The Evolving Leader

'Leading in the Age of AI’ with Andy MacMillan

• Andy MacMillan • Season 8 • Episode 9

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In this episode of The Evolving Leader, Jean and Scott sit down with Andy MacMillan, CEO of Alteryx, to explore how generative AI is reshaping work, leadership and organisational design. Andy shares a uniquely practical and grounded view of where companies really are with AI adoption, caught in a chaotic but exciting period where the opportunity is clear, but the scaffolding is not yet in place. He explains why AI transformation cannot be delegated to IT, how leaders should approach reimagining business processes, and why Theory of Constraints is one of the most powerful lenses for navigating the next wave of change.

Andy also opens up about the leadership challenges ahead: maintaining psychological safety in the midst of rapid technological shift, helping teams build confidence with new tools, and avoiding both complacency and panic. He shares candid lessons from his own leadership journey, the importance of transparency when organisations face change, and why the most impactful AI practices often happen at the “strategic altitude” rather than in day-to-day automation. 


Further reading re. Andy MacMillan and Alteryx:

·      How AI adoption is driving a new data era at Alteryx — An interview with Andy MacMillan discussing his role as CEO (appointed December 2024), Alteryx’s repositioning as an “AI Data Clearinghouse”, and his thoughts on shifting from siloed business-data systems to unified analytics.

·      Alteryx Looks To Become An AI Data Powerhouse With New Unified Platform (CRN, May 2025) — MacMillan discusses the launch of the “Alteryx One” platform, a strategic move to unify analytics, data-prep and AI workflows under one roof.

·      With agentic AI we are being sold on the idea of running before we can walk or crawl, says Alteryx’s Andy MacMillan (Tech Monitor, May 2025) — A leadership-focused piece where MacMillan emphasises the importance of starting with manageable AI projects, surfacing his mindset around experimentation, governance and human-machine synergy.


Other reading from Jean Gomes and Scott Allender:

Leading In A Non-Linear World (J Gomes, 2023)

The Enneagram of Emotional Intelligence (S Allender, 2023)


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The Evolving Leader is researched, written and presented by Jean Gomes and Scott Allender with production by Phil Kerby. It is an Outside production.

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After more than 5 years of hosting The Evolving Leader, Jean Gomes and Scott Allender are launching their new show The Mindset Economy in January 2026. The new show will explore how to live better, work smarter and be connected in a more uncertain world where machines can think. 

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Jean Gomes:

What does a workplace look like when AI becomes truly pervasive as we grow more comfortable using these tools for far more than an enhanced search engine, many of us are beginning to see their potential to unlock more meaningful work, spark creativity and amplify our impact. Yes, automation will take over routine tasks, but that doesn't necessarily mean a dystopian future. Instead, it's a call to proactively imagine and design a better, more human centred world of work. In this episode, we speak with Andy McMillan, CEO of AI services company altrex, about how to think in this forward looking way and how he's reshaping his own organisation to make it real. Join us one last time for an essential conversation on the evolving leader.

Scott Allender:

Hi friends. Welcome to the evolving leader. The show born from the belief that we need deeper, more accountable and more human leadership to confront the world's biggest challenges. I'm Scott Allender

Jean Gomes:

and I'm Jean Gomes.

Scott Allender:

How are you feeling? Mr. Gomes,

Jean Gomes:

I'm feeling excited about the end of the year. That's what I'm feeling. I'm feeling it's been a really full, full on year, with so much happening, so much happening in the space that our guest is going to bring into this. And I've been really immersed in immersing myself, trying to keep, you know, some somewhat, you know, wouldn't say ahead, but somewhat in the game on this, and really excited about next year as well. So I'm feeling more positive probably since we started the evolving leader, the level of kind of clarity about where we're going is great. And so yeah, I'm feeling I'm feeling great. How about you? How are you feeling?

Scott Allender:

I'm feeling a mix of things today. I'm feeling grateful that I've got some rest coming up here in about another month, looking forward to some downtime, already feeling really energised about the next year, though, lots of good things on the docket for the start of the year, so I'm feeling really optimistic and excited about that stuff and and feeling a mix of things about our show here. As you know, we've been doing evolving leader for five years now, and it's been incredibly enriching and successful, and now we're getting ready to pivot and launch our new show, the mindset economy, in January 2026 so lots to be excited about, lots to be grateful for, and I'm really grateful for our guests joining us today, because it's a great conversation to land things with on the evolving leader today, we're joined by Andy McMillan and is a seasoned tech leader who has recently taken on the CEO position of Alteryx, an AI platform for enterprise analytics used by 8000 corporate customers globally. Last year, Alteryx became a private company following a $4.4 billion deal that resulted in its delisting from the New York Stock Exchange. So we have lots of questions for Andy, and we're going to jump right in. But first things first, Andy, welcome to the evolving leader.

