Speaker 1Welcome to APAC's B2B Growth Podcast by X-Growth. I'm Shane Hoda, and on this show, we're going to be unpacking trends, busting myths, and delivering insights you can put to work today to drive growth in APAC. By 2030, Gartner predicts AI will create more jobs than it destroys, but the next four years, by their own admission, are going to be painful first. On today's episode, we're speaking to Neil Woolrich, Director of HR Advisory at Gartner. Neil has spent years advising organizations on culture, org design, and change management, and he brings real examples from companies like Lloyd Bank, ServiceNow, and Red Hat on how they're governing AI well. We talk through the pyramid to diamond debate, the tug-of-war between IT and HR for ownership of AI, and practical advice for any leader and especially marketing leaders trying to turn AI into results rather than just noise. Let's dive in. Neil, thank you so much for coming on the podcast. - My pleasure, Shane. - I'm really excited to talk about this, and there is a huge shift on org structure and how people are working in companies. Really love to touch on the traditional org structure and what it's been like for many, many years and many, many decades, which we had talked about, and you kind of described as the pyramid model, right? For someone who doesn't have context about that, can you just a little bit talk about the model that has been in place for the longest time? -
Speaker 2Yeah, well, what we mean by the pyramid structure is we have a lot of people at the base of the pyramid doing those lower-level, entry-level jobs, large numbers of people there at the bottom of the pyramid. Then your middle level of the pyramid, you have a smaller number of mid-level managers, managers managing teams of people. And then at the top, you have your senior leaders, your senior executives, and your CEO. And as you say, Shaheen, that's the model that sort of served us well for many, many years. But now artificial intelligence is sort of upending that model, and the people sort of most affected are those at the bottom of the pyramid, the entry-level roles, the less complex, the more procedural kinds of roles that we see in most organizations, but especially large organizations. They're the ones, the ones at the bottom of the pyramid, that, you know, seem to be most affected by artificial intelligence today. -
Speaker 1I mean, one of the, there's obviously a way that the effectiveness of that was there, right? And I was listening to somebody, and someone described it as, it was, it's based off of Roman legionaries. I hope I pronounced that right. And the structure was kind of the same back then, and org structure, kind of until now, has been very similar to the Romans and how they organized their army. First of all, what is changing? So what is happening now, and what are you seeing? Because you are, you know, you do a lot of consulting for different organizations on their, you know, human resources and all that stuff. What is changing in the market now? -
Speaker 2Well, of course, artificial intelligence, that's the thing that's sort of on the top of everyone's mind at the moment. That's probably one of the big drivers in changing the way we think about our organization design. And we're seeing a big shift in terms of what organizations are expecting from employees, a big shift from, you know, the way we think about our organization design. And I think that's a big part of the reason why we're doing this. right. And a lot of organizations are still at the early stages of adopting AI. We see a lot of hype out there around AI. A lot of the hype, I must say, comes from vendors themselves, people trying to sell an AI solution. But a lot of organizations need to get that sort of framework in place to think about what are the ripple effects or what are the unintended consequences of artificial intelligence? I already mentioned things like entry-level roles drying up and those things or what happens when the technology fails. So a lot of organizations are just starting to invest in AI governance, AI ethics. When can we use it? How much information can we collect from our customers or from our employees? When do we need to communicate that? And also change management as well. This will be a big change management issue for many years to come. How do we guide our workforces through that change management exercise? And also our customers, external stakeholders. How do we manage? And communicate the change with them as well, because they want to know as well that our organizations are using AI ethically, effectively, and in a way that serves their
Speaker 1best interests. Do you think we're going to be going from the pyramid model to the diamond model back to the pyramid model?
Speaker 2I'm not sure on that one. I'm skeptical about the diamond model. And when you say the diamond model, we mean this model where there's very few entry-level roles. So instead of having a big base at the bottom of the pyramid, if we're going to have a big base at the bottom of the pyramid, we're going to have a big base at the bottom of the diamond with very few entry-level roles. We're having a big internal debate about that ourselves at Gartner. So the jury is still out as to whether we will see the pyramid or the diamond or something in between. I suspect most likely probably something in between. We'll see fewer entry-level roles than what we saw in the past, but it won't whittle down to nothing or next to nothing. I suspect the base of the pyramid will be sort of smaller than what it was in the past, but not nothing.
