3099: EY Shares Its Vision for the Future of Work and Technology

[00:00:04] Is the future of auditing bound to be reshaped by the rapid advancements of emerging technologies?

[00:00:12] What impact is technology having on the world of auditing?

[00:00:17] Well today I'm joined by two leaders from EY and together we're going to explore how AI, blockchain, cloud computing and so much more are revolutionising the auditing sphere.

[00:00:30] So together as we navigate these technological enhancements, one question looms large and that is how are these innovations converging?

[00:00:39] How are they enhancing the quality, productivity and client value of audits?

[00:00:46] Yeah, we're talking about real world results here. That's what I want to find out more about. Look beyond those tech buzzwords.

[00:00:53] So together we're going to uncover the transformative efforts that EY is investing in and also some of the new horizons that they're aiming to reach in the assurance technology landscape.

[00:01:05] But enough from me. Time to get today's guest on.

[00:01:09] We have not one, but two great guests joining me today. So first of all, Mark, welcome to the show.

[00:01:15] Can you tell everyone listening a little about who you are and what you do?

[00:01:19] My name is Mark Yashonik and I'm EY's Global Assurance Digital Leader based in beautiful Hamburg, Northern Germany.

[00:01:26] Well, it's a pleasure to have you join us. And Paul, great pleasure to have you join us on the podcast too.

[00:01:32] Could you also tell everyone listening a little about who you are and what you do?

[00:01:35] I'm a partner in our assurance organization based here in London in the UK.

[00:01:40] And I have the pleasure of acting as our global assurance innovation and emerging technology leader.

[00:01:45] Well, there's so much I want to talk with both of you about today because every day on this podcast,

[00:01:51] I try and dive a little bit deeper into an area that you don't automatically associate with technology.

[00:01:56] And we're all talking about AI and so many different emerging technologies right now.

[00:02:01] And one area that I don't think you automatically associate with technology is auditors.

[00:02:07] So what you're both seeing out there, what do auditors face or what is the biggest challenges that auditors face in this AI era that we find ourselves in now?

[00:02:17] Well, I think from my point of view, Neil, it's been an amazing opportunity to see the pace of technology change over the last few years,

[00:02:29] particularly with artificial intelligence becoming increasingly mature and increasingly prominent as a technology capability that auditors can use.

[00:02:38] And maybe if I reflect back, I mean, this is a profession in its modern construct that's over 100 years old now.

[00:02:45] But over the last 10 to 20 years, you've seen really significant investments made by audit firms to equip auditors increasingly with technology to help them do their jobs.

[00:02:56] And that's evolved alongside new accounting and auditing standards.

[00:03:00] And from a technology perspective has really seen a move from what we historically had was was traditional paper based verifications of transactions all the way through to what we have today with modern cloud based audit systems or platforms,

[00:03:14] which are helping equip our auditors with workflows with data analytics automation.

[00:03:20] And as you said, they are.

[00:03:22] And in particular, when I think about why we need to do that and why that is such an important opportunity for us,

[00:03:28] it's because the role of the auditor increasingly becomes more complex on a day to day basis.

[00:03:35] There are new auditing and accounting standards to adapt to.

[00:03:39] Clients have new risks, regulations they need to adapt to as well.

[00:03:42] And there's no technology available than ever before.

[00:03:45] And what that means is our auditors are increasingly challenged with a large workload, more information they need to consider, more decisions they need to make.

[00:03:55] And so the power of AI technology in particular is becoming increasingly prominent to help create a high-quality environment for our people to work in with a lot of user experience.

[00:04:05] It's helping us power high-quality audits, which is one of our highest commitments as an organization.

[00:04:14] And it's helping us serve our clients who have high expectations of what an audit firm should deliver.

[00:04:20] And what that's meaning when I get into the technology itself is today we're using AI in a number of different areas.

[00:04:27] Just to give you a few examples of what those might be.

[00:04:31] Document intelligence, which is helping to analyze and understand and extract relevant information from documents as an order to connect supported elements.

[00:04:41] Secondly, another example, the use of statistical analytic techniques to identify potential anomalies in large volumes of structured data as an auditor looks at the company's ledger and scans for transactions that might warrant further investigation.

[00:04:56] And then, thirdly, to search and summarize the latest technical auditing and accounting standards and the associated methodologies.

[00:05:04] And that's really helping them in applying interpretations and judgments, including on complex technical accounting matters.

[00:05:11] And what we've been doing at EY as part of an ongoing $1 billion investment to integrate and transform our assurance technology is to develop new releases of AI technology, new capabilities.

[00:05:22] Just over the last 12 months alone, we've released new capabilities that allow us to equip our auditors with AI-enabled benchmarking.

[00:05:32] So if they're thinking about the risks associated with a company, which is something that is so fundamental to what an auditor does, they're actually able to use AI to compare their risks that they've identified for one company with a whole portfolio of risks across many other companies that might sit at peers for that one organization.

[00:05:53] A second example, your auditors have to review draft financial statements before a company publishes them to their stakeholders.

[00:06:02] Historically, that required our auditors to go through hundreds and hundreds of pages of draft financial statements, identifying potential data points within those documents, verifying if those data points were accurate, comparing them to other data points within the document, and making sure those data points are consistently consistent.

[00:06:22] I've consistently described in each of those documents.

[00:06:26] That's a huge amount of work that is required for our audit professionals.

[00:06:30] And historically, it was all done manually.

[00:06:32] Well, now we have AI capabilities of our people who can use, which way you feed the draft financial statements to the artificial intelligence and within minutes is able to go through hundreds of pages identifying as a first review on behalf of the auditor,

[00:06:49] the potential areas that warrant their further investigation and their review.

[00:06:54] So we're really seeing, particularly over the last few years, this first major steps into introducing AI into our technology platform.

[00:07:04] And that's really the trajectory is only up from here.

[00:07:08] And Mark, from what you're seeing in Germany and indeed the hundreds of conversations you must be having with people all around the world, is there anything that you're seeing here around this?

[00:07:18] Paul sometimes makes fun of auditors still sitting there with a calculator and that red hand, but seriously, we both know that we're actually at the forefront of this development.

[00:07:29] And people might wonder why that is, and I think Paul summarized it well.

[00:07:33] First of all, it is that our clients, that comes with a need for us to equip our people with the right skills.

[00:07:40] The second is about all of the opportunities.

[00:07:42] And Paul gave great examples how we capitalize on those opportunities in the various use case fields.

[00:07:49] But I would add kind of like two things from speaking to all of the parts of our organization here.

[00:07:55] One is the access to our alliance.

[00:07:57] I mean, just see how we've been able to tap into our partnership with Microsoft to really kind of like bring this up to scale.

[00:08:06] And the last one to mention, our talent requires that.

[00:08:09] I mean, it was 400,000 employees for EY, right?