Andy MacMillan:

Thanks for having me, guys, and congrats on a heck of a run. Five years you guys have had incredible guests and a great track record. So looking forward to what's next as well, but a privilege to be the Capstone here on this great run.

Jean Gomes:

Thank you, Andy, how are you feeling today?

Andy MacMillan:

Good. Feeling good. It's early for me in the morning and getting ready to get going. Yeah, things are good.

Jean Gomes:

Cool. Can we start with you setting the scene for what altrix does for its customers.

Andy MacMillan:

Sure, altrix has been around for over 20 years. The company started by helping people on their desktops work with spreadsheets in more effective ways. So you can imagine lots of people every month. Maybe you're doing something like budget versus actuals comparisons, and you got to pull two spreadsheets together and do a whole bunch of work to kind of smash all that data together and make it work. We helped people do that and then automate that. And then as we've grown and grown, we started helping people do that sort of an enterprise scale. And so a lot of businesses have essentially data automations that they run on Alteryx. And now more and more, we're seeing people build those kind of data workflows to power AI agents and llms and things like that. So you can imagine, if you wanted to write some kind of cool custom GPT or something that would maybe help you calculate sales commissions or help you understand your travel expenses, the first step would be, I have to go pull all that data together and have it make sense, and then be able to hand it to the GPT. And so a business user can do that in Alteryx. It's not a coding platform. Think of it as being for somebody who's good at Excel, not somebody who wants to spend their nights and evening writing Python code. Yeah.

Scott Allender:

So I'd love to kind of start with getting your sort of view on the sort of state of the nation, assessment of how organisations are currently responding to genitive AI, because. Getting a lot of different reports and perspectives, and I'd love to get your insights here.

Andy MacMillan:

I think it's pretty chaotic, but also exciting, and hopefully that's the kind of world people enjoy living in, because, like, that's the kind of world we live in now. I think the pace that we take on change now in business is completely different than, say, 20 years ago. I think the kind of enabled by internet and mobile, all of a sudden when things happen, they kind of happen in a snap, right? And and so when something like generative AI comes out, I think people can see the potential. I don't think you have to spend a lot of time in chat, GPT or Gemini to sort of go, Wow. This is different. This is something new. And to think about how you can apply that to your business or your life. But then you have the challenge of, okay, but all the all the scaffolding is not there yet, all the infrastructure is not there yet. However, I know that this is going to happen fast. I learned from the last couple of big waves. This is going to happen quickly. And so I think people are, are sort of scrambling. And I mean that in a positive way, I think that's people leaning in and trying to figure it out. But I think we're kind of in the scrambling phase right now as people try to move quickly, but maybe don't like I said, have all the scaffolding in place yet to really know how to how to scale and find value, find ROI and so that's the sort of chaotic moment we're in right

Jean Gomes:

now. Given where on this, you know, there's a lot of noise and kind of countering views and some fairly hysterical kind of commentary on on AI adoption, when you are talking to senior leaders, when you're talking to CEOs and C suite executives, what's your kind of sense of what's most helpful for them in building that scaffolding and actually making practical steps forward so they don't fall into the traps, perhaps, of some of the digital transformations of the past, I think

Andy MacMillan:

one is looking for an outcome you're trying to drive in your business generally, and applying AI towards it versus, you know, I got aI I'm running around trying to find what I'm going to do with it. Can run people in a lot of different directions. So I definitely think that's one. I think the other is thinking about it systematically. I think of AI as being this very interesting constraint remover, and when you remove a constraint, new constraints arrive. And so I don't think it means that things scale infinitely. But, you know, I spent a lot of the time in my business, thinking about, you know, what if we can write code 10 times faster? Like, how will we organise our teams differently? Maybe my teams seem to be located closer together, like, what changes about the business? And so I think one, you know, pointed at real problems, and think about how to work backwards towards solving business metrics that you already care about. And I think the second is, when you do that, think about it as sort of business process reimagination with different constraints. I think when we limit it only to a personal productivity tool, you're not really reimagining the business process. And if different people are going to be different levels of new efficiency, you're going to have to rebalance your teams and figure it out, and you're right back to business process reimagination. And so I think for me, those two things are the key pieces to really trying to drive value when you're trying to apply AI to your business, not just sort of play around with or learn a bit about AI.

