Episode #325

Nick Malone, Chief Revenue Officer at XTM, explains what separates successful AI-native companies from organizations simply adopting new tools. He explores value-led AI, executive leadership, experimentation, data, and practical workflows that improve productivity. Nick shows why companies that connect AI to measurable outcomes while keeping humans at the core can turn incremental gains into meaningful competitive advantage.

“A company’s got to be willing to go into uncharted territories, to be willing to experiment. You must go and dig deep and experiment and understand in what ways you can use the AI capabilities today to improve operational performance, possibly remove cost, definitely expand on productivity.” – Nick Malone

AI-native transformation requires more than giving teams access to new technology. Nick explores how leaders can connect AI to measurable business outcomes, create a culture of experimentation, improve sales productivity, and build smarter workflows around trusted data. He also explains why executives must demonstrate AI fluency themselves and how practical, incremental improvements can compound into significant business value.

Follow Nick Malone on LinkedIn

Follow Steve MacDonald on LinkedIn

[Transcript]

[00:00:10] Steve MacDonald: Welcome, everyone, to the C-Suite Sales and Marketing Perspectives podcast. I’m Steve MacDonald, your host. And today we’ve got a really interesting guest, Nick Malone. And Nick, you’ve been a longtime sales executive. You’re Chief Revenue Officer today at XTM. You lead global operations. You’ve lived in the US, in Europe, and Asia.

[00:00:31] Steve MacDonald: You’ve overseen not only sales operations, but you’ve also seen and overseen a lot of different functions. Right now, you have the entire go-to-market strategy underneath you. You’ve got a great perspective on cultures, how you develop and foster teams, and how you operate globally in a B2B environment. And you’re at a company right now that is helping other businesses adopt an AI-native perspective and keep up with the pace we all know we need these days.

[00:01:02] Steve MacDonald: We’re going to be talking about how to become a successful AI-native company. What I love that I heard is you, and I share something: we have kids who are just for the first time going off to college right now, and as parents, we’re very, very proud of them. It makes us a little bit nervous at the same time.

[00:01:20] Steve MacDonald: But you also, throughout all of that, being a father and living internationally and everything, you’ve competed in triathlons. Triathlons that actually mount mountains, go up and down mountains as you’re competing in the triathlons. I have to give it to you, I’m not sure I would have that kind of stamina.

[00:01:39] Steve MacDonald: Mm. But here’s what I’d love to do. I’d love to give you an opportunity to expand a little bit more on your background before we get started, and talk about how to become a successful AI-native company.

[00:01:51] Nick Malone: Great. Well, Steve, yeah, thank you. A pleasure to be here. Looking forward to the conversation. I’m fortunate that across my career, which spans over 28, 29 years now, I’ve had the opportunity to live and work in different geographies.

[00:02:03] Nick Malone: Very much enjoyed, in my early 20s, living in the US. Fantastic experience there. Obviously, my home country is here in the UK, where I spent a lot of my career, and I’ve also had the privilege of living in other parts of the world that are less charted. My family and I had the opportunity to go work in Kazakhstan, in Central Asia.

[00:02:19] Nick Malone: So we spent five years, in fact, over there, which was a really interesting experience, very different cultural experience. I’ve had the opportunity to work for companies that are global of nature, and with that comes the opportunity to work in different cultures, learn different perspectives on the business.

[00:02:33] Nick Malone: And as you said, although most of my career has been on the commercial side of the business, I’ve also had the opportunity to work in different functions, sales, operations. I’ve run transformation programs for national companies, as well as driving the go-to-market agenda, as I am here at XTM at the moment, which, as you say, is an AI-native globalization platform.

[00:02:51] Nick Malone: So we effectively are a partner helping companies grow their business across international borders whilst looking after their brand and their tone of voice, and making sure that their customers have a fantastic experience.

[00:03:04] Steve MacDonald: I have to ask you just upfront: your definition, right? What is a successful AI-native company? We can kind of come up with our own ideas on that, but you’re helping companies do this globally every single day. What’s your definition of an AI-native company, and how does it become a successful AI-native company?