Speaker 1Interesting. Okay. Because it's, and we talked about this as well. There was a report coming out from Ramp, which they talked about, they did the analysis of like hiring trends and inside of the organization, what is happening, where they saw companies that were adopting AI had kind of the same rate of hiring junior team members as kind of what it was in pre-AI. And I found that really, really fascinating. Any thoughts on that? I mean, that sounds like it aligns quite nicely with Gartner's view as well.
Speaker 2Aligns reasonably well. You know, we didn't go into as much detail at looking at what was the impact on those entry-level roles. We more looked at the overall impact on the workforce. And again, AI being a net job creator, but, you know, having looked at that Ramp report at a high level, you know, it sort of ties in with the Gartner thesis as well. And, you know, it seems plausible to me. Certainly from the conversations that I'm having with human resources leaders. And as I said before, organizations are not getting the value that they want from artificial intelligence. So they need to have that human AI infused workforce. There's still going to be a role for those entry-level people in organizations.
Speaker 1I do want to touch on companies not getting the ROI that they want from AI. And what is the conversations that you're hearing coming out of boardrooms and the C-level? Love to hear if there is anything specific that you think it's worth sharing.
Speaker 2Well, I think probably the two main things that are affecting organizations' ability to get that return on investment from AI, a prioritization and intentionality in the way they change work. I have a simple framework that I like to talk to organizations about in terms of prioritizing. What you want to do is match where you've got really high maturity in the AI technology solutions with poor performance in your internal processes. So if you're in a situation where you're in a situation where you're in a you know, a good example in the human resources sphere is candidate selection. So, you know, hiring new people, finding candidates. There are lots of really good AI solutions out there to help you find candidates, whittle it down to a short list, and then you get a human involved to select the candidate who gets the job. Marry that up. If your organization is poor on candidate selection, marry that up with your poor performance in your process. So that's one element in terms of technology with a bad process that you have internally. But the second is being, as I mentioned, being very intentional about the way you embed it in work. You know, find those frustrations in your processes and find those pain points that people have, what we call work friction, those organizational barriers that get in the way of them being effective in their day-to-day work. And again, you need to be really intentional about that. Some organizations that I've seen get an AI governance council or an AI workforce council, that kind of idea, to have broad oversight, but then they get smaller groups, pods, scrums, working groups, whatever you want to call it, to sort of really figure out, well, where are those frustrations and frictions in our day-to-day work that we can apply AI to provide a solution? So they're the two things I think I've seen organizations do well, that prioritization and then being very intentional about the way we change our workflows.
Speaker 1Do you think AI is going to become another department like IT, or do you think it's going to become infused inside of the organization? I don't know if you have any thoughts on that.
Speaker 2Yeah, it's interesting because, you know, there's a tug of war going on in a lot of organizations that I see. And the tug of war is primarily between the IT function and the human resources function. Both want ownership over artificial intelligence. And, you know, human resources leaders traditionally have not had a great reputation in terms of technology. And so any technology solution tends to sit with the IT function. But we've got to remember that artificial intelligence is not a technology solution. It's a technology solution. It's a human experience as well. And so that's why a lot of human resources leaders are saying that, you know, we should at least have a seat at the table, if not own AI strategy. You know, interestingly, Moderna, the pharmaceutical maker, they merged their IT and their HR function recently, you know, recognizing that, yeah, yeah, recognizing that IT is a human experience as well.
Speaker 1Fascinating. Fascinating. What about, there is a lot of talk, about the organizational chart. And yes, it's shrinking and less people are going to be in the organization. But there's also a conversation about now we're going to have agents as part of the org chart. Talk to me about that.
Speaker 2Yeah, that's an interesting one. And, you know, I have started talking with some organizations that are either doing that or considering it, you know, putting your organization chart down with humans and AI agents as well. It's a really interesting change management issue for a lot of organizations. You know, one, should we do it? How do we communicate it to people? And how do we help our people sort of navigate through that change? But then secondly, the governance around it. You know, what responsibilities does the AI agent have? Who pulls the AI agent into line if it strays beyond its boundaries? And who owns the outputs of the AI agent as well? Is it, you know, the human on the org chart who sits right next to them? Or is it their manager or leader somewhere above them in the organization? It was still in the very early days of doing this. But I think the two key things that organizations really need to manage is that change management part of it. And then ownership of outcomes. Because one of the things that we see employees really struggle with is role and goal clarity. And if they're not sure whether they own the outcome or the agent sitting beside them on the org chart does, then, you know, it's a recipe for disaster in organizations.