Jean Gomes:

That feels very different from some of these digital transformations in the past, where it kind of gets driven down to the digital director or the head of transformation or the IT department. This sounds like it's a much more cross functional leadership required.

Andy MacMillan:

I think you can think about any aspect of a business and imagine how AI changes it. And I would posit that the people that will ultimately think about how to change those parts of the business will be those people in that part of the business. So I agree with you. Whereas digital transformation, I think, initially started off very technology driven, you know, oh, we need to stand up a website and E commerce and things like that, and we turn to our technical teams to do that. You think of where that ended. We have handed most of that stuff back to the business, right? Most websites are, you know, yeah, the IT team runs the the infrastructure, but the marketing team owns the website, or the the merchandising team owns the E commerce site. I think with AI, you know, every leader in every functional area is going to have an opportunity to look at the thing they're running and try to reimagine, how would I do this with this new capability that I've never had access to so you're going to be in the Office of Finance and thinking about, well, how would I, how would I manage Travel and Expense differently? If I have access to a real time agent, you're going to be in the legal team and say, how would I run my legal team differently if I can red line a document using AI before I ever have my lawyers actually look at it? And I think that's not an IT problem. I don't think that's going to, I mean, it is going to help. They're going to provide against a lot of that scaffolding. But I think unlike these other technology transformations, I think it's pretty easy to imagine a universe where, no matter what function you're in, you need to be thinking about, how does this new capability? Forget about as a technology, just this capability. Let me scale what I'm doing and. Entirely differently, and I think that's where we're going to see people over the next year or two, really figuring out almost function by function. Like, what does this mean if I work in accounting? What does this mean if I work in supply chain? What does this mean if I'm in sales? And I think anybody who's not thinking about that risks sort of having their skill set get left behind.

Scott Allender:

What about beyond a year or two. Take take me five years, 10 years down the road. What do you think an automated workplace looks

Andy MacMillan:

like? Yeah, I think companies look a lot different. And I think again, if you if you imagine it from a Theory of Constraints standpoint, and again, I think it's helpful to almost think about it by function. I'll give you an example in software development over the past 20 years, one of the big trends has been offshoring. And the reason is, the main constraint when you're building software is how many developers do I have access to? Right? If I more developers, I can write more software. And so you would have your designers and your product managers often close to customers the biggest markets, often the US. So those people might be here in the US, they would design things. They would send them offshore to a lower cost location where you had a lot of engineers. And they would do these, you know, two weeks sprints. So if you're not in software development, a two week sprint is two weeks of writing the code, and then you sort of pop up two weeks later and go, Hey, here's a here's a demo of where we're at and how it works. And you sort of iterate. Imagine now if that sprint only takes an hour? Well, I don't want to have that team now on the other side of the world, I might want to have them really co located, iterating with that team. And so again, I don't know if that becomes the new constraint or not, how fast I can iterate, but how many people I hire, where they're located, how they work together, what that job entails. What does it mean to be a software developer if I'm using coding assistant tools. So that job changes too. So I can imagine, in five years, the entire model around software development doesn't go away. I don't think it's all the robots doing it like I don't think that's, that's the you know, I think we're headed for that dystopian future. I think we are headed to a place where we'll write better software faster. We'll do it. I think with teams, it can iterate much more quickly. And so that makes me start rethinking, well, how do these people work together, and where are they located, and what are the new constraints? Is the new constraint, how fast they can work versus how many developers I have? I don't know. I think about that with with sales people, we have a whole bunch of people. We surround sales people with that try to make them more effective. We have inside sales people, and we have renewal managers and all these other things. And you start to wonder, well, what parts of those functions can AI help the salesperson do more effectively? So do I hire more sales people because they're more effective? Do I have to hire fewer salespeople because they can get more done? It's going to change. And so I think leaders are going to have to come at every part of their business. And I think a CEO is having to work with every one of their functional leaders to kind of come at it with an open mind. And again, really operate from like a first principles. Again, I really think Theory of Constraints is very helpful. When you think about AI, it will just change what the constraints are. And so that means you different ratios of roles, different skills in those roles, and so I think businesses will look a lot different in five years.

Jean Gomes:

Let's pause here and on this theory of constraint idea, because that's a very helpful lens to think about the underlying assumptions that are playing out in in in how your business processes, business model and so on is developing. Can you walk us through an example? How? I mean, you've given us a few high level examples, but how you think about applying that and how new constraints start to emerge? How do you what's the if you were guiding a team thinking about how to apply that thinking in a more detailed way? Can you just walk us through an example to help us?