[00:08:12] It's still our work that we do and deliver to our clients is empowered by our people and enabled by technology.

[00:08:19] And these people request that we use the latest technology, embrace that, give them access to.

[00:08:25] Otherwise, we would probably end up having a recruiting challenge.

[00:08:28] And one of the big questions that we're hearing more and more at the moment is around ROI and business value when it comes to AI.

[00:08:36] It's not just about the shiny tech.

[00:08:37] It's now about what problems are we solving?

[00:08:39] How is it helping?

[00:08:40] So I'm curious, how are you seeing auditors streamlining tasks, boosting productivity and ensuring higher accuracy levels by harnessing AI and automation?

[00:08:51] What are you seeing here?

[00:08:52] We particularly see as we're investing in technology and increasingly deploying technology as part of our integrated technology platform.

[00:09:03] We've seen opportunities to use automation and the linear automation, RPA, more recently intelligent automation and now AI as capabilities to help our professionals on a day to day basis.

[00:09:16] I gave some examples.

[00:09:18] And when you talk about ROI, we're very thoughtful about the sort of benefits that this technology brings.

[00:09:26] And I mean, just to call out a couple of specific benefits.

[00:09:29] Number one is around quality.

[00:09:30] The ability to deliver a power or high quality audit.

[00:09:33] It is just so fundamentally underpinning through the use of technology today.

[00:09:38] And whether it's automation to help an auditor for many of those routine and manual tasks, authority would have been done using a calculator or using an Excel workbook or even using paper-based recording of information.

[00:09:54] That today has fundamentally changed through the investments we've been able to make.

[00:09:59] And that brings with it a level of precision and accuracy with a stake on the way to power in a high quality audit.

[00:10:04] Next, when we think about the expansion of AI using techniques like predictive and statistical analysis, using the ability to read documents, read information, extract relevant information,

[00:10:18] those types of opportunities and those AI patterns that we can start to invest in and explore are going to unlock the more opportunities to invest in technology around audit quality.

[00:10:30] But as Mark mentioned, also around the user experience and at a time where we need to attract and retain the very best people in the profession.

[00:10:38] It's so fundamental that we have technology capabilities to create a user experience that matches up with what people expect as consumers using day-to-day consumer technology as well.

[00:10:48] And then the final thing I would point to is just at a time when there's so much change in the world, we have elevated expectations of the boss as an audit firm, expectations around relevancy, value, insights we can deliver to our clients.

[00:11:05] But there are also new risks, new risks to consider and new regulations to adapt to.

[00:11:10] That includes, for example, a non-financial reporting and assurance agenda where new technologies like AI are going to be fundamental for us in actually being able to access data, manage data and analyze data that historically was never tapped into before.

[00:11:26] So particularly in areas like ESG, that's just going to be absolutely fundamental going forward.

[00:11:33] And Mark, when it comes to things like solving real-world problems, generating business value with AI and automation, what are you seeing here?

[00:11:42] Mark, the first is productivity as such as a requirement these days.

[00:11:46] Because with all of those additional requirements being given to not only our profession but also to our clients, think about the expansion from the financial part of the assurance business to the non-financial part.

[00:11:59] Think about the impact of technology here.

[00:12:01] If we wouldn't get productivity gains on the routine tasks, the demand on our operating model would be even bigger.

[00:12:08] The second piece to mention is we are required to closely work with clients.

[00:12:16] And what does that mean with all regards to independence here?

[00:12:19] Our clients need to supply data.

[00:12:21] Our clients need to respond to questions.

[00:12:24] Our clients need to hand in the information very timely when the time is most precious in these kind of closing cycles.

[00:12:30] And technology helps with that.

[00:12:32] So when we say productivity, it's also reducing the time lag here.

[00:12:36] And Paul mentioned the financial statement tie-out tool before.

[00:12:39] If you just think about the turnaround, somebody manually ticking and tying hundreds of pages and then days later coming back with the question versus being immediately able to turn around and then focus on where the risk is.

[00:12:51] That is another angle that is very important for the productivity and why this ultimately impacts, as Paul said, the quality of our services as well as the experience for our clients and our people.

[00:13:02] And, of course, although artificial intelligence is the big buzzword right now, one of the things that attracted me to EY and wanted me to get you on the podcast today is you guys don't just leverage AI.

[00:13:14] You are a tech company in every sense.

[00:13:16] So how do technologies such as blockchain and cloud computing also enable auditors to access things like real data for swift gathering and analysis, ultimately facilitating effective risk assessment and timely risk mitigation?

[00:13:31] Because it's not just about AI.

[00:13:33] You use so many different technologies.

[00:13:35] Maybe I'll start with the blockchain one.

[00:13:37] And that's a really interesting technology, particularly from an audit perspective.

[00:13:41] It's certainly an example of how a technology and an emerging technology can often come with high expectations and then move down a slightly different path from what was originally anticipated.

[00:13:51] So, I mean, as we know, blockchain as a technology became prominent following the launch of Bitcoin way back in 2009 now, which seems like an awfully long time away already.

[00:14:00] That, at the time, generated a lot of interest in the auditing and the accounting space as people, including us, really explored the concept of putting information, including transactional information, onto a blockchain.

[00:14:14] And the opportunity or the angle that was spotted was to really create transparent and immutable ledgers of transactions.

[00:14:22] So effectively, the idea was you can see the information and you can trust it on the blockchain.

[00:14:27] And people saw that that would be opening up a world of opportunities and new possibilities, including real-time auditing with the traceability of all transactions on the blockchain.

[00:14:38] Now, if we fast forward 15 years, things have panned out a little differently.

[00:14:43] If for various reasons that's not happened, to a large extent, because the value proposition of how to roll of your day-to-day transactional information constantly stored on a public ledger was not that strong, candidly.

[00:14:55] And when it came to intentionally using private blockchains or public blockchains with privacy in place, the costs were often very high.

[00:15:02] And frankly, organizations just didn't adopt it at mass scale.

[00:15:06] However, as we know, digital assets, or what we may commonly, more commonly know as crypto or described as crypto assets, have gone through some fairly spectacular boost and boost, boom and bust cycles over the last decade or so.

[00:15:22] And increasingly, those assets, including Bitcoin, Ethereum and others, are being used by organizations, including wealth and asset management organizations, as a store of value.

[00:15:31] And our auditors, particularly our auditors who work for work in serving many of our financial services clients, need to be able to understand those digital assets who've stored on the blockchain.

[00:15:42] And we've had to develop technology to help it.

[00:15:46] EY's blockchain analyzer allows our teams to really follow the flow of transactions across the blockchain.

[00:15:52] It allows us to follow the path of funds.

[00:15:54] It allows us to verify the authenticity of those transactions.

