Episode 349 - Paul Turley, general manager, ServiceNow Ireland

Today we’re tackling a problem that every consumer and every business leader can relate to: why is customer service still so frustrating in an age of AI, automation and digital transformation?

Despite years of investment in technology, new research from ServiceNow reveals that Irish consumers are losing an astonishing 284 million hours every year dealing with customer service issues. Even more striking, nearly half of consumers say they would switch brands after just one poor customer service experience.

So what’s going wrong? Why are businesses still struggling to deliver seamless customer experiences? And with AI dominating boardroom conversations, are companies focusing on the right solutions—or simply adding more complexity to already broken processes?

To help us unpack these questions, I’m joined by Paul Turley from ServiceNow, a company at the forefront of helping organisations modernise customer service and employee experiences through digital workflows and AI-powered solutions.

In our conversation, we’ll explore why customer service remains one of the biggest pain points for consumers, the common mistakes organisations are making in their AI and customer experience strategies, and the practical steps businesses can take to improve service without committing to massive technology budgets.

Visit www.thinkbusiness.ie for more news and supports for start-ups and SMEs in Ireland. If you want to start and grow a business, ThinkBusiness.

Transcript

SPEAKER_00 0:19

Hello and welcome back to the latest Think Business Podcast Powered by Bank of Ireland. Despite years of investment in technology, new research from ServiceNow reveals that Irish consumers are losing an astonishing 284 million hours every year dealing with customer service issues. Even more striking, nearly half of consumers say they would switch brands after one poor customer service experience. So what's gone wrong? Why are businesses still struggling to deliver seamless customer experiences? And with AI dominating boardroom conversations, are companies focusing on the right solutions or simply adding more complexity to already broken processes. To help us unpack these questions, I'm joined by Paul Turley from ServiceNow, a company at the forefront of helping organizations modernize customer service and employee experiences through digital workflows and AI-powered solutions. In our conversation, we'll explore why customer service remains one of the biggest pain points for consumers, the common mistakes organizations are making in their AI and customer experience strategies, and the practical steps businesses can take to improve service without committing massive technology budgets. Paul, you're very welcome to the podcast. Who knows? You know, the impact of all this. But AI itself, I mean, if you use it, anyone who says they aren't using it are lying because it's it's it's it's so pervasive and it's so easy to use. And it's literally it's like someone switched on a light bulb in 2002, or sorry, 2022, and then suddenly like now we all have gen AI and it's flying along um as if it's always been here. But the reality is it presents more uncomfortable truths than I think most people are fairly willing to recognize. And I think what we're going to talk about today is the impact of AI on customer service and how businesses are dealing with their customers. Uh to begin with, tell tell us about um ServiceNow and uh the roads that led you to where you are today with ServiceNow.

SPEAKER_01 2:22

Yeah, and uh John, great to be here and thanks for having me on the on the podcast today. It's it's a pleasure. So so yeah, so ServiceNow is a company was founded um 21 years ago in the US um by a guy called Fred Luddy, and his vision was always to have a platform that made it easier for people to get things done, both at mainly at work, but that's since expanded out into you know, how do we make it easier for citizens to interact with government? How do we make it easier for customers to interaction interact with service providers and and um sellers of services? So that was 21 years ago. Um and ServiceNow today is is over 28,000 employees um and has grown significantly both globally and um, I guess for for this podcast, more importantly here in Ireland. So four and a half years ago, we we we made a pretty big investment in Ireland, um, both in terms of our our team that serve our Irish customers, which is the team that I run. But um more broadly than that, we now have over 650 people employed here in Ireland. We have people in each of the 32 counties and north and south uh working for service now, and over 30 nationalities in the workforce here. And we we moved into a new building two years ago now in Dawson Street in the centre of Dublin, um, which has been uh which have been which has been great. So with that investment, our our our local business has grown. Um we're working with some of Ireland's greatest companies, the likes of Kerry Group, um Glombia, Icon, etc., and some of the major service providers um servicing the Irish market like Auxillian, Argo, Kenos, um Um among others. So so yeah, the business has grown, the team has grown, and um it's been it's been it's been great. So that's that's been the journey so far. But I guess the the the reason for this call or this conversation is we recently conducted a piece of research globally, um across 35,000 people, but um over 1200 respondents here in Ireland, and it was all around customer service. And I think the key findings um in this AI world is that customers actually want human connection, not just speed. And and service reps, the people who are servicing are the people that we deal with, people like us, people who are serving us every day, they need to be empowered rather than just which is the the narrative is that they're all going to be replaced, which we we we don't we don't believe uh that that would be the case. They need to be empowered to serve customers better, and we'll talk a little bit about that later. Um, but the third part of the research, which is interesting, is that the focus from an executive level in many of these organizations is that they're investing in more on the efficiency side, and by invest by overinvesting in efficiency and driving those efficiencies and cost savings, and and maybe looking at this as a as a way to cut employee numbers, they're risking customer loyalty because we're finding that the the um I suppose the level of patience of customers is dwindling, and and you you you only get one or two shots at this, and customers are very quick to change. So they're the three key findings of this piece of research.