[00:03:24] Nick Malone: I guess first and foremost, a lot of it depends on a little bit of culture. A company’s got to be willing to go into uncharted territory, to experiment. I think at the moment, it’s being helped a lot by the media frenzy about AI. And what do I mean by that? A lot of the companies we work with around the world have boards giving mandates to executive leadership teams to invest in AI. They may not even be sure what the outcome will be.

[00:03:51] Nick Malone: They’re not overly specific, but they know there’s something there. First of all, it’s mandatory to dig deep, experiment, and understand how you can use AI capabilities today to improve operational performance, possibly reduce costs, and definitely expand productivity. That’s one of the areas that we’re helping our customers with.

[00:04:14] Nick Malone: In the globalization world, essentially, we help our customers take their content to new audiences around the world. Now, the traditional way, if you rewind a few decades, was that, you know, you have your content, let’s say it’s in English. A professional linguist would translate that into multiple languages.

[00:04:30] Nick Malone: They do it, making sure that they respect your brand, your tone; they do it accurately, and so on. Over time, technology has complemented that. Machine translation technology’s come on, which essentially did it, automated it, and did it quickly. Now we have AI coming to the fray as well, helping companies do more with the same and more with less.

[00:04:50] Nick Malone: XTM has been pioneering in this space for many, many years. We’re pioneering as the AI world has come, not only in deploying this technology to our customers, which is a huge cost saving and ability to drive performance and speed to market, but we’re also, of course, seeking to adopt AI technology internally so as that we, as a company, can also operate in our leanest form and be as most productive as we can.

[00:05:17] Steve MacDonald: I’ve talked to many, many executives that, yes, their board is asking them, CMOs, CROs, but their CEO’s asking them, “What’s your AI strategy?” They don’t have a particular outcome other than it’s going to help the business, but they know that there’s something there. There’s a competitive advantage, or we’re just going to be behind if we don’t. You’re having conversations with customers every single day, and those conversations, they expect an outcome.

[00:05:45] Steve MacDonald: They expect something that’s going to be achievable. And we’re all operating under the assumption that we’ve got to do it faster, and we’ve got to provide more value than ever. AI has set those expectations. How are you seeing AI impacting outcomes? Because I know you’re asked that question every single day, and it’s not just about, “Let’s become more efficient.”

[00:06:09] Steve MacDonald: A successful AI-native company is one that’s going to have better outcomes and better value for the clients. How do you translate that? How do you, when we’re not even in, our boards don’t even know what the outcomes they’re really looking for are, how are you bridging that chasm with your customers, your prospects?

[00:06:27] Nick Malone: Yeah. Well, well, quite frankly, it’s a value-led conversation. Our value proposition right now is so compelling. We just need to convey that to the customer. For the thousand customers that we already have on our books, our value proposition is: we’ve released an AI module that complements what you’ve already invested in.

[00:06:47] Nick Malone: It is likely to reduce your operating cost of linguistic services by 50 to 80%, and the time it takes to enjoy that saving is the time it takes you to switch it on. When you do the ROI calculations on that, it is phenomenally compelling.  The next element to it. Yeah, is to express to people the one, depending on the level of the organization you’re talking to, people can be a little bit nervous.

[00:07:14] Nick Malone: If you’re going to save us all of that money, does that bring any risk to my job or my team? Because what, what are we going to do, you know? And that’s a very valid question. For the C-suite, being able to take out such huge percentages of cost in a particular area of the business is extremely exciting, but people are always skeptical.

[00:07:31] Nick Malone: So what we find is people have an enthusiasm as long as you articulate the value, but they want to trust but verify. That’s great. Let’s do a trial. Let’s just check that what you’re telling me is going to deliver, as you say, the outcome we’re expecting, so we can lean in hard and run fast.

[00:07:49] Nick Malone: So I think the onus is on us at XTM; it’s to talk to the people that are familiar with our part of the business. For any company that’s providing an AI offering that is going to drive value, I think it has to be a value-led conversation. What is the outcome? Let me prove it to you.