Andy MacMillan:

Yeah, I spend a lot of time with all of my teams trying to think through, if I want this team to go faster, to be more efficient, whatever the goal is of the thing that I'm working on, what is the one lever that changes the most? Right? So if we were going to double our sales, what's the first thing everybody think of that changed? Was it that we had twice as much pipeline? Was it pipeline? Was it that we had a twice the win rate in our customers? And simple questions like that can lead to, what is the core constraint? The fun thing about constraints is, as soon as you fix a constraint, something else becomes the constraint like that's just the way that works. But you start working through what are the biggest problems? And I think that's a useful way to think about rolling out AI, if I can apply AI to my biggest constraints now, it starts to really open up my business to scale and do new things. Versus again, I'm running around with AI, you know, it summarises stuff. Well, what can I go summarise like that's not a particularly interesting business problem to go solve. But when you think about constraints in a business today, very often, constraints come down to head count. It is one of the biggest expense items in a lot of businesses, certainly a lot of kind of software style businesses. And if I start applying AI to make people dramatically more productive in certain roles, and maybe that's not as dramatic in other roles, again, those constraints start. To shift. My ratios start to shift. So if I think of something, yeah, like my go to market team, it's very ratio driven. You know, I have all these regional teams, and in each region, I have, you know, X number of sales people, and I've had X number of sales people. I have, you know, y number of field marketers, and I've got, you know, z number of of technical sales specialists that are helping the sales people. And so you look at that, that's a pretty finely tuned machine. It's a it's a pretty common in my industry sort of software go to market motion. I would guess, if I met with 10 other software CEOs, our ratios look pretty similar, you know, maybe a little different here, a little different there, but for the most part, pretty similar. And now imagine AI makes one of those groups three times more productive. It makes one of the ones only 50% more productive? Do I now change all the ratios of how these teams work? Am I hiring kind of a different workforce at that point? How do they work together? That's going to change. And so that's really where I start to think about the impact. It's not all our jobs go away and the robots do all the work, it's more well, it's going to change how we work together and what work we expect people to get done. And I think that, to me, is, is interesting. I think the other one, I think a lot about, is there's this debate, I don't know which side of the spectrum I'm on, of, you know, with AI do all entry level jobs go away because the, because the AI does all the the entry level work, or if the flip side, you know, I can give AI to somebody in the early part of their career. And it's this amazing amount of expertise that can sort of apply to problems. To problems. And so I think just that friction sort of shows I'm not sure the answer is one or the other. I think I go back to like, well, some barely, really senior roles might scale better, because you can give them access to AI. Maybe if my entry level people are now way more productive, because I can give them AI, might hire more entry level people too. I think a lot about when something's better and cheaper, people tend to buy more of it. And so I also think about employment that way. If what I get for my dollar is a senior executive when I hire someone who's way more productivity, I might hire more people rather than just hiring fewer people, because I've got productivity gains. So those are kind of the three things I think about when I reimagine what business looks like over the next couple of

Scott Allender:

years, what are some associated and emerging leadership challenges and opportunities for inspiring and motivating you know, economic activity in the sort of new world and the sort of new way of doing business.

Andy MacMillan:

I think a big one is acknowledging how much change is coming. I think people get it wrong when they start telling people, like, you know, don't worry, nothing's going to change. It's like things are going to change. I told my whole team, like, my my engineering team, for example, is starting to use a lot of these coding assisting tools there. I have a great engineering team. It's obviously a little bit nerve wracking when you start going, like, wow. Like, this, this thing can write half the code I would have written before. Like, that's an unsettling feeling. And my advice to leaders is is, you know, you lean into that. What I've been telling my team is, let's take up these tools. We've got a lot of stuff to go build so we're not maxed out on capacity like I would. I would take if you told me I got 1000 more developers at no cost, I would take them in a heartbeat. So there's a lot of room to grow, but for themselves, personally, your career strategy at this point can't be I'm going to hope my current employer doesn't know or use AI, and maybe for the next 10 years, I'll just find other employers that don't know about or use AI, like, that's not a career plan. Yeah, and so, so sort of embracing that with your team. Hey, we're on a mission together. This change is happening. You're going to work at a place that's going to support you going through this, and we're going to learn as we do it. And, you know, embrace that this change is coming. I think that's really important. And then to be listening, I'm not also just directing my team go do this, and I don't want to hear about the results. I'm trying to lean in and learn how are each of these functions changing? What concerns do people have as these ratios start to shift, starting to think about, how are we going to rebalance our teams? And our message internally has been, we're going to slow hiring a little bit right now. And what I'm trying to do is create space in our business. So as we rebalance, we can apply the head count as we're rebalancing. So trying to be really upfront with people, like, yes, there will be change that comes. We can kind of both manage that change as a leadership team, so that all the impact isn't just hitting the front lines as we, you know, hire a bunch of people and go, Oh, oops, we should hire them over here. Like nobody wants to work at a company that does that. Does that. So sort of acknowledge, yep, we're being a little a little cautious with hiring, until we see, kind of some of the dust settle on some of these ratios, but we're going to lean in. And I think that's really important. I think people want to feel led through change, not that change is being managed for them. I think a lot of leaders make a big mistake trying to obfuscate change and challenge trying to obfuscate into the change is coming. And I do the opposite. I get in front of a say, this is happening. You read about every single day, every conference you go to, you know this is going to be a place that sort of helps you go through that change.