SPEAKER_00 5:59

And that and that's the thing that interests me, is like I, as anyone else who's seen AI, I I I'm both in awe of its capabilities and a little bit terrified, but also uh I use it myself. Uh, it comes in handy for certain time-consuming tasks that used to lose hours on, that now I can cut down to minutes, and allows me uh I'd like to think ultimately to be able to think more clearly about what I'm doing and put my full mind to my job as opposed to cutting corners, which is sort of what people think that AI does. And some people I've heard have cut back on hiring because they believe that well, AI can do a lot of things. I've heard that a lot in the legal profession, for example. Um, but you're right, I think people like doing business with people. And if I'm, for example, doing something as serious as maybe taking out a mortgage or um, you know, I need to maybe it's a medical assist situation, I want to talk to another human being who's gonna kind of think about what I'm saying as opposed to you know a machine. And the thing is, human nature seems to want to go better, faster with newer things, and suddenly um, you know, if they take the human out of the loop, they might be saving money. But the reality is, like, you know, if I have a less than satisfactory experience somewhere, I'm not gonna go back to that business. For you know, the the there's an adage in business that uh, you know, it's it's easier to get a customer, sorry, it's it's easier to keep a customer than lose a customer, or it's better to keep a customer than than you know, try and win them back again because you know it's harder, right? So I think you're totally right. I think AI should certainly boost your efficiencies, but it shouldn't replace the human. And if I'm especially if it's large high-value transactions, I uh or even just generally, if I have a good experience in a shop or somewhere or a restaurant, uh I'm more likely to go back because I like the people.