[00:08:08] Steve MacDonald: That’s the part that can be difficult. But it sounds like you’ve got that kind of down to a science. I think that’s the first big takeaway here: an AI native company has to be successful. An AI-native company has to be tied to outcomes. In the end, that’s what it’s all about. So how do you break that down? You mentioned that a lot of your prospects and customers worry about what it will do to them and their teams.

[00:08:37] Steve MacDonald: We all worry about AI, you know, taking our jobs away and everything. I know you have to address that, but you also talked a lot in our last conversation about how do we hire for this environment? How do we hire in an AI native successful company, and how has that changed? So two questions. How do you allay the fears of, “You’re going to get rid of a big portion of my team or my job,” and how do you then internally hire and recommend, for all those that are going to be listening here, how to hire for an AI native company?

[00:09:13] Nick Malone: I think it’s the three traditional, three core pillars of the process, which is people, process, and technology, right? So on the people side of the equation, as we’re taking our offering to market, it’s about awareness, which is a combination of marketing and enabling our internal staff, who can then convey the message externally.

[00:09:30] Nick Malone: The product itself obviously has to be fit for purpose. It has to truly deliver on that promise. And then, of course, the performance. We need to be able to get those outcomes. When we talk about hiring, it’s a great question, of course. We’re all playing with AI in one way, shape, or, at least, we should all be playing with it in some way, shape, or form.

[00:09:46] Nick Malone: And the more we play with it, the more we start to experience how quickly and how informative it can be, and how sophisticated we can start with. So I’ll give you an example. We recently hired a new chief marketing officer, and so part of that interview process, of course, is we want to understand how you would utilize AI within XTM for the purposes of marketing, for doing function, working at a high level of productivity.

[00:10:16] Nick Malone: Part of that interview process was talking about the topic, asking perspectives, but it was also about, great, show us. Let’s do an experiment right now, live. Share your screen. Show us what you’ve been working on. Come up with a scenario. We really put people through the paces, and I think there’s, historically, I suppose one could imagine that the folks in the C-suite are leaders.

[00:10:37] Nick Malone: We need to know a little bit of stuff, but we don’t necessarily have to do it. Other folks a little bit down the organization actually do the work. I think that paradigm has shifted a little bit now. I think AI is something we need to lead by example on. Now, of course, there’s, there’s leading by example to a certain extent, and then there’s getting right down into the, the mechanics of complex AI workflows within a business.

[00:11:00] Nick Malone: But in my mind, the C-suite today should be using AI and be able to demonstrate that and lead by example within an organization. And that’s exactly what we put our candidates through during the interview process. And I can tell you now, one of them fared very well, and that outcome presented itself. And what we’ve seen since that lady joined our business is a huge amount of productivity, not only in terms of her leading by example, but by the fact she’s showing people the art of the possible, and the pace of change is, quite frankly, phenomenal.

[00:11:34] Nick Malone: I think there’s a really good test case there for us internally, is that when you bring people on board who’ve got that energy, who’ve got the learning-for-life attitude, who are willing to experiment, we don’t fail; it’s a learning moment. That kind of attitude is helping us to push the boundaries internally.

[00:11:50] Steve MacDonald: You know, it was interesting. I just had a conversation on Monday, so a couple of days ago, and this company had instituted a competition internally where all the different departments were vibe coding, and they used Lovable and all kinds of different tools to see what they could do on their own to accelerate the use of AI in their traditional workflows that they’re using today.

[00:12:21] Nick Malone: We invite people to come onto our all-hands and show: how are you using AI? Show us something cool. Get people excited. Demonstrate the art of the possible. Yeah. And it’s everywhere. It’s all functions, all levels, all departments. It’s fostering that creativity, the willingness to embrace innovation, push the boundaries within guardrails.

[00:12:42] Nick Malone: I should definitely add that. You don’t want people taking sensitive data, customer data, or financial data, and putting it out in ChatGPT, you know, in an unregulated environment. So, of course, we at XTR have agreements in place with our chosen providers where the data we’re putting in there isn’t then used beyond that.