Jean Gomes:

How are you I mean, I love the kind of. Spirit that you're creating in in this because, you know, psychological safety disappears when people are in in an environment where the technology is threatening them in that way. And that's always been the case, but now you kind of a whole new level of threat, because it's, it's it's intelligence, not just automation. What? What are you doing to help people at a practical level, to be able to quickly lean into all of these things. What have you learned about what works?

Andy MacMillan:

Well, part of it's giving people access and opportunity to play around and work with this stuff. So I did this, not only here, but at my last company, very early on. We licenced an LLM non training, you know, private use, but company wide, gave people access to that, gave them training. So we run a regular training on how, what are the rules for using this? How can you use it? You know, what data can you put in it? What can you be doing? We've been showcasing on our all hands on things that people have built using AI and so, really trying to make it a place to sort of learn and let people sort of evolve and build stuff. So I think that's a big part of it, and sort of celebrating that, and again, just continuing to to highlight, you know, for us, we're trying to efficiently grow our business. You know, as you mentioned in the the opening, you know, we just went through a pretty substantial take private we did a financial restructuring of the company, got us to a very healthy place on our balance sheet, and we want to drive even more growth. And so I've been telling the company, this is the perfect place to apply AI. We want to drive growth while we manage having a strong balance sheet. So from the top level of the company, I've given a vision of how AI is going to help us do this in a way that brings everybody along, I've then tried to provide them the tools to start to, frankly, play with the technology. And I've told them, you know, you are free to start applying this to how you do your job, and let's start sharing what works. And so I think those things are all part of it, and it's just a continual topic. I think this is something that comes up on almost every one of our all hands. I write a weekly note to the whole company. Every Sunday night, I just write a little email. I talk about AI transformation quite a bit in those emails, what I'm doing, what I'm seeing other people do. I built a little GPT myself using Alteryx to prepare some data for something I was working on. And I was like, I'll just show this to the company. So on one of our all hands, I literally just got out my little thing, and I'm like, here's what I'm doing. And, you know, and just trying to let people know, you know, this is kind of how you learn. You just sort of iterate and play

Scott Allender:

with stuff. When I echo John's sentiments about the sort of spirit that you're setting and the tone that you're bringing, and your sort of intentionality, which is really inspiring as you talk about this stuff, I'd like to take a slight tangent and kind of hear about how you got here, like, what are some of your sort of most important leadership lessons that has readied you to lead this organisation and prepare people for the future?

Andy MacMillan:

I think one of them, Scott, that stands out specific to kind of this approach was, you know, when you when you become a hired CEO. One thing I tell people, very rarely does somebody say, hey, this business is running perfectly. Why don't you come run it? So there's usually stuff to go in and do. And one of the things I found earlier, one of the first companies that I joined as CEO, was the more people I openly shared problems with, the more people wanted to help with those problems. And I always felt like, wherever the line got drawn, like, if I you know that, I think I started too small with who knew about what we were trying to do. There were some real problems in the first business I joined. I mean real, real issues. And those issues hadn't been shared widely in the company. And I sort of found that as those as I started to bring more people, kind of into the tent. People were like, Oh, yeah. Like, actually, that makes sense. Why things have been like, the like, how do I help? But then wherever the line had stopped to the next level was like, what's going on? Like, I'm really frustrated. Why are people and so I've just found the way to get everybody working on something big change, or whatever is, to bring as many people as possible into the process. And if you're really open with people again, in positive I'm a naturally optimistic person, so I'm always like, Okay, well, here's the problem, but we're going to fix it. You get people helping you fix it. When you try to fix the problem, before you tell people about it. And I think this can be something leaders try to do. You think, oh my gosh, if, if everybody finds out that we have this big challenge, you know, people will quit, people will leave. You know, people can go. They'll vote with their feet, and so then they're on the outside, looking at the leadership team, going, seems like something's not working. Nobody's telling us what's going on. They must not know what to do. That's unsettling. Versus, hey guys, we've identified the problem. Here's what it is. It's a big problem. We're working on it, and let's figure it out. Most people, even if, like, I don't know this might be really hard. They sort of grab onto the rope and they start pulling, and people like feeling like they're helping work on the thing that you're working on. So I think that's one of the big leadership lessons for me. I think throughout my career, I came up through the product management side of the world as a developer, early on in my career, I've always liked the problems the company works on. I just find that interesting. And so I think one of the things that served me well as a leader is, strangely, I never managed frontline people. My first leadership Job was a VP level job, and I managed people that were 10 years older than me, and I sort of got this big like career accelerator. So So one, I've never been a micromanager, in part because I've never had to lead people in the very first stage of their career, which is where I think you have to do the most hands on management. So I've gotten management. So I've gotten to be kind of a little bit of a senior leader, leading leaders early. And then the other is, while doing that, I've always enjoyed leaning into problems, but realising when you're a senior leader, it's not always your problem to solve entirely. But I like to sort of, hey, let me I kind of call it participant leadership, like, I like to, hey, we're having a design meeting. I'm going to come to the design meeting as the CEO. I maybe have some context of what's going on in the market and the company, but I'm not running the design meeting. I'm not the ultimate approver. I'm just sort of there to participate, and I really enjoy that, and that has served me well, I think throughout my career, is to be somebody who just likes to, you know, work with different teams trying to solve problems around the company, but not feel like I'm the the ultimate solver. I'm sort of an enabler.

Jean Gomes:

Coming back to, you know, the kind of challenges of embracing AI, we hear a lot of evidence now coming that it's making people de skilled. It's creating cognitive complacency. People's memory is going they can't remember what they've created on AI and so on. What have you learned? I mean, either in your own use or in helping your your teams to adopt it so that they get smarter, not dumber, using it.

Andy MacMillan:

Um, I don't know. I think there's some, you know, like brainwave, kind of fancy studies on all this. But my analogy is a little bit, you know, I think they said that about calculators and computers. And I'm not really sure where dumber as a society, because we use computers. I remember my dad, when I was growing up, always wanted to teach me to do math on his slide rule, because that was the way to really understand it. And I don't think I ever understood how to use the slide rule, and I don't think I'm any dumber for not having figured that out. So I feel a little bit like it's a new capability. How do we learn how to use it? I don't think that means we don't think anymore. I think it means, pretty soon, we learn how to work with this much smarter set of intelligence that can help us learn a whole lot more. I feel like I learn a tonne using AI every day. I find myself even just when I get interested in something, I can go into chat, GPT or Gemini, and sort of work through a problem in such depth, where I learned so much. So I'm not entirely convinced that this is something that's going to make us dumber. I think it's something we're going to have to learn to work with differently. It might change how we operate. I would argue maybe the advent of like, my kids just get to use calculators, even when they take the AC, T and stuff. So, yeah, maybe they don't do off the top of their head arithmetic as fast as my generation did. I don't know that that's going to set them back, but, you know, maybe it changes. So I think that's my my mindset is, I don't think this is a replacement for cognitive capabilities. I think it's a new skill that we're going to learn, and I think it's going to mean that people can do more things more quickly, and do them better. I think about the even around the house, like I can go into Gemini and get help on doing a home repair. I'm terrible at home repair. I'm a lot better with Gemini. So does that mean I'm dumber or smarter that I know how to use Gemini before I start, you know, smashing holes in the walls. I think it makes me smarter than I know how to use it, but I sort of get the argument of, like, Well, my brain didn't figure it out. Like, Well, okay, but my brain wasn't doing a very good job figuring out home repair before I started to have

Jean Gomes:

access to this. So I think, you know, I think it probably comes down to how you use it, and as a, as somebody who's, you know, grown up as a, as a product manager and probably has a quite good understanding of how to think about solving problems. It really helps you. I'm, I'm more concerned about, you know, how people who don't know how to use it are sort of relying upon it like a search engine to get easy answers, who don't dive into the detail, who don't use it to think together, you know, might, might fall into the trap of, you know, losing their abilities. I

Andy MacMillan:

do think we're starting to learn what it's good at and not good at. I mean, we've all had the experience where you you ask the LLM a question, it gives you an answer, and you sort of go, are you sure? It goes, Oh, you're right. This is totally wrong. How about this idea? And so I think we're learning also sort of what it's good at, what it's not good at, to your point, which is, maybe we're not taking everything always at face value. Sometimes there's a little bit more connecting the dots that we want to be do, doing, rather than just, you know, offloading all of this. I think every student I know has learned the lesson of, you know, oh, I used one of these tools to summarise the thing I was supposed to read for class. And I got to class and realised I didn't, didn't know what was going on, right? So you, I think there's sort of a where to use it, how to use it, that we're all still figuring out when to trust it, when to when to drill deeper. So I agree with you. I think that's, that's, again, kind of a skill we're learning.