[00:15:57] And as some markets, including the US, look at potentially relaxing regulations around those digital assets, we can anticipate that we're just going to see an increase in companies over the coming years taking an investment position there, which is going to require our auditors to consider the risks associated with those digital assets and use our technology, including the blockchain analyzer, to really understand more about those as part of their collection of audit evidence.

[00:16:23] So that's really kind of fundamentally where blockchain has gone.

[00:16:28] One thing I would flag, just looking ahead, when we think about blockchain and auditing, one topic to consider is smart contracts.

[00:16:36] There's still potential here.

[00:16:38] And the idea would be smart contracts is that they can be implemented by companies.

[00:16:43] This would actually help facilitate automation within the audit process.

[00:16:47] So, for example, we can actually verify financial transactions and take a specific accounting standards because that information is recorded within the smart contract.

[00:16:56] So some exciting possibilities going forward.

[00:16:58] And I think that definitely indicates there's more to come in this space.

[00:17:02] But it's certainly evolving maybe in a different direction from what people originally anticipated.

[00:17:08] And Mark, I think whether it be public cloud or the more recent trend towards private cloud, cloud computing also plays a huge role here, doesn't it, too?

[00:17:18] Yeah, absolutely.

[00:17:19] And I love that you expand the focus on various technologies here because clearly, right, AI is the topic that is top of the agenda for everyone.

[00:17:30] But don't underestimate the opportunity when all of these assets and applications come together.

[00:17:36] That is, by the way, why in 2022, as Paul and I were just about one year enrolled, we assessed kind of the needs of our practice and announced a $1 billion commitment to invest into assurance technology in three different areas.

[00:17:52] And one that you mentioned is about kind of like moving our applications to the cloud, integrating them further, making sure that we don't have separate applications where people copy and paste from them.

[00:18:03] But they really kind of like our interface that will streamline the data use throughout end to end.

[00:18:09] Let me give you a few examples.

[00:18:10] You mentioned it's not just AI.

[00:18:13] Automation is even bigger.

[00:18:14] Like we have just the linear decision trees that can help solve very complex problems here.

[00:18:20] Like even from the benchmarking perspectives, think about that, harnessing the knowledge of more than 500,000 people working on one global platform and all of the data points that we gather from that.

[00:18:30] You don't need generative AI to capitalize on that.

[00:18:33] You can provide the insights here, harvesting the data using kind of like less also power-consumptive technologies.

[00:18:41] And like seriously, Paul and I were just in Miami at the EY's Global Assurance Leadership Summit this week.

[00:18:48] And there were young folks.

[00:18:50] We call them global voices invited from all around our business.

[00:18:53] And one of their questions to me was, Mark, how do we kind of measure the sustainability impact of the technology that we use?

[00:19:00] And for me, that's part of that, using the right assets for the right use case.

[00:19:04] And it's not always AI.

[00:19:05] It's not particularly always generative AI.

[00:19:08] It might be linear formulas.

[00:19:10] It might be descriptive analytics being empowered with additional capabilities.

[00:19:14] Now, cloud computing.

[00:19:15] I mentioned that we moved our audit platform to the cloud.

[00:19:18] That was one of the first steps and included also the knowledge library to give our people seamless access to accounting and auditing knowledge.

[00:19:25] Then the next step was embedding automation.

[00:19:28] So really making sure that things like data transformation, confirmation process, exchanging information with the client, all of that was facilitated in a seamless interface.

[00:19:39] But the next frontier that we started then in 2022 with this investment, moving also our suite of analytics into one consistent platform that is now based on the cloud.

[00:19:50] And this now enables us that what we call the EY Helix Amaritics suite talks to the EY Canvas suite very seamlessly.

[00:19:58] And you can imagine the power when you have access to, as our teams analyze more than 800 billion of general ledger line items every year.

[00:20:05] When these are connected to the workflow, what that means compared to having them on local SQL servers or like working with Excel in separate applications and then copying things over into the workflow.

[00:20:17] That's huge.

[00:20:18] And the last bit to mention here is the category of user experience.

[00:20:23] Investing into very seamless and intuitive and harmonized user interface.

[00:20:28] People totally underestimate that.

[00:20:30] We all love shiny new faces.

[00:20:32] But seriously, some of those chatbots here give me a headache still.

[00:20:36] Like finding where to click, where to go next.

[00:20:39] How can I start a new session?

[00:20:41] Where to find the guidance?

[00:20:42] So we decided to invest from the very first moment, not only in kind of moving to the right infrastructure, bringing the right application layers in place and modernize them, but really making sure it's very intuitive, very seamless for our people.

[00:20:56] And that comes down to kind of like the icons, the buttons and all of that being kind of like intentionally designed to best use by our people as well as by our people.

[00:21:06] And I suspect there'll be people all around the world listening to you there and nodding their head in agreement.

[00:21:12] I think that some of those chatbots do give you a headache and it will resonate with so many people.

[00:21:17] And I also completely agree with you that the exciting thing is when all these emerging technologies converge.

[00:21:23] That's when something quite magical happens.

[00:21:26] So why would you say it is essential for firms to embrace these emerging technologies if they are indeed serious about enhancing things like client satisfaction and ultimately gaining a competitive advantage in the auditing market?

[00:21:42] Anything you'd like to share on what you're seeing here?

[00:21:44] But Paul, I'm happy to start with one example that also like you were able to introduce to our practice this week.

[00:21:51] And that is EYQ assurance knowledge.

[00:21:54] Well, we now apply generative AI to the library, that knowledge library that I mentioned for our people to harness the power of that technology when it comes to accounting and auditing knowledge.

[00:22:04] And if you see that interface, Neil, that the team design, which is not a separate chatbot or even kind of a search interface in a separate application, but it's embedded in that workflow and then comes back with kind of like the extracts and the search results here, giving that to the hand of our people.

[00:22:20] I think that demonstrates kind of like why it is essential for us to embrace the emerging technologies.

[00:22:26] We also learn with that.

[00:22:28] Like if we speak to regulators in a regulated industry, for example, the earlier we tap into certain technologies, the earlier we actually can think through what are some of the risks and kind of like how to mitigate them.

[00:22:40] So like for that search and summarization capability, just to name one, it was essential for us to have the source transparency at the forefront because we still want people to have access to the underlying vetted knowledge.

[00:22:54] These are kind of like from standard setters texts that where every word matters and like even slightly kind of like different words might make a difference.

[00:23:03] So like it helps to give people early access, but then kind of like comes with the need to still go into the details here.

[00:23:11] That was one of the considerations.

[00:23:13] Like, well, when you think about the other emerging technologies here, apart from that example, anything that you would like to add?

[00:23:20] Yeah, I think there's two dimensions, Neil, through which we look at it.

[00:23:23] One is obviously our clients are investing in emerging technologies for increasing the artificial intelligence.

[00:23:29] I've spoken about blockchain as well.

[00:23:31] Well, we need to understand those.