[00:13:04] Nick Malone: Super important to maintain that regulation. Again, within the parameters of that guardrail, we really want to promote the experimentation. So yes, similar to the people you were speaking to at the other companies: promoting that experimentation, giving people the time, blocking an hour every day to learn and experiment. Pretty powerful use of time.

[00:13:24] Steve MacDonald: Today, and I know you oversee the go-to-market team, so I’d love to get your thoughts on this, but the thought is that every go-to-market team member, whether you’re in product or sales or marketing or customer success, is on AI every day doing their portion of the workflow.

[00:13:45] Steve MacDonald: If, as leaders, we’re not stimulating experimentation, if we’re not promoting it, we’re not rewarding it, then we’re shooting ourselves in the foot a bit because that’s what it takes. I guess the question is: is part of being a successful AI-native company that, from the C-suite down, we’re promoting and fostering an environment of experimentation with AI?

[00:14:15] Nick Malone: Yeah, I think so. Put the guardrails up. Here at XCM, we actually have our chief operating officer with an AI team, and his role right now is to enable us to move to agentic workflows. So not just working with individual tools and individual agents, but how do you string an entire workflow together, which engages multiple agents across a workflow that maybe touches different departments and strings it all together to get an outcome?

[00:14:41] Nick Malone: Whilst we’re promoting adoption and experimentation within the company, as I said, we can all geek out with ChatGPT and ask some questions. But when you get to building enterprise-grade multifunctional workflows that are touching multiple agents and so on and so forth, there’s a little bit more to it than the experimentation. That’s why our COO has taken it upon himself to build a team that works with all of those different departments to build those enterprise-grade workflows, leveraging all of the agentic capability we have in the business.

[00:15:15] Steve MacDonald: Do you have some examples? You’re obviously, as a company, doing quite a bit. It’s what you offer to your clients. You’re doing quite a bit internally. Just some examples of how AI has changed the way that you work every day that you wouldn’t mind sharing. No data or names or anything, but just some examples that we could understand.

[00:15:34] Nick Malone: Yeah. Well, well, as chief revenue officer, one of the places I spend my time is with customers. We might have an account executive who says, “Nick, we’d love you to come and meet customer ABC.” Normally, the old-fashioned way of doing that would be that they would prepare me a briefing document, and that briefing document, yeah, something they’d probably type out by hand. Who are we meeting? What’s the history?

[00:15:54] Nick Malone: How much do they spend with us? What do we think the opportunities are? What are their business drivers, et cetera, et cetera. Now, we have a Gemini Gem that prepares all of that; not for them, I prepare it for myself. So, an account executive may say, “Hey, Nick, I want you to meet this customer.” I don’t ask them to prepare a briefing for me.

[00:16:12] Nick Malone: I go to my own Gemini Gem, and I say, “Please prepare me to meet with customer ABC.” It prepares a document for me based on the template I described, and it pulls in all the information I need to get ready for that meeting. It uses customer support ticket data.

[00:16:30] Nick Malone: It gets the financial data. It gets the data from the CRM. There’s nothing I don’t need. And, of course, it also researches what that customer’s priorities are based on what’s available in the open web. That document, which is created by Gemini, in my case, for me, I haven’t had to ask the account executive any. They’ve wasted zero time briefing me at that point.

[00:16:53] Nick Malone: So now, when I do have my briefing, I’ve already had an AI brief, and then I’m just validating: is this correct? And is there anything else, as an account executive, you want me to focus on? Anything to be avoided, et cetera, et cetera. So again, just time-saving. That may have saved that account executive an hour. So small uses. Little, little things that can help.

[00:17:15] Steve MacDonald: You walk in more well-informed than, on average, you probably ever have, right? What an account executive can put together in an hour and what Gemini can put together for you to consume in a matter of minutes, which is a night-and-day difference. What are your recommendations?

[00:17:33] Steve MacDonald: You’re leading the go-to-market, ABM company, ABM go-to-market strategy. We’ve got C-suite leaders that are going to be consuming this podcast that are in an ABM go-to-market motion as well. So that’s one really incredible use case for CROs, right? Getting prepared for meetings with customers. What are some other big areas you’ve seen in marketing, customer success, product, or RevOps?

