just going and doing manual work early in your career, now you're kind of almost more in a position to manage a process much earlier on. I think that's definitely really exciting as a young member.
PL: So it's exciting – the uncertainty is not making you apprehensive?
GO: I don't think so, no. I think it's an opportunity and the fact that things are changing so quickly, more represents, you know, how powerful these AI tools are, and how quickly the landscape is changing. So I think with the right mindset, with the kind of progressive mindset, it's an opportunity more than a threat.
PL: Next month on behind the numbers, we'll be looking at the government's plans to modernise corporate reporting. What will they look like, and will they truly reflect contemporary corporate reporting considerations? If you have any thoughts you'd like to share about today's episode or the podcast in general, you can now do so via our contact email. Here it is: podcasts@icaew.com, that's podcasts with an S on the end. And now that you've listened to this one, please do remember to log it as CPD on the ICAEW website. Handily now, we've added a link to the show notes from this episode so you can literally click through from wherever you're listening. It is a job for every single time. But now, of course, it's a very quick one. Thanks for being with us.