[00:23:33] We need to understand the technologies.

[00:23:34] We need to understand the risks associated with those technologies.

[00:23:37] We need to understand how those technologies are going to enable our clients' processes and their overall running of their business.

[00:23:44] And so fundamentally, from an audit perspective, we need to understand them.

[00:23:49] And there's no better way to understand something by practicing, by doing it.

[00:23:54] Right.

[00:23:55] And ultimately, that translates to when we start to actually apply those technologies ourselves internally.

[00:24:01] We've spoken a lot about AI already.

[00:24:03] And the use of artificial intelligence is not only giving us great opportunities to improve our user experience and deliver high-quality audits, but it also requires us to understand the risks, as well as the opportunities associated with something like AI.

[00:24:18] And that particularly includes understanding and looking at how to use AI responsibly, how to use it safely, how to use it ethically, how to make sure it's also giving you accurate resources and helping you do work in a high-quality way, but making sure that the AI, for example, the generative AI, is not creating planning solutions that people rely on without truly querying and understanding the data.

[00:24:43] So it is really important for us to really develop those technologies so that we can understand them and be able to serve our clients.

[00:24:53] But there's obviously also an opportunity to transform the way we deliver our services as well.

[00:24:59] Actually integrating those technologies into our delivery platform is obviously helping us to stay competitive and stay relevant in an increasingly competitive marketplace.

[00:25:07] So certainly from my perspective, when I joined EY 13 years ago now, technology was not a conversation that was had with clients during, for example, a competitive tendering scenario.

[00:25:23] It just wasn't the topic.

[00:25:24] We would talk about our network.

[00:25:25] We'd talk about our people.

[00:25:27] We'd talk about our experience.

[00:25:28] But technology wasn't a factor.

[00:25:29] Today, in some markets where you actually have mandatory audit rotations or tendering, our teams are constantly out in the market talking to clients.

[00:25:40] And one of the number one topics, which you can bet your bottom dollar is always going to come up, is technology.

[00:25:46] And that includes artificial intelligence.

[00:25:48] It includes blockchain.

[00:25:49] It includes cloud.

[00:25:50] It includes risks around things like cyber.

[00:25:52] And so it's just at the heart of everything we do today.

[00:25:55] And I think sometimes it can be incredibly easy to get distracted by just the technology and almost end up neglecting the culture side of things.

[00:26:05] And I think changing corporate culture, being more innovative, adopting a continuous learning mindset is equally as important, if not more so.

[00:26:14] So how are you seeing the integration of emerging technologies into audit practices requiring this fostering of a culture of innovation, promotion of continuous learning and development amongst all auditors?

[00:26:28] What are you seeing here?

[00:26:30] Look, first of all, I'm a firm believer that innovation rarely happens when you sharpen your pencil in front of a white paper and really think about, like, what's next to invent here?

[00:26:41] It happens when people collaborate.

[00:26:43] It happens when you face real-time problems, as you previously seen.

[00:26:47] And that's kind of like where we tap all of the knowledge and the curiosity of all of our people.

[00:26:54] So I mentioned 500,000 users overall on one platform, which means kind of like all of our users here, our professionals plus the clients.

[00:27:02] And honestly, feedback is kind of like just the first starting point of a culture where even when we build technology and roll that out, we from the very first moment need to make sure that we have the ability in the tool to submit feedback.

[00:27:15] That is like from a technical perspective, sometimes a simple form or a contact providing kind of like the contact points for the people.

[00:27:23] It also comes down to a network that really drowns in the local markets, in the offices, having champions.

[00:27:29] We call them ambassadors here that foster that and bubble up the ideas very quickly by being connected.

[00:27:35] And we have sounding boards where people regularly on certain domains come together wherever something happens.

[00:27:41] The radar with the speed of change here needs to be very close to work.

[00:27:45] The next one is about federated development.

[00:27:49] As I said, right, the central team year that we have is great, but it would not enable us to really kind of like go out and have the speed to test our technologies with MVPs, POCs at an early stage here, with some of them fail and it's good that they fail as we learn.

[00:28:07] So we tap into kind of like various markets that contribute to that.

[00:28:11] And just one example of the latest version of our EY-EBX General Ledger Enterprise was born at the West Coast of the US.

[00:28:18] And why was that?

[00:28:19] Because we are auditing a lot of kind of like the giant tech companies over there.

[00:28:23] And just imagine, right, with centralized ERP systems that a volume of data that Excel at a certain point kind of like came to its limits and kind of the processing power that on local service was there was not enough.

[00:28:36] And kind of then the complexity of the data also required another interface.

[00:28:40] So that was why these people started connected to the global team and then really scaled that up.

[00:28:45] The financial statement tie-out tool that we have here came from like the audit team of one of our largest banking auditing clients that really faced exactly the challenge of kind of these hundreds of pages of financial statements and the kind of very precious time in the short close cycle.

[00:29:01] They kind of like started to experiment and then the global team helped to scale it so that it's now available to all of our people around the world now going to the next languages here.

[00:29:12] And that's the power, right, of really kind of federate development.

[00:29:15] It's not just the ideation.

[00:29:16] It's even when we scale that the people in our team here that Paul and I have are sitting in more than 50 countries.

[00:29:24] Even the global team that we have kind of virtually connects because if like one idea started locally, it's not throwing something over the fence.

[00:29:31] But the culture of taking it over and that means embedding these people that started with the idea into the global team like myself here in Germany, Paul in London and many, many other peoples in many other countries.

[00:29:42] The last thing you said, the culture needs also some very systematic patterns.

[00:29:48] And one of that we saw is that learning cycles, like having certain milestone events every year, that's probably good to meet people, have some networking, etc.

[00:29:58] But doesn't still the need of people having the information, the training available whenever they need it.

[00:30:03] So the self-service kind of micro learning type.

[00:30:06] And we are very proud that EY batches now with all of the programs in particular on innovation technology are so well adopted.

[00:30:13] So more than half a million of batches have already been issued to our people since the inception of that program.

[00:30:19] That was part of really kind of bringing in that culture that people have the chance to educate themselves.

[00:30:24] And when they're educated, it makes them even easier to contribute to the overall job.

[00:30:29] 100% with you.

[00:30:30] And Paul, is there anything that you're seeing here around this turn?

[00:30:33] I think what's been most interesting from my perspective, alongside some of those angles that Mark highlighted,

[00:30:41] is just the fact that innovation and technology has required our professionals and our teams to get even deeper under the skin of what our clients do.

[00:30:52] Understanding our clients' data, understanding their processes, understanding the complexities associated with their IT environment,

[00:30:59] understanding how to access that information and wrap data, and to use our data to collect all the evidence.

[00:31:05] That has required a level of technical understanding from our people, but has also required them to get much closer to our clients,

[00:31:13] whilst remaining independent, but working even more closely alongside management,

[00:31:18] and the finance and accounting and IT teams that our people work with every single day.