[00:18:03] Steve MacDonald: Is there an example of something you should be thinking about this, this is a huge time saver, a huge way that you can increase the quality of what you’re doing and the outcomes that you’re getting? That was a great example there.

[00:18:17] Nick Malone: I’ll give you another one. So, battle cards. Again, another old favorite of how we train and enable people. Battle cards, as you know, are supposed to be a quick way to go and remind yourself about how to compete against a particular competitor. Now, our competitive landscape is changing rapidly. The competitive angle, and how you combat that particular competitor, can vary not only by industry or market segment, but also by customer status.

[00:18:42] Nick Malone: So again, we used to have quite comprehensive battle cards that you would read as part of an enablement function. We now have a battle card Gem. So again, I type in which customer I’m going to see. It will prepare me against that competitor based on all of our battle cards, specifically personalized for that particular account in this moment.

[00:19:03] Nick Malone: It’s increasing the personalization with negligible time in a repeatable fashion that helps us be very specific about how we compete out in the marketplace. Another example. This is something we’re experimenting with, right? So don’t take it as a slam dunk, tried and tested, but it’ll give you a sense of the attitude that we have towards adopting AI internally.

[00:19:23] Nick Malone: One of the key metrics we have in sales, in all companies, is productivity. How much revenue will a salesperson generate, and how quickly after we employ them can they get to that ultimate productivity state? It might be enterprise business-to-business sales; it might be six months, nine months, or so.

[00:19:41] Nick Malone: So the quicker we’re able to get them up to speed, the more productive, the more valuable it is. But we’re in a pretty complex industry. There are a lot of technical questions as well as commercial questions. The way we’re experimenting at the moment, there’s a company we’re working with, a very small sort of startup company, and their offering allows you to, when you’re using technology like this. 

[00:20:04] Nick Malone: So we’re using Zoom today. When I’m presenting to you, as you ask questions to me, as you’re a customer asking me a question, it could be, what’s the return on investment, or do you have single sign-on, or whatever it is, the tool is actually listening to the conversation. At our end, it’s plugged into all of our knowledge, our knowledge bases of customer support, product, enablement, and CRM.

[00:20:25] Nick Malone: It’s plugged into all that. So as you ask a question, it will put a nudge on the screen of what it thinks is the answer. So as a salesperson, it is very difficult to have the answers to everything. Quite often you will hear a sales guy, “Oh, I’m not sure of the answer to that. Let me make a note, and I’ll come back to you with that tomorrow or next week.”

[00:20:45] Nick Malone: By having the in-call nudging, we have the opportunity to dramatically reduce the number of times that happens, and therefore get our salespeople up to speed more quickly. Now again, we’re in the early stages in this, but we’re quite happy to engage with startups that are innovative, that have what we intuitively think is a really compelling concept, and we’re willing to invest a little bit of time and effort to experiment with that.

[00:21:09] Nick Malone: I guess two takeaways from that are, again, we’re trying to live that innovation attitude. But the other important thing is, think about David and Goliath. You don’t need to be a huge, multinational, proven company to experiment or work with companies like us. We’re looking for innovation that we think can move the needle.

[00:21:25] Nick Malone: We’re willing to work with small as well as large players to do that.

[00:21:29] Steve MacDonald: So one of the things that you said there that I think is really important, that isn’t something just to gloss over, is you said that’s connected to all of our databases. So Gemini itself, Claude, ChatGPT, the next model that comes out, is, in some respects, a commodity because we all have it.

[00:21:51] Steve MacDonald: We all have the same models. What becomes the differentiator is the data, the information that you give it so that it knows you and it knows your clients and what stage they’re in, the prospects and everything. I just didn’t want to gloss over this, but in your mind, how important is it to have the right data to connect to these tools, to a Gemini?

[00:22:15] Nick Malone: The more data you have connected in, the richer your output. But again, we’ve all heard that artificial intelligence can hallucinate. You’ll even see it in the footnotes of whichever provider you have. There is a bit of that caution; do check the data. And I think that’s very prudent. It’s a way to get information quickly and make informed decisions.