SPEAKER_01 7:56

Yeah, I mean, absolutely. I mean, it's it's like the old adage of trust is earned in drops and lost in buckets, right? So you you you you mess up once and and you lose that trust. And once you lose that trust, you you it's very hard to earn that back. I guess the key the key point I would say, John, is is that people want to deal with humans. Okay, we that's been the same from time immemorium, but they also want to deal with humans who are empowered to actually help them. And they don't want to deal with humans who have to say, hold on a second, I need to log into this system or I need to log into that system in order to help me. They want to deal with humans who have the technology at their fingertips to actually offer that help in the most efficient manner possible. Personally, I prefer to deal with an empowered robot than an unempowered human if it meant that I was I wasn't sitting on the phone for for you know a half an hour when I could be on the phone for five minutes or I could be on a on um an empowered chatbot. So from from our perspective and from ServiceNow ServiceNow's perspective, what we're trying to help our clients do is allow these complex workflows. So if you think about most customer service requests, they're complex, right? And and they're gonna get more complex. Humans are gonna be dealing with more complex customer issues as AI becomes more pervasive. Because AI will deal with all the mundane, the run-of-the-mill, the you know, the stuff that just can be done like that. Humans are gonna be dealing with the more complex cases, and the more complex cases are gonna involve um engagement with potentially multiple different systems. I'll give you an example. So everybody thinks um, no, it's not a particularly customer service example, but hopefully it lands the point. If you have a new joiner in a company, everybody thinks that's a HR process. But it's not a HR process. It there's parts of HR in it, obviously, but it's also the new person is gonna need a laptop, the new person is gonna need access to the systems on day one, not day 10, for them to do their job. The new person is gonna probably need some um uh expenses or some there's there will be finance parts of that. There will be potentially learning and development and certification, um, meaning that they won't be able to do certain parts of their job until they're trained or they've done. You think of a construction use case, they might have to get a safe pass, or in an airport environment, they they're gonna have to go through you know, preach like um character checks and all that kind of stuff. So there's lots and lots of different parts to a new joiner joining a company, and that requires integration with lots of different systems. But what's happen what happens today is that employees, customers, people serving employees and customers, they have to they have to interact with a myriad of different systems. The average in a large company, by the way, is over 370 systems on a day-to-day basis. There are 370 things that people need to use. Not not everybody needs to use them, but on average, to get their job done. And that's that's driving a massive amount of inefficiency. So the stat from the research is that 284 million hours were lost in Ireland last year by people waiting to be served by customer service agents. And that you think about that, that's a massive tax on our efficiency as a country. But it's also a huge amount of toil on the poor people in the back office who are trying to serve these customers, but they don't have access to the right data, they don't have access to the right systems, they're not being empowered to do their job properly. And if you put AI on top of this, it's just gonna make it worse. It's gonna make that hornet's nest worse and actually make them more efficient, more inefficient, and uh and increase the churn that people they're just gonna say, I'm not doing these jobs anymore. So that that's that's what we're trying to enable and empower.

SPEAKER_00 12:01

Yeah, so the bottom line is that it looks like businesses are going about AI the wrong way, in the sense that, oh yeah, AI is great, but they're not thinking of how it could work inside their organization. And like just because I may have a Gen AI workflow or Gen AI platform there that lets me write nicer emails or lets me, you know, interrogate things better or maybe write documents faster, no one's thinking about, well, should you not be able to free your mind up to talk to the customer about a problem? And then the AI in the background should be if the person says, Okay, I will fix that for you now, and they can then use AI to cleverly fix things, whether it's fixing a account or setting in place, you know, sending a service engineer out to fix your boiler in your house or whatever the poor purpose of the business is, that ultimately businesses might be going around AI the wrong way. It's like literally you've put this amazing a bit a bit like giving a um Fiat 500 a Ferrari engine. You know, you put that on top of the car, but you it doesn't mean the Fiat 500 is going to go any faster.

SPEAKER_01 13:03

Yeah, I mean it's funny. I I spoke to uh a very senior executive in in in a large Irish multinational last week, and he he he k he said um that the only person who's benefited from some of their rollouts of AI has been the dog because they get walked more often. Um he said that's not a core, that's not going to benefit the the guts of our company, right, in terms of driving efficiency. And I think the mistake that people are making is that they're bolting AI onto these existing applications, and and companies have grown up in silos. So the finance system got their the finance department got their finance system, SAP or whatever. The HR department got their human capital management system, which is like a workday or something like that, and IT got IT and and and and and so they've grown up in silos, and now what people are doing is they're bolting AI on top of this this um hornet's nest or whatever you want to call it of of stuff that runs their business, but they're not actually allowing, they're not flipping the organization 90 degrees and allowing these workflows to go across. So that's that's the that's the the key point. And I think the other thing to consider is that we're ServiceNow today in the in across the globe, we run north of 80 billion workflows in large companies. So we are the the guardrails and of the rails and the rules of how these companies operate, right? So you can't just put AI agents on top of these complex workflows without some kind of governance. And it makes me go back to the the time, and I'm probably showing my age a bit here, is you know, all of the rogue traders back in the day, whether it was Nick Leeson or or I think it was John Rosnack back in AIB, like these people made mistakes and they did things they shouldn't have done. But at least the banks were able to find out who did it, what the damage was, and then they were able to deal with it. And their processes and their procedures and their internal risk management mechanisms improved with that. You think about these autonomous AI agents that are able to do things now, unless they're within some kind of a control tower and they have guardrails around them to only do what they're allowed to do, you know, they won't scale within the enterprise because it's too risky. It's too risky. They could go rogue. How do we stop them doing what we're doing? How do we audit what they're doing? How do we roll back? What's where's the kill switch? So the answer is embedding AI within the existing workflows that run these businesses and finding the the parts of these workflows that are highly inefficient currently, or that have people doing pretty boring mundane work that they probably hate doing anyway. And we elevate our workforce and we allow the AI agents to do the stuff that that that um that can be done by them in a in a in a secure, auditable, and and risk-free manner.