[00:31:23] So when you think about client-centricity and the relevancy of an audit and the relevancy of the audit profession,

[00:31:30] that is really where I would point to technology and say that's really driving that relevancy of the profession today

[00:31:36] as we think about the culture of innovation needed within a firm, encouraging people to always be curious,

[00:31:42] always be sceptical, and always be looking out for the risks and the new opportunities associated with technologies.

[00:31:51] And of course we are at that magical time of year where self-proclaimed futurists, experts, and analysts

[00:31:58] all try and determine what are the big trends that are going to take shape in 2025.

[00:32:04] I think Gartner mentioned agentic AI.

[00:32:07] There's a lot of talk around a move to the private cloud, driven by data sovereignty and artificial intelligence.

[00:32:14] But I'm curious, from what you're seeing in your industry, what other tech trends do you think will impact the industry next year?

[00:32:21] Polishing the crystal glass wall is a bit against the nature of a German public auditor,

[00:32:27] but let me nevertheless give it a try here.

[00:32:31] If you have technology as such and the advancements that we also observe here, as Paul said,

[00:32:36] kind of having access to not only these alliance partners, partnerships,

[00:32:40] we see what happens in our clients, academia here, we carefully observe that.

[00:32:45] But we have to acknowledge that one is the advancement in tech,

[00:32:49] and also kind of the appetite to always have the next shiny thing.

[00:32:53] And then it comes that there are two additional forces.

[00:32:55] One is the real expectations, client people, regulators,

[00:32:59] and then the regulation, how kind of like it allows us to progress.

[00:33:03] So the maturity of the tech, the expectations here of the stakeholders plus the regulation,

[00:33:08] that triangle here needs to come magically together that it really becomes relevant for us.

[00:33:13] And I have to admit, when I kind of probably 10 years ago,

[00:33:17] really was so excited to see the first BI applications,

[00:33:22] like low-code applications giving us the ability to go beyond what actual people tables were doing.

[00:33:28] Like look at controlling departments today.

[00:33:30] Excel is still everywhere.

[00:33:31] And kind of despite kind of like the opportunity,

[00:33:34] it hasn't really scaled to its full potential yet.

[00:33:37] And you mentioned the same year around AI.

[00:33:40] Now in the domain of AI, we definitely kind of like have very promising kind of work

[00:33:45] on the front of AI agents,

[00:33:47] because we believe that the combination of different tasks related capabilities

[00:33:53] into something that brings it holistically to our people,

[00:33:56] we mentioned the chatbots and the headache here is kind of like the way forward,

[00:34:00] where it's not just arbitrarily kind of like little gadgets here and there.

[00:34:04] It's kind of like the idea of having the system that has broader capabilities

[00:34:09] and even proactively recommends that.

[00:34:11] That's for us kind of like rather on the maturity side of the hype side.

[00:34:15] Let me now give you two that people might be a bit surprised about.

[00:34:20] One, I think, is about quantum computing.

[00:34:22] So we've started early to invest here for various reasons.

[00:34:27] One is, first of all, the sheer processing power.

[00:34:30] And with the level of information that our teams face here

[00:34:34] and that we have access to at the clients,

[00:34:36] logically, right, with the processing power,

[00:34:39] that accelerates the abilities here very quickly.

[00:34:41] But also from a risk perspective, encryption is one of that.

[00:34:44] And as we'll exchange information here with our clients,

[00:34:47] we kind of like one of the things that we need to really force in here

[00:34:50] is how can we ensure data security at the high standards that we have right here.

[00:34:55] The second one that I mentioned is one that comes up every other year.

[00:35:01] And it partially annoys me, I have to say.

[00:35:04] Because Paul and I have been in wave spaces, our innovation labs, again, right,

[00:35:08] probably decades ago, seeing the first kind of like virtual reality,

[00:35:13] augmented reality glasses where after 10 minutes, right,

[00:35:16] everything here hurts and you really kind of, you felt that it was something,

[00:35:21] but the devices were in barrier.

[00:35:22] And we are slowly moving towards something where they just become

[00:35:26] kind of more realistically something that you use on a daily basis.

[00:35:29] But I still think there is some way to go.

[00:35:32] But I believe, firmly believe in that potential.

[00:35:36] And you see that with kind of people they just wanted,

[00:35:39] the metaverse hype that we saw here,

[00:35:41] of kind of all of these comic type creatures walking through virtual reality rooms.

[00:35:46] But in two-dimensional rooms, like just combine all of that.

[00:35:50] I sincerely believe that people sitting in front of a laptop

[00:35:53] with a screen as small as the one that I'm just looking at at a keyboard here

[00:35:59] is not the latest stage that we'll see.

[00:36:02] When it comes to the interaction of humans

[00:36:05] that are still essential to deliver these services,

[00:36:08] they empower them, but enabled by technology.

[00:36:10] I see that these interfaces, human machine interfaces

[00:36:14] and virtual reality glasses might be one,

[00:36:17] touchscreen might be one.

[00:36:18] But I even go further without now explicitly mentioning it

[00:36:21] is something that we observe very carefully

[00:36:23] because we truly believe that it restricts people.

[00:36:26] It restricts people to still type

[00:36:28] and the voice recognition that then kind of like is there

[00:36:31] or like seeing things just two-dimensionally on the screen.

[00:36:35] So you can hopefully feel my passion

[00:36:37] when it comes to kind of like that part

[00:36:39] of the opportunities with technologies that still meet you.

[00:36:43] Wow, what a great answer,

[00:36:45] especially considering you had reservations

[00:36:47] about answering that with your cautious nature.

[00:36:51] And Paul, your turn to look into my virtual crystal ball.

[00:36:54] What do you see ahead?

[00:36:56] Okay, Neil, you mentioned AI agents

[00:36:58] as one technology theme or opportunity,

[00:37:01] but many people are high-righting at the moment.

[00:37:03] And I do see that it has some really interesting potential.

[00:37:06] Actually, it's something that we're starting to explore

[00:37:08] in much more depth over the next few months.

[00:37:11] And why do I say that?

[00:37:13] I mean, it's two years now since the launch of ChatGPT

[00:37:16] and many organizations have now gone,

[00:37:18] as we have done with EY with our own EYQ product,

[00:37:23] is actually putting in place a private version

[00:37:25] of ChatGPT internally,

[00:37:27] keeping it securely ring-fenced

[00:37:28] within their own corporate environment.

[00:37:31] Organizations are now deploying technologies

[00:37:33] like Microsoft 365 Copilot as well.

[00:37:36] I would characterize many of those

[00:37:38] as tools that help you,

[00:37:42] help you as a professional, right,

[00:37:43] or help you as a user.