[00:22:34] Nick Malone: I’ll give an example. When we’re selling our AI technology to our companies, they’re translating text or content from one language to another. We can score the quality of what an AI system will do that. If you’re working in a highly regulated healthcare industry where, by law, you need a human to check that data, then there’s a different proposition than if you’re dealing with less risky content.

[00:22:58] Nick Malone: So we’re able to score the quality of an AI-translated piece of content to then give the client the option of how they want to manage it. Like, which workflow do we put it on? Can it go straight into production because it’s not high-risk and it’s low-risk content; we want zero cost or negligible cost attached?

[00:23:17] Nick Malone: Or, at the opposite end of the extreme, do we want to make sure that we’ve had a human review every single word in this document and rubber-stamp that, yes, this is perfect and fit for market? There’s a number of workflows that flow in between that, but essentially our technology allows a customer to get that optionality, all operating behind the scenes, and ultimately gives them the most optimal route to market.

[00:23:40] Nick Malone: So using AI, but being cognizant of the fact that there is a quality measure, you do need to check this stuff before you sort of blindly put trust in the bucket.

[00:23:52] Steve MacDonald: We’ve covered so much, and I would love to go on like another hour, but there’s one last question I wanted to ask, and it’s the most important because we can’t remember everything.

[00:24:03] Steve MacDonald: We’re poor human brains. We can retain about two or three things at the same time in a conversation. What’s the one thing that you want your C-suite peer executives in other B2B companies to take away from our conversation? If there was one thing for them to take away, what would that one thing be?

[00:24:22] Nick Malone: If I reflect back on nearly 30 years of sales leadership, the one consistent competitor, the competitor that was there the most, irrespective of the country, irrespective of the company I was working for, the number one competitor was do nothing. Right now, we have a generic mandate that’s coming from boards to executives to do something.

[00:24:47] Nick Malone: As we said at the beginning of the conversation, you’ve got to look at AI. Don’t miss the boat. Find out how it’s going to add value and experiment. So for me, my take is that there’s never been a better opportunity for people working in companies that provide AI technology to their customers.

[00:25:04] Nick Malone: There’s never been a better time to take that message to those organizations. As long as you can, as long as you’ve got a product that you can demonstrate firstly, the value, secondly, the ability to deliver on the promise, and you can switch it on, I think there’s never been a better time to overcome do nothing because they’re mandated to do something.

[00:25:23] Steve MacDonald: I love that. I love that. You made this so simple, right? Don’t do nothing. You’ve done so much more than nothing. You’ve embraced it. You’re incentivizing it at all levels. You’re requiring it. The hiring of your new CMO was a great example of that- of a requirement- but just a cultural move inside of the organization to adopt AI and experiment with it.

[00:25:46] Steve MacDonald: That’s my biggest takeaway, that you’re doing so much more than doing nothing. You’re embedding it culturally within your company. And I think that’s a really important takeaway. The mission here of this podcast is to get different perspectives from different C-level executives from all over the world. And if we do that and bring it all together, all of our experiences and our insights, that’s the rising tide that lifts all boats.

[00:26:09] Steve MacDonald: You’ve been a great motivation today that we can’t do nothing. We’ve got to do way more than that. We’ve got to really embed AI culturally into our own organizations. I just wanted to say thank you for coming on and sharing that perspective.

[00:26:23] Nick Malone: Yeah. Pleasure, Steve. Great to be here. I think, you know, there was an English or British cycling team back in the day who really were not performing very well, and ultimately, they had a new coach come in.

[00:26:34] Nick Malone: He started focusing on what he called marginal gains, the little things that you can do to ultimately move the needle. So whilst the topic of AI is huge, and it might seem like the big silver bullet, I think there’s, it’s all the little use cases, the marginal gains that, when you bring it all together and you have it managed like you would an orchestra, you’re going to generate a beautiful production of music and hopefully an efficient and an enjoyable workplace to work in. That puts humans at the core rather than humans in a loop.