Speaker 1Maybe they should ask the agent. Have you seen anyone doing this really well?
Speaker 2Yeah, a few companies, you know, we, we've profiled organizations around the world who've done some, you know, made some good steps in artificial intelligence. Lloyds Bank in the UK, they're one who've really got on the front foot in terms of governance and got ahead of that early. They have what they call a controlled power approach to governance. They've done that really well in terms of oversight of artificial intelligence. And their approach at Lloyds Bank was that, you know, there are hundreds, maybe thousands of things that we could apply artificial intelligence to. How do we narrow it down to that small number, say a dozen of really high priorities for the organization? So they've taken that controlled power approach. Another organization that we profiled was Service Now, which provides HR technology. They do that sort of two-tiered approach of AI council that has sort of overall governance and oversight with pods underneath them to decide the use cases for artificial intelligence. And then the third one is Red Hat, an open source technology company in the US. And they've done a really good job of doing that. And they have been looking at their organizational pyramid in a slightly different way to what we've been talking about in Shaheen. But they look at the pyramid in terms of who are those big people or the big group of people at the base of the pyramid who are sort of mildly affected by AI and what's the sort of low-level support that we need to give them to get through. Then at the middle of the pyramid, people who are sort of mid-level affected by AI in their workflows. And then at the top of the pyramid, who are those people who are most acutely affected by AI? Those people whose roles either might be made redundant or they really need to be significantly reskilled or upskilled to manage the introduction of AI. Red Hat has sort of had that three-tier approach depending on the degree of impact on people's roles with AI. So contextualizing their support for those three different levels in the organization based on how acutely affected people are by AI in their roles.
Speaker 1Interesting. So if I kind of summarize Lloyd Bank, there is one kind of decision-making unit. You call it the control tower. And we basically make the calls and where are we going to focus on service now and creating this like center of excellence and then pods and on that one so are the pods for example like in each department so it's like hey marketing will have a pod that is going to be doing marketing stuff and char is going to have a pause hr stuff and is that is that the model or that was
Speaker 2their model but you can do it other ways as well you know you could have sort of cross-functional pods to really sort of get that cross-functional view and and bring in some expertise so you know you might have say a human resources pod to look at artificial intelligence in the human resources function but they might call in experts from somewhere else you know legal for example what are the legal and ethical constraints that we in the human resources team need to think about or finance what are our budgetary constraints and it of course you know where does it see the big opportunities so you could do it either way and i think you know the cross-functional approach probably gets better outcomes in terms of getting that wider enterprise view
Speaker 1interesting and with red hats model across the across the three tiers that you mentioned the way i would summarize and you tell me if i got this right is you have it across any of the tiers you look at the impact that ai is having and then what you need to do for for that kind of body of of people and whether it's at the very top or in the middle or at the bottom right is like what what what is the tiers for that well well
Speaker 2the tiers are for the the degree of ai impact on the roles so the base of that pyramid is it's not
Speaker 1necessarily the hierarchy inside of the
Speaker 2organization exactly yeah yeah okay so it's a different different pyramid context to what we were talking about earlier at the bottom of the pyramid there's a large group of people who might be mildly impacted by ai so they just need a low level of support and in the middle you've got people who are a bit more affected by ai they get a bit more support and then at the top that small group of people who are really profoundly affected by ai in their roles and you know red hat some done some interesting things like for that group who are really profoundly affected if we can't upskill them where is the next logical step for them outside of the company so thinking about you know external labor market support for those people which sounds counter intuitive you know most organizations don't think about well how do we exit somebody you know to another job somewhere else but if you've exhausted all other opportunities and there's no way to upskill somebody the next best thing you can do for them is support them to consider external
Speaker 1opportunities yeah of course of course i'm trying to think red hat is owned by ibm are they are they an ibm house obviously ibm had a very devastating news as the recording of this i think was just a couple of days ago where their stock massively dropped it's funny to see that and a lot of that was i think their ceo was talking about we missed the ai train and we were not fast enough and then you have red hat underneath ibm who's kind of creating these models and really pushing the frontiers on incorporating a fascinating to see the difference between those
Speaker 2two yeah but but it's interesting as well you know and i won't name names here because it's oh yes please do i've talked to some human resources leaders who've done tours of silicon valley and talked to the hr teams in those organizations and even the hr teams in those ai leaders in silicon valley don't feel as though they've made a lot of progress you know they've made a lot of progress you know they've it's a challenge for a lot of organizations even the tech leaders i had
Speaker 1one question that i wanted to ask you and i don't think it's relevant anymore and my question was around where do you think the middle management is going to come from but if we are not going down that diamond shape org structure it almost sounds like we're going to be fine we're going to be fine for middle management and and the people who are going to populate that that bottom tier are going to move up to to middle management and it should potentially be okay it