[00:37:45] Whereas if you think about AI agents,

[00:37:47] the potential there is,

[00:37:48] they're more of a, rather than a helper,

[00:37:50] they're actually a doer, right?

[00:37:52] And that's where you can use this concept

[00:37:54] of an AI agent or an autonomous AI agent framework

[00:37:57] to actually bring together multiple AI skills,

[00:38:00] which can be classical AI skills

[00:38:02] or generative AI skills,

[00:38:04] which can perform individual tasks

[00:38:06] or micro actions,

[00:38:08] together with a range of other plugins as well.

[00:38:11] Even simple plugins to calculator,

[00:38:14] which allow you to actually perform multiple tasks

[00:38:17] and multiple activities in a stream,

[00:38:19] a stream altogether,

[00:38:21] which actually effectively is autonomously

[00:38:23] performing multiple steps

[00:38:25] that you might need to do.

[00:38:26] And so we've seen some really interesting potential

[00:38:29] in some of the hackathons and POCs

[00:38:32] that our teams have been developing

[00:38:33] to really actually look at the potential

[00:38:35] to automate multiple tasks together.

[00:38:38] And really, it's just been so impressive

[00:38:41] to see the potential of the AI,

[00:38:43] where it's really learning how to do things

[00:38:45] with only minimal guidance and input from us

[00:38:48] at the very beginning of the hackathon.

[00:38:51] And so I think there's a lot of potential there,

[00:38:53] and that's something that we're really excited

[00:38:54] to explore in line with some of our first releases

[00:38:57] of generative AI technology,

[00:38:59] which we're focused on over the coming months.

[00:39:02] Well, I think you've both done a fantastic job

[00:39:05] of demystifying tech

[00:39:07] and highlighting some of those real-world problems

[00:39:09] that you're solving here

[00:39:11] and in a language that everyone can understand.

[00:39:13] And to give everyone listening

[00:39:15] one final valuable takeaway,

[00:39:17] is there any advice that you'd offer

[00:39:18] to somebody listening working in the industry

[00:39:20] wanting to leverage some of these new tech tools

[00:39:23] that we're talking about,

[00:39:24] but maybe unsure where to start.

[00:39:26] Any advice that you'd leave them with?

[00:39:29] Yeah, maybe just a couple of reflections from my side.

[00:39:32] Maybe thematically, first,

[00:39:33] I would say a couple of things.

[00:39:35] One, be curious, right?

[00:39:36] Look to learn, look to learn about technologies.

[00:39:40] Just really get under the skin

[00:39:41] and don't be afraid to ask

[00:39:44] the stupidest question possible,

[00:39:45] because actually it turns out

[00:39:46] it's usually the slightest question.

[00:39:48] So honestly, get under the skin,

[00:39:50] be proactive, but also be skeptical.

[00:39:53] Be skeptical about whether or not

[00:39:54] these technologies have real potential,

[00:39:56] have real ROI attached to them,

[00:39:59] and just learn.

[00:40:00] And so be back curiosity about proactivity,

[00:40:04] of being skeptical as well.

[00:40:05] Those are great, I would say,

[00:40:07] thematic considerations

[00:40:08] for someone who's getting involved in this space

[00:40:11] and wants to get more involved

[00:40:12] in technology to consider.

[00:40:15] Now, maybe let's get a bit more practical, right?

[00:40:17] At a practical level,

[00:40:18] if you're working in,

[00:40:19] whether it's an accounting department

[00:40:21] or if you're working in an audit firm,

[00:40:23] I would say one could speak

[00:40:24] to the responsible individual

[00:40:26] who is ultimately leading on tech

[00:40:28] or innovation or digital.

[00:40:31] That could be someone

[00:40:32] within a functional team

[00:40:34] who is the IT contact,

[00:40:36] or it could be someone

[00:40:37] who's an innovation lead in a department.

[00:40:39] Sometimes you might find out

[00:40:41] there is not one person.

[00:40:43] There isn't someone specifically

[00:40:44] that you need to talk to.

[00:40:45] That might actually be an opportunity

[00:40:47] to step in, right?

[00:40:48] And we've seen that over the last years

[00:40:50] where people who have gone into this space

[00:40:52] have done it organically

[00:40:53] because they were curious

[00:40:54] and they were professional

[00:40:55] and they wanted to get involved.

[00:40:56] So I think, number one,

[00:40:58] speak to the relevant person

[00:41:00] or find out who the right person

[00:41:01] is to talk to on tech,

[00:41:03] get to know them,

[00:41:04] understand more about what they're doing,

[00:41:06] what their role is,

[00:41:07] and really, really,

[00:41:08] that could be an opportunity as well.

[00:41:10] And we see that

[00:41:11] where we've got dedicated account leads

[00:41:13] on all of our top accounts

[00:41:14] who are focused on tech and innovation.

[00:41:16] We've got them in every single one

[00:41:18] of our geographies around the network.

[00:41:20] And it's just been fantastic

[00:41:22] to see this organic building,

[00:41:23] which has then become

[00:41:24] a very structured building

[00:41:25] of a network

[00:41:26] of connecting technology professionals

[00:41:28] across our business.

[00:41:30] Then maybe the final thing

[00:41:31] I would flag as well

[00:41:32] is when it comes to actually

[00:41:34] some of the technology itself,

[00:41:35] start using it,

[00:41:36] start playing around with it,

[00:41:37] start exploring its potential,

[00:41:39] and that increasingly today

[00:41:41] involves things like no code

[00:41:43] and low-code applications.

[00:41:45] Mark mentioned Power BI earlier,

[00:41:48] building out automation solutions,

[00:41:50] analytics.

[00:41:51] Now you can start to experiment also

[00:41:53] with some of the early capabilities

[00:41:55] that are being democratized

[00:41:56] around generated AI

[00:41:58] and really start to explore

[00:41:59] the potential of building

[00:42:00] your own potential skills

[00:42:01] and designing your own prompt

[00:42:03] and tweaking your own prompts

[00:42:04] to get to the right information.

[00:42:06] So those, for me,

[00:42:07] are some of the kind of

[00:42:08] big picture things

[00:42:09] that people should be considering,

[00:42:10] but also some of the practical steps

[00:42:12] to really get involved in this thing.

[00:42:14] Wow, fantastic advice.

[00:42:16] So many big takeaways there.

[00:42:18] Mark, over to you.

[00:42:19] Any advice for everyone listening?

[00:42:21] That was comprehensive.

[00:42:23] Yeah.

[00:42:23] So my advice here is

[00:42:24] have a colleague or a good friend

[00:42:26] like I have in Paul

[00:42:27] that you can always ask

[00:42:28] for recommendations,

[00:42:29] whether it is kind of like

[00:42:31] sometimes reading a book,

[00:42:32] might be an e-book,

[00:42:34] a podcast,

[00:42:35] kind of like subscribing

[00:42:36] to a newsletter,

[00:42:37] the micro-learnings here,

[00:42:39] but be curious.