SPEAKER_00 16:07

I I sometimes liken it to giving uh someone a gun with loads of ammunition without training them how to use the gun because the the situation is like a lot of people already have access to these gen AI agents. Like we were hearing stories of people forming relationships almost with some of them, uh asking the DAI personal questions, you know, almost letting the D AI tell them how to live their lives. You know, it's it's becoming conversational. There's amazing technologies. Uh you know, I'm a big fan of all of them, to be honest. I've tried them all and most of them out and they're great. But the thing is, um you know, you can give people all these tools, uh, but a lot of companies aren't formalizing how to use them right. They're just saying it's either you might wake up someday and you've got either ChatGPT or Microsoft Copilot sitting there on your on your on your on your company system, um, or you may be using it on your own personal time and you're you know you've already started using ChatGPT or Claude or whatever. But the thing is, um you know, if people are just using these things and and they're being encouraged to use them and they're encouraged to learn them, fair, fair enough, but they're not being formalised into how a company should work, use them, how they should use them in their processes. If you have a situation or scenario, maybe but no one's been taught how to use it. And then the other one I've heard of lately is vibe coding, where people now are being encouraged to create nearly applications on the fly. So, into that chaos, you know, you've got people figuring out how to use it to their own personal advantage. Like me personally, I keep a big sticky note with a load of prompts that I keep add adding to all the time that I find clever ways to do things using what AI is available to me. Um, and that's just my way of doing it, but nobody told me how to do that. There's no formalization of that in my situation. Uh, and I under one, I only I just think out there at the moment you've given people lots of interesting and cool weapons to do things, but they don't really have a strategy or tactics or a rule book to follow.

SPEAKER_01 18:01

Don't get me wrong, I mean the opportunity here is enormous, and we're seeing we're seeing huge um efficiencies being driven by this technology within our customers and and and within our own company. So, for example, we've we've automated the 80% of our accounts payable queries that come in uh using AI. Um, you know, because you can read invoices, match them with whatever. So there's there's amazing use cases. Um, but the facts are that AI adoption has actually dropped 20% year on year. Because what people were finding, and this is the anecdotal evidence we're hearing, is that they were they were treating this as a technology looking for a use case or or a solution instead of the other way around. And I think what we're seeing is because we've been in the business of service, whether it's customer service, employee service, IT service, whatever, we've been in the business of service for over 20 years. We understand where the efficiencies are in terms of customer service. So if I can if I can help a customer service agent elevate themselves by taking away the um the problems of actually dealing with five or six different systems every time I need to um answer a query, um, or I don't necessarily need them to worry about where the data is. That the the workflows can get access to the data they need to fulfill these requests, that drives massive amounts of adoption and value from from these organizations. So that I think that's the key point. Um but as I as I said earlier, and I maybe make the point again, that unless you have the rails and the rules that that most organizations have today, um you you you you just need that. You need to embed these AI capabilities into your existing workflows and expand those workflows um and make it more efficient for people. And I think in Ireland we we don't exactly have um a huge um group of people who are looking for work either, right? We we we we we we more or less are at full employment, depending on what stat you look at. So if Ireland is going to grow as an economy and develop as an economy, especially with some of the threats that AI is, you know, to the some of the lower-level jobs, then we're gonna have to we're gonna have to embrace this and elevate ourselves to be able to use this technology so that it becomes more than just expensive advice, but that these AI workflows are actually doing something. So they are resolving incidents faster. They're resolving them in an automated way, and they're taking away that that toil from people, whether they're dealing with a customer service request or they need something at work. That's that's the key where the key value of this is going to be.