Jean Gomes:

What are your top tips in using it? Well, I mean, what? The things that you've learned about it.

Andy MacMillan:

I think, as most people say, I think learning about how to prompt and ask for very specific things is important. I'm also learning a lot about the responses come back with full confidence, like the dial is always set to 211 on confidence, regardless of how confident it actually is. And so you can query into like, How sure are you, and where did you get this from? And so I think, sort of, again, that level of interrogation on things that matter, I think, is really helpful. I think we're seeing more of this now getting cited. So I'm finding now often, if I ask, maybe my personal life, a more general question, and now it shows a little bit of its work. And sometimes we'll show sources, I'll find myself clicking through the sources. So it's like, okay, like, yeah, it's summarised for me. And everybody felt like, Oh, this is going to be the death of, you know, search engines with click through results. And now I'm finding like, no, no, I've read the summary, but now I want to click through, you know, oh, here's the thing, and there's three references. And I'll look at the middle and go, Oh, that looks interesting. And I'll kind of click through and and read. I think that's new. I don't think I was doing a lot of that, you know. Six months ago, I was sort of taking sort of taking it at face value. And so I think those kinds of things, you know, learning to prompt, learning to drill in, is is a big one. The other is it work. I've learned this pattern of trying to do narrower things. And so what I'll do is, again, maybe, because I work at Alteryx, I'll pull together a set of data, right? Like so, for example, I was analysing my sales pipeline recently. I went into Alteryx. I pull in my Salesforce data, I do a little calculation on my pipeline, and then I hand that to a narrowly scoped GPT and say, Okay, you're a pipeline expert. Help me work through this. I think that's really interesting, too. You're not doing this like, broad general you know, I think of it as like, are you asking a smart friend a question, or are you asking a specialist a question? And more often, I'm realising, you know, AI is sort of a smart general friend, but I can sort of tell it to be a specialist. I can give it a narrower set of data and a narrower set of instructions, and I think I get real value when I do that in my business work, right? And that's important, because I think when you ask it generalist questions, you get generalist answers. And it worked. That's not that interesting. If I say to to chat GPT, you know, what will my sales commission be if I close this deal and it goes well, here's how companies normally calculate sales commissions. It might be something like this. That's not the right answer. Like, the answer I'm looking for is, like, what will it actually be? So again, if I it work, can create a small data pipeline of how we actually do that, and I can tell it, hey, only work in this thing. Do this work. I think that's really useful too. So I think also learning to think about scoping, you know, in personal life too, like I've done that with. I wanted to analyse some some stocks recently, and so again, I gave it a narrow data set and a narrow set of instructions and asked it to do something, versus just asking, you know, the front page of Gemini or something, to go do the work. So I think that scoping is a skill set that will emerge to

Scott Allender:

those are good suggestions. Are there any other sort of, maybe five to 10 minute a day practices for people listening saying, I've been kind of avoiding this. I don't really know how to use Gemini or chat GPT the right way, anything that you'd say. You do this 510 minutes a day, and you'll start to really build your your muscle around AI, yeah,

Andy MacMillan:

I sort of, I like to think of it as, like, imagine two very discrete altitudes that you want to interact with an app. One is sort of the, you know, do some leg work for me, kind of stuff, you know, on the ground cover, summarise this email kind of stuff, right? Like, it's great, helpful, but it's pretty kind of low level, like, hey, grind out some work for me. I think the big unlock is when you start to think of it more like, hey, what if I could hire a McKinsey consultant to look at this? Normally, I wouldn't. But like, I can. I can ask this thing to act as an expert that understands audit and finance, and go through this thing really quite fascinating. What you can get out of it? I've been doing things like for my last board meeting, I get my financial sent to me by my CFO, and I can go into, again, our private non training instance of an LLM, and I can say, imagine you are a BCG or McKinsey consultant advising a CEO in a PE backed company on the following board meeting. What trends in the business would you recognise? What kind of questions do you think the board would ask? Now, I would argue, 80% of what came back, like, I do this for a living. I'm like, yeah, those are the things. But you get a couple nuggets here. They're like, okay, that took that took two minutes, and I got a couple of it's point. I should think about that. One of the was a really interesting idea. Didn't come up my board meeting, but I was like, I should take that and go talk to my team about that idea. And so I think again, using it at that higher altitude, again, with a scope set of questions, of, you know, hey, act as an expert in software development. You know, look at this project. What would you say are the holes in this project? What other areas would you advise? It takes two minutes, and even if you know, you only get a really interesting answer one out of three times. That is not a lot of. Effort for a lot of material that you can get back. And so I think that's really useful, I think especially for senior executives that are trying to operate across a large set of information coming to you. I'm finding more and more often I'm taking something sent to me and I'm just dragging it into the LLM, and I'm not doing the summarise for me. I'm doing the Hey act in this role and help me really think through what this does. And then again, you can go back and forth with it. Hey, that's a really good point. Why did you bring that up? What are other companies doing around that, you know, prepare a two pager for me on how I would go about, you know, looking into that area, it's a really interesting brainstorming exercise, kind of at that level that I think people should do more of.

Jean Gomes:

And, you know, this is probably one of these kind of questions or thought experiments that comes and goes with every new trend. But one thing that came out probably six, eight months ago was the idea that at some point, you know, an organisation might actually have a, you know, an AI CEO I'm just interested in, you know, like your thoughts on, on that kind of idea.

Andy MacMillan:

I mean, someone said recently that AI makes very confident decisions on very little data. And I'm like, well, that's most of my job. So maybe, maybe they could do that quite well. You know, I don't know. I go back to, I think there's a, there's an amazing capability set emerging. But I still think businesses are going to be people figuring out what they want to go do, why they want to go do it, and sort of using these tools to think about how to go do that. So I definitely think you could imagine having a series of agents acting as really skilled consultants and advisors and a whole bunch of areas in the business, and you might turn to that more often than not. I still think there's a level of accountability that exists in the job, in a lot of roles, not just CEO, but also CFO and things like that. I think we're a long way from somebody saying, you know, the financials are good because the robots signed off on it. I think we're gonna say who signed the financials to say that. That's right, a little bit like that. You know, there was a Waymo recently they got pulled over here in the Bay Area, and there's this great video the cop walking up to the window, and there's nobody in the driver's seat, and they're trying to figure like, Well, what happens now? Because the Waymo made an illegal U turn, I don't know that we're ready for that to be like a company that did something wrong or a company that needs to make a hard decision. So I think there's a lot of play still in this world for people having ownership over what we're doing, but I do think the role changes. I think it'll be hard to imagine being a CEO a couple years from now and not being regularly advised and interacting with, you know, data driven AI, I think that's, that's the reality of where we're headed. What's

Jean Gomes:

the thing you're most excited about for next year? The

Andy MacMillan:

thing I'm most excited about for next year is we have just started to enable in our product the ability to let people build their own data pipelines and put them directly into whatever kind of LLM they're using. And so for me, I have a whole model I use to run the business, a whole set of meetings, cross functionally and stuff like that. And I'm basically creating customer gpts aimed at every one of those meetings. And I think I'm going to live in a universe next year where before we go to every one of those meetings, we can have a report coming to us, generated by our AI agent telling us all of the things that we're going to be focused on in that meeting. And I think that's going to make life a lot of a lot more fun. Like, I'm kind of excited about the pace at which I think I can run the business using AI kind of blended into my current leadership model. And I don't think this is a three year off thing. I think this would be something that I'll be able to do at altrix in the first half of next year, and I think that'll be pretty I know I like change, so it'd be interesting to see, like, how does that how's that work?

Scott Allender:

Thank you, Andy, this was really insightful and a really practical way for us to wrap five years of incredible conversations on the evolving leader. But don't worry, folks, the evolving leader isn't going away. It's just evolving. There is a new multi trillion dollar global economy that's rapidly emerging, spurred by transformational advances in our understanding of how our brains and bodies work and the question of, what are humans for in an automated world, how we feel, how we think and how we see, will profoundly influence our economic success and our well being and our capacity to embrace uncertainty. So this January, January 2026, a new show is coming to you from us called the mindset economy, and our goal, as always, is to forge a more human world. So we'll see you there. And until then, I ask you, for one final time, the world is evolving. Are you? You? You.

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Jean Gomes

Co-host
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Scott Allender

Co-host