[00:42:40] I fully agree with Paul.

[00:42:41] Yeah, 100%.

[00:42:42] And of course,

[00:42:43] there is one thing

[00:42:44] that we've all got in common

[00:42:46] at the moment,

[00:42:46] and that is that real pressure

[00:42:47] on us all to be in a state

[00:42:49] of continuous learning

[00:42:51] and curiosity plays

[00:42:52] a big part in that.

[00:42:54] And as two people

[00:42:54] who are helping

[00:42:55] lead the way here

[00:42:56] from London to Germany,

[00:42:59] one final question.

[00:43:00] Where or how

[00:43:01] do you self-educate?

[00:43:02] Mark,

[00:43:03] I'll let you answer

[00:43:03] this one first.

[00:43:04] Anything you can share

[00:43:05] around that?

[00:43:06] I just re-emphasize

[00:43:08] what Paul said.

[00:43:09] People on my team

[00:43:10] and even kind of leaders

[00:43:11] at Microsoft

[00:43:12] to know that

[00:43:13] sometimes I say

[00:43:15] I hate PowerPoint,

[00:43:16] which is not against

[00:43:17] the application,

[00:43:18] I always clarify,

[00:43:19] but about kind of like

[00:43:20] very high-level

[00:43:21] aggregates of information.

[00:43:23] As a starting point,

[00:43:24] that is fine,

[00:43:25] a YouTube video,

[00:43:26] a TED Talk,

[00:43:27] et cetera.

[00:43:27] But I really kind of like

[00:43:29] the moment,

[00:43:30] and that's in my nature,

[00:43:31] kind of like

[00:43:32] also in the profession

[00:43:33] that I am,

[00:43:33] I go deeper

[00:43:34] and I'm kind of

[00:43:35] it really goes down

[00:43:36] to reading kind of

[00:43:37] latest studies,

[00:43:38] going into academia.

[00:43:40] Most of it

[00:43:40] is publicly available

[00:43:42] and you can use

[00:43:43] kind of just

[00:43:43] the normal search engines

[00:43:45] or even kind of like

[00:43:46] conversational chatbots

[00:43:48] to give you an entry point

[00:43:49] and then I personally

[00:43:50] really kind of love

[00:43:51] to go deeper

[00:43:52] and have access

[00:43:53] to the underlying literature

[00:43:55] that is behind that.

[00:43:56] The good news about that

[00:43:57] is at the end of it,

[00:43:58] if you really stay awake

[00:43:59] until the end of it,

[00:44:00] it contains

[00:44:01] all of these lists

[00:44:03] of additional

[00:44:03] supplemental sources

[00:44:05] and references.

[00:44:06] So if you don't want

[00:44:07] to go deeper,

[00:44:07] it's kind of like

[00:44:08] a weapon that

[00:44:09] that you can thriller.

[00:44:11] Oh, brilliant.

[00:44:13] Paul,

[00:44:13] any secrets

[00:44:15] you can share

[00:44:16] from your secret source

[00:44:17] on how you self-educate,

[00:44:18] how you keep up to speed

[00:44:19] with the pace of change?

[00:44:21] I think what has been

[00:44:23] really helpful

[00:44:24] the last few years

[00:44:25] is just how easily

[00:44:26] information is now

[00:44:27] at our fingertips.

[00:44:29] And so,

[00:44:29] what's YouTube?

[00:44:30] I love it, right?

[00:44:31] It's just the best place

[00:44:32] to go to get immersed

[00:44:34] into a different topic.

[00:44:35] It can lead you down

[00:44:35] some rabbit holes,

[00:44:36] but it's just a fantastic

[00:44:37] source of learning.

[00:44:39] And more recently,

[00:44:40] looking at ChatGPT,

[00:44:41] I find it really interesting

[00:44:43] because you can obviously

[00:44:44] learn about a technology,

[00:44:45] but if you don't

[00:44:46] understand something

[00:44:47] which is very complex

[00:44:48] and very technical,

[00:44:49] you can ask it

[00:44:50] to simplify the answer

[00:44:51] and then signify

[00:44:52] the answer even further.

[00:44:54] And then you can expand

[00:44:55] in different directions.

[00:44:57] So if you want

[00:44:57] a big picture view

[00:44:58] or if you want to understand

[00:44:59] a very technical topic,

[00:45:01] I think it's a great source

[00:45:02] of information

[00:45:03] you can go to

[00:45:03] to be able to actually

[00:45:04] understand something

[00:45:06] that you may historically

[00:45:07] have not felt comfortable

[00:45:08] asking a question around.

[00:45:10] And what's really helpful now

[00:45:13] increasingly is

[00:45:14] these technologies,

[00:45:15] these generative AI applications

[00:45:17] or large language models,

[00:45:19] the tech companies

[00:45:20] that are providing those

[00:45:21] are equipping the answers

[00:45:22] with links

[00:45:23] to the relevant source material

[00:45:24] as well.

[00:45:25] So as Mark mentioned,

[00:45:27] when you read something,

[00:45:27] you'll be able to go

[00:45:28] to additional references

[00:45:29] and additional reference material

[00:45:31] to do that now

[00:45:32] is really valuable.

[00:45:33] What that all points to

[00:45:34] for me, though,

[00:45:36] is that you can actually

[00:45:37] use the technology

[00:45:38] to get information

[00:45:40] in your fingertips

[00:45:40] at the point

[00:45:41] when you need

[00:45:42] to consume it.

[00:45:43] And that's actually

[00:45:44] something that Mark

[00:45:45] and I are working on

[00:45:46] right now with our teams

[00:45:47] is to bring things

[00:45:48] like short snippet videos

[00:45:50] directly to our end users

[00:45:52] right at the,

[00:45:53] in our technology platform,

[00:45:55] right at the point in time

[00:45:56] when they need

[00:45:56] to consume that.

[00:45:57] So if you're performing

[00:45:58] a specific task,

[00:45:59] a specific auditing task,

[00:46:01] or if you're using

[00:46:02] a piece of new functionality,

[00:46:04] you're going to want

[00:46:04] to get access

[00:46:05] to that enablement

[00:46:07] and that learning

[00:46:08] around that topic

[00:46:10] right at your fingertips.

[00:46:11] So the ability

[00:46:12] to have technical

[00:46:13] accounting answers

[00:46:14] and auditing answers

[00:46:16] right at your fingertips

[00:46:16] is that for one thing.

[00:46:17] But what about also

[00:46:18] bringing short videos

[00:46:19] in as well

[00:46:20] to equip our people?

[00:46:22] And I think

[00:46:22] that point in time

[00:46:24] consumption of learning

[00:46:25] is something

[00:46:26] that we will all do

[00:46:27] in and outside of work

[00:46:28] over the coming years.