SPEAKER_00 21:00

We hope you are enjoying this podcast. Bank of Ireland is welcoming new customers every day, funding investments, working capital, and expansions across multiple sectors. To learn more, Google Bank of Ireland Business Banking. Bank of Ireland is licensed by the Central Bank of Ireland. Well, that's the thing. Like, I mean, we're not saying AI is bad. What we're simply saying is that maybe we're just going about it in the wrong way. And maybe you could look at it as a filter through which existing things are looked at. So your HR systems, your your accounts payable, whatever, that you're basically putting this new veneer on top of it, and just businesses need to make sure that that's interpreted correctly, not simply a case of just adding extra stress or extra uh things for people to have to deal with um and interpret in their own way.

SPEAKER_01 21:45

Yeah, that that's exactly it. Um so you know, the the the multitude of applications that people need to deal with, if we can make it easier and we can elevate people to do their jobs better, that's where we've got to be focused. And um Again, that once that gets embedded into the core processes of a company, then the the the efficiencies really, really multiply and accelerate.

SPEAKER_00 22:09

But one of the things you hear about in the narrative at the moment is uh how a lot of um particularly in Silicon Valley, a lot of companies laid off a lot of their developers and people like that, and then decided, oh well AI is going to make us so much more efficient, and then the story here now is a lot of these people are being hired back, um, like as if it's a dirty little secret in Silicon Valley because oh, actually we needed these people, or we've just learned that um we did rely on AI, but it was making more mistakes, and we actually needed humans in the loop to correct it and make sure things were done right, which is kind of a a way of looking at exactly what we're talking about here, in the sense that you know don't be too hasty here. You still need your people, you still need people with experience and insight and knowledge to make the correct decisions. Uh AI just maybe helps them to you know skate to that puck a bit faster and resolve situations faster, you know, reply to situations faster, deal with things faster, but still you need the people there to do it. Like throwing the baby out with the batwater is not exactly the answer, just because you can make it you think you can save a bit of money.

SPEAKER_01 23:15

Yeah, and I think um I mean somebody used an analogy last week I heard where this is like the horse learning how to drive the tractor. And so now the tractor needs to be steered, etc. etc. So there's and there's been tons of examples over history of of major shifts, you know, whether it was the invention of the printing press and eliminating the need to write a book on every book needed to be written on an individual tablet, or whether it was the invention of the spreadsheet, which everybody predicted that would put accountants out of business, but now there's three times more accountants in the world than there were back then. So I I think, and everybody from our our secondary school kids, primary school kids, our teachers, um you know, the young people coming out of university. I spoke to a managing partner in a law practice last week as well, who said, you know, we will hire probably a lower level of graduates next year than we did last year, but those graduates will be doing much higher value work on the deals that we're involved in much earlier in their career. Because the the research and the putting together of all of the information stuff, that will be done more and more by AI. But our graduates will be will be doing more elevated work earlier in their career, and that's a good thing because they'll be learning earlier, they'll be engaging in in more client work earlier, they'll be probably fee generating earlier. So that that will drive revenue, it will probably drive employee employee and customer satisfaction because they're doing more interesting work, frankly. Um, and and also will will allow these firms to scale. And who knows? You know, there will there will be more, the world will evolve and humans, humans will evolve with it.

SPEAKER_00 25:03

So would it be fair to say that like you know, a lot of the again, the narrative out there in many ways anticipates this white-collar bloodbath, but at the same time, what I'm getting from what you're saying is that, you know, if you move with the time and take on the skill, move the times and take on the skills, you know, that's all the difference between being a victim of this change or rolling with the changes and triumphing that do you think over overall this will settle down into a kind of a new normal, or are we just because it's it's it's like there's a lot of flux in this at the moment, or the way it's been presented, the way it's been discussed. Uh, you know, ultimately I'd like to think of people just doing their jobs to the best of their abilities and given the the abilities they really deserve to be really good at their jobs. Um if that is the case, then you know, maybe we're not seeing this bloodbat come along unless you don't keep up with the skills and you know keep up with the times.