Speaker 2could be but you know it will depend on the organizations and and the kinds of roles that they have i'll give you a couple of examples at different extremes of the spectrum one is say somebody working in a call center a very sort of process oriented job with in most cases not a lot of complexity not a lot of judgment required that's the kind of role that can you know really be complemented quickly by ai and people who move into those jobs complemented by ai can move up into middle management pretty quickly so that's the kind of role or out of the company yeah yeah yeah but you know at the other other end of the spectrum people like lawyers that's where it's you know you need a lot more experience to use artificial intelligence you know an entry-level lawyer somebody straight out of university can't just rely on artificial intelligence to upskill themselves because you know you need to know the case law you need to know the way the courts operate and those sorts of things you need to be able to detect hallucinations you know there's been so many cases of people relying on ai in the courts and it's just made up case references so that's where somebody with low experience in in a legal job can't really rely on ai you need a lot of that experience so it will depend on the organization and the complexity so some organizations will continue with sort of the traditional pyramid structure others may be able to get away with the diamond structure and the challenge for them yeah how do we train up those middle level of managers how do we get them to experience quickly and you know quite often it's probably going to be more about the experience of the organization and the complexity of the internal training rather than being able to rely on the education system or the universities to you know churn out people who are ready for those entry-level jobs because they won't have those entry-level jobs anymore those companies will probably have to figure out their own training approaches to get that next generation of middle
Speaker 1managers projection is by 2030 ai is a net job creator what is gartner's position for the next four years what what what do you think the next four years is going to be like more layoffs keen to hear what that journey potentially going to look like by by 2030 well we've kind of
Speaker 2charted it on a graph and you know 2030 is the year the two lines intersect so you know one line is ai eliminating jobs and the other line is ai creating jobs and by 2030 that line of ai creating jobs will move ahead of ai eliminating jobs so for the next four years yes you know likely to be painful in the labor market but you know regardless of whether we're gain jobs or lose jobs there's a real disruption happening right now in the workforce and so the human resources leaders that i talk to their focus is on well how do we manage people through that disruption you may not have lost your job but the responsibilities that you have and the work that you perform may have changed profoundly and you know that might be disengaging for you as a as a human you might be working on things that you don't really enjoy you might be working on things that you didn't think you signed up for so you know the role of organizations and in particular the human resources leaders that i work with is how do we manage people through that difficult disruption that is happening in jobs even if people aren't losing jobs there's a real um reallocation of work that's
Speaker 1happening and it's real now what are you saying in terms of difference between let's say companies in the u.s and the uk and australian companies in terms of adoption in terms of everything that we've talked about have you seen a difference are we behind is it again that's another thing i'm really keen to hear your thoughts on if you've seen any patterns or or differences between the two yeah this
Speaker 2is probably a generalization and just you know based on my anecdotal observations rather than any data but um you know as a general observation u.s seems to be leading the world australia behind and uk probably around the same level of adoption as us and but that's sort of historically been the the case australia has typically been a slower adopter of technology compared to the rest of the world especially in the field that i work in in terms of hr technology so yes we we are a bit behind but there's you know there's a lot of fear of missing out out there but i don't think it's justified you know as i mentioned before some of those tech giants in silicon valley are not as advanced as as we might think they are so i think the important thing for organizations here in australia to get right is get your governance right and be very clear on what is your ai ambition what is your desired return from ai versus what is your risk appetite be very clear on that before you start launching into it headlong and be very clear on directing people to productive use yes we're a bit behind you know the the game is by no mean by no means over the last
Speaker 1question i want to ask you is is maybe a little bit more focus on sales and marketing if i'm a leader either a sales leader or a marketing leader in an organization that could be a couple hundred people or a couple thousand people what do you think i should be thinking about and focusing on in the next six or twelve months i think
Speaker 2really focus on you know what is your desired return from ai how can you use ai to deliver on your strategy because ai is not a strategy itself it's a it's a tool to deliver on your strategy and then what are the implications of that for your customers stakeholders shareholders employees and how do you manage them through that change get your governance in place from the start rather than just letting people play with ai because that's where the frustration is happening people just dabbling with ai and not really knowing where they should be using it and how they should be applying it if we get our governance right and direct people to the most productive use that will better our chances of really using ai as a tool to deliver on strategy is
Speaker 1there something from a governance perspective that you see that is really critical or certain elements in there that you're like these are some of the key pillars for for your ai governance and i know we're getting a little but maybe two, two, deep on the AI front, but if you have a view on what you've seen work inside of organizations.