[00:46:30] And I think

[00:46:30] it's just a great example

[00:46:31] of where technology,

[00:46:32] including AI,

[00:46:33] is just going to help us

[00:46:34] all elevate the roles we do

[00:46:36] and how we live our lives.

[00:46:38] Yeah,

[00:46:39] I completely agree with you.

[00:46:40] There's another tool,

[00:46:41] I think it's called

[00:46:42] Notebook LLM

[00:46:43] from Google at the moment.

[00:46:44] You can give it

[00:46:45] 10,000 words

[00:46:46] on a complex topic

[00:46:47] and it will create

[00:46:48] a podcast

[00:46:48] with two different speakers

[00:46:50] that will simplify

[00:46:51] that topic

[00:46:52] so you can just listen

[00:46:53] and it will break it down.

[00:46:54] Incredibly useful

[00:46:55] for learning too.

[00:46:56] So,

[00:46:56] so many big takeaways there.

[00:46:58] And for anybody listening

[00:46:59] just wanting to find out

[00:47:01] more information

[00:47:02] about anything

[00:47:02] we talked about today

[00:47:04] or connecting

[00:47:05] with you personally,

[00:47:06] anywhere you'd like

[00:47:07] to point them

[00:47:07] over to you first,

[00:47:09] Mark.

[00:47:09] You can't imagine

[00:47:10] how many pings

[00:47:11] we get every day

[00:47:13] and that is lovely.

[00:47:15] Well,

[00:47:15] sometimes it takes

[00:47:16] a moment

[00:47:16] to respond to them.

[00:47:18] LinkedIn,

[00:47:18] the email address,

[00:47:19] if you go to

[00:47:20] our ey.com homepage,

[00:47:21] you find our profiles,

[00:47:23] feel free to reach out.

[00:47:24] We love that.

[00:47:24] Not only because

[00:47:25] we're always searching

[00:47:26] for more talent

[00:47:27] but any contact here

[00:47:28] if you're really curious

[00:47:29] brings us one step.

[00:47:31] Perfect.

[00:47:32] Paul,

[00:47:32] assuming it's exactly

[00:47:33] the same for yourself there,

[00:47:35] right?

[00:47:35] Or is there anything

[00:47:35] you'd like to add?

[00:47:36] Yeah,

[00:47:37] absolutely.

[00:47:37] Please do check out

[00:47:38] our ey.com presence

[00:47:40] on LinkedIn profiles.

[00:47:42] Mark and I

[00:47:42] are both pretty active

[00:47:43] in promoting

[00:47:44] the latest

[00:47:45] interesting snippets

[00:47:46] that we've seen.

[00:47:47] Articles,

[00:47:48] sport leadership,

[00:47:49] the latest development.

[00:47:50] So you can rest assured

[00:47:52] that there's usually

[00:47:53] one or two bits

[00:47:54] of good content

[00:47:55] that we've got

[00:47:56] on our LinkedIn sites

[00:47:57] and definitely

[00:47:57] that's the best place

[00:47:58] to get a hold of us.

[00:47:59] Awesome.

[00:48:00] Well,

[00:48:00] I'll add links

[00:48:01] to everything there

[00:48:02] to make it nice and easy.

[00:48:04] And as I said,

[00:48:05] we covered so much

[00:48:06] from how auditors

[00:48:07] are facing

[00:48:07] some of the biggest challenges

[00:48:09] in the digital age

[00:48:10] but also how technology

[00:48:11] is helping

[00:48:12] streamline tasks,

[00:48:13] boost productivity

[00:48:14] and ensure

[00:48:15] higher accuracy levels

[00:48:16] by harnessing things

[00:48:18] like AI

[00:48:18] and automation

[00:48:19] but of course

[00:48:20] it's not all about AI.

[00:48:22] There's other

[00:48:23] emerging technologies

[00:48:24] that are converging

[00:48:25] blockchain,

[00:48:26] cloud computing

[00:48:27] and you've also given

[00:48:28] so many nuggets

[00:48:29] of gold

[00:48:30] and advice

[00:48:31] and valuable takeaways.

[00:48:32] So just a big thank you

[00:48:33] to both of you

[00:48:34] for taking the time

[00:48:35] to sit down with me

[00:48:36] and share your insights.

[00:48:37] Thanks again.

[00:48:38] Thank you, Neil.

[00:48:39] Thank you, Neil.

[00:48:40] I think our exploration

[00:48:42] with EY's leaders today

[00:48:44] has painted

[00:48:44] somewhat of a vivid picture

[00:48:46] of an auditing industry

[00:48:48] that's on the cusp

[00:48:49] of a technological revolution.

[00:48:52] And with significant investments

[00:48:54] channelling into AI,

[00:48:55] blockchain

[00:48:56] and cloud technologies

[00:48:57] it seems the goal

[00:48:59] is not just to meet

[00:49:00] the evolving demands

[00:49:01] of the field

[00:49:02] but also

[00:49:03] pioneer a new era

[00:49:05] of efficiency

[00:49:06] and precision

[00:49:07] in the world

[00:49:08] of auditing.

[00:49:09] But how do you see

[00:49:10] these technologies

[00:49:11] influencing

[00:49:12] your professional practices

[00:49:14] or the broader industry standards?

[00:49:16] Are there any

[00:49:17] other innovative technologies

[00:49:19] that you can think of

[00:49:20] that could further

[00:49:21] transform the world

[00:49:22] of auditing?

[00:49:23] This is where

[00:49:24] I invite you

[00:49:25] to share your perspectives.

[00:49:26] This show

[00:49:27] is a dialogue

[00:49:28] not a monologue

[00:49:29] so please

[00:49:30] join me

[00:49:31] in this ongoing discussion

[00:49:32] about the future

[00:49:33] of technology

[00:49:34] in business.

[00:49:35] Email me

[00:49:36] techblogwriteroutlook.com

[00:49:38] LinkedIn

[00:49:39] x Instagram

[00:49:40] at Neil C. Hughes

[00:49:42] Please

[00:49:42] let me know

[00:49:43] your thoughts.

[00:49:44] We've had so many

[00:49:45] great guests lately

[00:49:46] and sometimes

[00:49:47] I am incredibly guilty

[00:49:49] of keeping my head down

[00:49:51] and recording

[00:49:52] so many different interviews

[00:49:53] I've got so many

[00:49:54] great guests to come

[00:49:55] but I just want to

[00:49:55] take a time out

[00:49:56] to thank you

[00:49:57] my listeners

[00:49:57] on what makes this show

[00:49:59] you tuning in

[00:50:00] every day

[00:50:01] so thank you so much

[00:50:02] and hopefully

[00:50:03] you will join me

[00:50:04] again tomorrow

[00:50:05] I'd love to speak

[00:50:05] with you all again

[00:50:06] but that's it for today

[00:50:08] so bye for now.