SPEAKER_01 25:57

I think that's right. I mean, if if you look at stats, I mean there's all kinds of stats out there, but um there's one book I can't remember the name of it, but I'll send it to you afterwards. But um the research showed that only 11% of people in the world actually enjoy their job. So so um the the other one is that only f customer service agents only spend 43% of their time on customer issues. So they spend more time in and out of different systems trying to find information than they do on actually solving customer issues. So if we can increase the amount of time that customer service agents spend, and we're seeing it in some of our customers where they're getting up to 85-90% of the time of their time they're spending on customer um issues and solving real customer problems. Um and then at the same time, the organizations are dealing with more customer queries because they're automating more, that can only be a good thing. Um so that's that that's where we're focused. Um that's where what we're helping our customers do. And it's very much an evolution of what we've always been doing. So we we we wanted to make the world work better by taking away toil from people's lives, and we're now all about putting AI to work for people, and whether you're a customer service agent, an employee, a citizen interacting with government, as I said earlier, it's all about making AI work for people so that people can get on with their lives and and and hopefully enjoy their work lives better as well.

SPEAKER_00 27:29

What's the mood like among the CIOs and the tech leaders that you talk to from the point of view of um, you know, the research tells you one thing, um what the you know, individually when you're talking to people, like they're going about it, uh like I'm not asking you to tell me private conversations around that, but do you get the feeling that um some are going about it in different ways than others? Some are going about it the right way, some maybe going around it wrong way. Uh what's the general uh posture of tech leaders when you talk to them on an individual basis about how they view the deployment of this? Are they in line with the way you're thinking, or are they kind of more thinking of the low-hanging fruit?

SPEAKER_01 28:10

I think both. I think the first thing to say is that, and everybody knows this, it's extremely noisy out there at the moment. I mean, the market is very noisy. I mean, everybody has their own AI agents. So the the amount of information that's coming at these CIOs and and other C-suite executives in in these organizations is is is huge. And it's I'm I'm sure it's it's uh quite overwhelming at times. What we're hearing is that the the focus has to be on the outcomes. If we're not driving outcomes, well, if the there's no point even starting. It if there's no problem to solve, well, then there's no value in solving the problem. So we're we're very much focused and working with with our clients on what are the outcomes based on the data, and where can they where can the highest value outcomes be driven? And that's where you focus. There has been a lot of I think over the last two years of of let's throw AI at everything, let's bolt it onto everything. I think that's been proven to be the wrong strategy, and and that's why the adoption levels have dropped, because end users aren't seeing the value in that. Um, you know, draft me an email, uh, it's fine, right? But I think a lot of people are saying, well, you know, that email doesn't sound like me, and I'm probably spending more time editing the email than actually would have written it in the first place. So the the the the use cases are are really, really important. The other thing is that it's important to have an approach, a platform approach, left to right across the organization or east to west, whatever you want to call it, that embeds AI into my existing processes and doesn't just bolt it on as a nice to have, which doesn't really drive much value. And that that leads us on to the whole change management side of things. So, for example, in within ServiceNow, our CHRO, our chief HR officer, is also our um head of AI enablement. So we see AI and us becoming an AI first company and in terms of how we use the technology ourselves in our day jobs as being um fundamental to the human resource of the organization. It's not something else, it's not an operational thing or it's not a specifically a finance thing. It's actually a thing that every employee of ServiceNow needs to be using AI every day in their job, whether that's preparing for a customer meeting quicker, whether it's driving automation and efficiency to allow us to continue to grow and scale without necessarily having to hire as many people as we would have previously done, hiring people in different parts of the business instead. So that that that's the fundamental. It's it's to focus on the outcomes and not just technology for technology's sake.

SPEAKER_00 31:10

There's wisdom in that because your main problem in your business may be, for example, service delivery, for example, or something you're doing wrong. Um, but if you just go and throw a lot of technology on top of things, that's not the answer. But if you can use that technology to find out where you need to put your resources, so maybe you need to be hiring more people in service as opposed to you know doing what you've always done. But the uh the other side of it as well, I I get the feeling that a lot of CIOs and tech leaders and leaders generally, CEOs, are under pressure to seem innovative and be seen as AI leaders in their own right doing amazing things with this stuff. But uh from what I'm getting from what you're saying is that it's it's really a case of deploy it broadly and then put put your resources where you really need to be at the best of your game.