Speaker 2Probably the number one question is who owns it? Who is ultimately responsible for AI inside the organization? And then AI delivering on your strategy and delivering outcomes to your clients, stakeholders, shareholders. So ownership of AI is probably the most important thing around governance. How do we get that clear level of ownership right? And then as AI goes through the organization, again, how do we clarify roles and responsibilities and ultimately lines of ownership? Because as we mentioned before, if you've got an AI agent sitting on your org chart next to a human, who's responsible for what and how do we manage the AI agent in the context of the organization to deliver on our strategy?
Speaker 1I keep saying my last question, but the questions keep coming up. Why do we are having a conversation about responsibilities, right? And what I mean by that is why are we not treating this as you are creating this agent or why is this not treated like any other tool that then the person who's kind of operating the tool becomes responsible for it, right? And why are we talking about, hey, it has its own rules and responsibilities versus, you know, you are the human in the loop and therefore you're, this is just another tool like your CRM or your, you know, or your Microsoft Word that you're using and therefore it's you. Why is, why is that there? There's a difference.
Speaker 2Because it's moving so quickly and it's doing so many things that, you know, even six months, a year ago, we couldn't anticipate that it would, would do. I was talking to a chief human resources officer recently who was saying she was using AI to help with her presentation to the CEO and board six months ago, a year ago, you would have thought that was unfathomable. Would have got laughed out of the room if you said to the CEO and the board, I used AI to help with this presentation. Now it's become an accepted way of working. So the boundaries are shifting all the time and people need guidance as to, well, what, what are the boundaries today? And again, that will depend on the organization's own culture, its own capability, its desired returns and its risk appetite for artificial intelligence. So we know artificial intelligence has its shortcomings. It will get things wrong. So what are the acceptable boundaries within organizations? And as artificial intelligence gets better and better, are we shifting our boundaries? And, and keeping pace with the development in the technology?
Speaker 1You know, I have some rapid fire questions for you. Okay, let's do this. But before I get to rapid fire questions, is there anything else that maybe I haven't asked that you think it's important for us to touch on?
Speaker 2Probably just a question around culture. Culture is one of those important things. It's always a top priority of CEOs and chief human resources officers. So what's the culture that we need to successfully embrace artificial intelligence in our organizations? And how do we change that? We shift that culture in a way that responds to changes in work. So, you know, traditionally, when we thought about organizational culture, we've tried to build a culture that will endure. But now with all of the changes in work, and especially artificial intelligence, we want our cultures to evolve rather than endure. So how do we build a culture that's right for artificial intelligence and one that will evolve as the technology changes, but also as our human expectations change as well in our organization?
Speaker 1What is your recommendation? My recommendation for organizations to communicate, hey, we're rolling out AI, but this is not to replace your job, or this is to kind of basically create efficiencies in the organization where people are like, oh, we're rolling out AI. Sometimes people might feel like they're going to be doing extra work because, oh, you're talking about efficiency. That means more output that probably then maybe people can't see the fact that that in AI enables them for more output. But the most immediate, the most immediate, the most immediate, the most immediate thing that people would see is I got to do more. It sounds like I got to do more work, or am I going to be here in six months time or in 12 months time? What do you see is kind of the best approach? And I feel like this is relevant not only for HR leaders, but also across the board of like, how do you communicate that as a head of a department to the rest of your team? But how do you communicate that from a head of an organization to the entirety of the organization? How have you seen that done really well?
Speaker 2Well, I think the organizations that do it well, are the ones that really have a strong focus on the human experience. So as you're going through change management, you can think of it as a process that you've got to go through. And the process is sending out the right information about what this means for the organization, why we're doing it, what does it mean for roles? So there's a process you've got to go through, but there's also a human experience. A lot of organizations get it wrong, just focus on the process and they don't focus on the human experience. So what are our people going to feel through this? What do we want them to think? What are the positive emotions that we want at the end of this process? So make sure you get that human experience right. And make sure that you factor in that there will be skeptics about this. There will be negative reactions. We've got some longstanding research that says in any major change initiative, 40% of your people will react to it negatively. So even if we roll out artificial intelligence with the best of intentions, and we think this will help make people's lives easier, you can expect a large chunk, your workforce to react to it negatively. So get ready for that, get on the front foot and think about why people might be reacting negatively. And the number one reason is certainty. Will I have a job in six months or will I be replaced by a bot? But it might affect people's feelings like their status within the organization. I used to be a subject matter expert and now we've got a bot that people can answer those questions much quicker and much better than I can. Think about those kinds of human reactions and how do we make sure we get the human experience right along with the change management process.
Speaker 1Is there a Neil bot going around in Gartner? There is not yet. Not yet. Coming, coming soon. All right, let's do some rapid fire questions. The first question I have is resources. What is a resource? It could be a book, a blog, a podcast, whatever it is that you either recently have come through, gone through, or you just can think of right now that has had a pretty profound impact on the way that you work or live.
Speaker 2I mean, just artificial intelligence generally. We've got our own artificial intelligence tool. I'm sure a lot of organizations have it or they've just rolled it out. But I was skeptical about artificial intelligence a couple of years ago, but it has got so much better so quickly. I use it several times a day now, helping me coalesce my thoughts. Or if there's a question that comes through that I don't know the answer to, it's a good starting point to check my thinking. So artificial intelligence itself, just generally, I'm using it in my work, use it in day-to-day life, like recipes, entertainment suggestions,
Speaker 1all of that sort of stuff. Fixing the kitchen sink in my case. But 100%, 100%. Okay. If you could give one advice to our audience or B2B kind of marketing and sales leaders, but if you could give one advice to them, what would that be?
Speaker 2Just be intentional. Be very intentional about everything that you do, whether it's artificial intelligence or anything else. Be intentional about what does this mean for our workflows and for our people and for our ability to deliver on strategy. And that's, you know, we keep coming back to this point. That's why we see organizations fail to get the return on investment from artificial intelligence that they want. It's intentionality and understanding really how work is getting done and how it should be getting done. And where is the opportunity to embed artificial intelligence in that?
Speaker 1Who are some of the people that you kind of follow and listen to and you really like what they're saying?
Speaker 2You know, out of left field, I don't know if you ever listened to Rick Beato, the music guy on YouTube. He's a guy in his 60s. He's a music academic, but he's also, you know, played in bands, been a producer, had sort of mid-level success in his music career, but he's got this YouTube channel and technology is a big part of it. And so he's discussed a lot about artificial intelligence and he's got some insights about what happened to the music industry 20, 30 years ago. You know, there used to be big studios where everyone had to go to, to record their music. Now people do it in studios. And his connection to today is that, well, that's what we're seeing with artificial intelligence. You know, there's all this investment in data centers, but people are just going to get, you know, download LLMs to their home computer, get storage at home and do it all at home. So he's opened my eyes about people talk about the AI bubble and is it going to burst? And why is it going to burst? He's somebody from left field, you know, who can translate his knowledge of the music industry and trends in what happened to the business to the current day in
Speaker 1intelligence. Love it. Love it. Last thing. What is something that excites you about future today?
Speaker 2I think just the opportunities with artificial intelligence to make our lives better. You know, I'm optimistic generally about most things. And I think, you know, I genuinely believe that artificial intelligence will get rid of those menial jobs, the jobs that nobody likes in our organizations and free us up for more strategic impact and to be more creative. On the flip side, there are huge risks with technology. And, you know, I sort of see this, you know, myself and with others sort of, you know, being consumed by the technology itself. And it takes away the human connection in our lives. So, you know, get out and touch the grass, as they say. I have to remind myself to do that. But I think it's having that balance between sort of technology and all the other interests that we have outside of work and the things that we use technology for.
Speaker 1Neil, this has been an awesome conversation. I just want to say thank you so much for coming on the podcast. I learned a lot, today. So thank you. My pleasure. Thanks for having me. We hope you enjoyed this episode. If you like APAC's B2B Growth Podcast, please share it with your B2B friends and subscribe. For weekly insights on B2B growth across APAC, sign up for the XG Weekly newsletter. Link is in the description. APAC's B2B Growth Podcast is produced and edited by Alexander Hipwell, and music is by the mysterious Breakmaster Cylinder. We'll see you next time.
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