SPEAKER_01 32:03

Yeah, but I I th I think as well, it's it's if if we don't adopt this technology, it's it's you know, organizations that don't adopt it are going to be in trouble because they'll they're just out outthought by by organizations who do. So I think it's an important thing.

SPEAKER_00 32:17

It's really down to doing it in the right way, and not just doing it for the sake of it.

SPEAKER_01 32:22

Yeah. It's uh it goes back to the point I made a minute ago about value. Um but also I think, and you you mentioned vibe coding and and these different things earlier, but it's also about putting it in the hands of the people who understand the business best. So it's not an IT problem. It's it's it's it's it's a it's an opportunity for business reinvention in many respects. And um that opportunity for business reinvention is best placed in the hands of the people who understand the business best, but that then comes back to the point about the the rules and the rails of how it gets deployed within the existing business processes or as a way to um improve or augment or supplement those business processes so that the business uh remains secure but can scale and use this technology effectively to allow growth and to allow new product innovation, customer service. You know, we've we've seen with Knos, for example, customer satisfaction go from 80% up to nearly nearly 99 to 100% in terms of their MPS surveys. And that's because the agents are being empowered to serve customers better. Um, others like Ergo, Auxilia and others, it in the service world, driving that efficiency is really important because if you think about it, if I solve a problem for a customer and I'm able to capture that problem succinctly and maybe next time give the customer the ability to self-serve in a way that demonstrates empathy and not just doesn't just frustrate people, that that drives more deflection, it drives more automation, and it drives customer service. So, or customer satisfaction. So the ability to reduce cost and increase customer satisfaction at the same time, while also employing um increasing the satisfaction, job satisfaction of my employees, if you can get that trifecta together, that's magic. Yeah, and that's that's the real value of what AI can, some of these AI technologies can can um can enable.

SPEAKER_00 34:31

So by doing it right, instead of adding confusion, you're creating the ability to think clearly, serve customers clearly, bring the whole mind to a problem as opposed to someone sitting on a call going through loads of different AI agents just to get to talk to eventually to a human that maybe maybe you maybe it goes back to the origins of business. Maybe you can talk completely to a human who's completely empowered also to solve your problems. You know, like it's all there, and maybe the AI is doing the work in the background while the person has their whole mind on a problem.

SPEAKER_01 35:02

Yeah, and and the models, whether it's anthropic or open AI or or any any of them, the models are very good at advising. So if I if I like you just use loads of examples, but if I want to know something, I mean these models they're amazing. The information you're getting is amazing. But the next level and where we're focused is on the doing.

SPEAKER_00 35:24

Yeah.

SPEAKER_01 35:24

So don't just tell me what I can do, do it for me, and do it for me in a way that's really, really efficient, drives massive levels of customer satisfaction, and does it obviously in a secure way, which and and irrespective of if you think about a large organization, there isn't one be one model, right? There's going to be a multitude of these things, but the the the knowledge is a commodity right now. I mean, the models are getting better and better every day. The knowledge is the commodity, it's how we leverage that knowledge to actually do things. Um, and in large companies, the doing of those tasks is where the real real value is.

SPEAKER_00 36:06

Brilliant. With that, Paul Turley from ServiceNow, thank you so much for your time. And uh it's a different kind of conversation about AI. I mean, we we probably started off earlier on talking about the potential chaos, but if anything, it's the ultimate vision is to just have organizations operating in a peak efficiency by being completely clear on what they're about, as opposed to having having to uh swim through a lot of technology and more problems brought about by throwing more technology on top of more technology. It's actually just making things clear and simple, really, at the end of the day.

SPEAKER_01 36:41

Yeah, that's it. Focus on the outcomes, and and that's where the real value is. So, John, thanks for the time. Really enjoy the chat.

SPEAKER_00 36:49

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