What to expect?
Transcript
[00:00:01] Brandon: Technology could be the field plough, the typewriter, email, the fax machine, now AI. We've always designed and adopted technology to help us be at the things we're trying to do in the world. AI just happens to be the latest of these technologies.
[00:00:20] Naomi: Welcome to The Future is Human. I'm Naomi Trickey. And in this podcast, I talk with leaders from tech and hospitality businesses about how both they and their people are navigating the edge between humans and technology in an increasingly automated environment. We break out of the mould of a standard business conversation to hear more informal perspectives and reflections to understand what people are really feeling about the future of work.
[00:00:48] Naomi: Hello. Welcome to The Future is Human. Today, I'm really delighted to be joined by Brandon Sammut, who is the chief people and AI transformation officer. We're gonna talk about that job title in a second at Zapier. So, we want to talk about navigating the edge between humans and technology in an increasingly automated world. And you are literally doing that in one job, so you were an obvious person for me to ask if I could ask you some questions. And I know that you've built talent systems that really drive performance and purpose, and blending experience across recruitment, and sales, and business development operations. I'm really looking forward to hearing more about how you do that and how you navigate that edge between humans and technology. So welcome, and thank you for coming on the show.
[00:01:34] Brandon: It's great to be with you, Naomi.
[00:01:35] Naomi: So, let's go straight in with your job title because it's quite unusual, although increasingly less unusual, actually. I've heard a bit about it, but I'd love you to talk a bit about how you landed here and what your title actually means in terms of your role.
[00:01:51] Brandon: Yeah. Oh, it's a mouthful, isn't it? Chief People and AI Transformation Officer. What does that mean, indeed? So, when I came to Zapier four and a half years ago, I came as the team's first chief people officer. And what's interesting about this new role, which now more explicitly involves leading or guiding our AI efforts inside the company, is very conceptually aligned with why I ended up here in the first place. A chief people officer, a head of HR, but really, I would say, ideally, any senior leadership role at a company is effectively a talent leadership role, first and foremost. And even if you go back hundreds of years ago, if you're interested in maximising human potential, maximising human performance, helping a team, an organisation, a village, a community of people be unusually successful together, you've always been interested in the technology piece of that. Technology could be the field plough, the typewriter, email, the fax machine, now AI. We've always designed and adopted technology to help us be better at the things we're trying to do in the world. AI just happens to be the latest of these technologies and what we found when we were embarking on kind of our own adoption of AI over two and a half years ago at Zapier that like a lot of other org transformations that came before this one, our belief and really as we studied kind of the history of this, you know, is that the difference between the companies who really make the most of the opportunity compared to the ones who kind of miss it. It typically doesn't come down to whether you chose, like, the perfect iteration of that technology at first or whether you have the perfect policies or governance frameworks; those are all very important. The differentiators typically are leadership, talent, and culture. Leadership, talent, and culture. And when you think about it that way, it's like, oh, well, that's what our leadership team wakes up thinking about every day. It's certainly what I wake up thinking about every day, and so does my people team at Zapier. And so we, in some ways, started naturally filling in some of the blanks as it related to how our team was trying to use AI, from skills development to use case ideation to rethinking, ultimately, how and for what we hire, how we onboard people into the organisation. And so when, about three months ago, Wade, our CEO, asked me to update my title to chief people and AI transformation officer, it was really a reflection of what was already going on in the company at that point, where the people team really was out front guiding the scale-up with AI.
[00:04:24] Naomi: That's so interesting because I was listening to the new Spotify CHRO last week. She was talking on one of the Netflix podcasts, and she was talking about how the requirement for a chief people officer is such a variety of skills. And, actually, it just feels like this is just another skill that we're adding to an already fairly broad role. Is that your, because that really resonated with me, I was like, oh, yeah, it sort of makes sense.
[00:04:50] Brandon: It sure does. I mean, the roles become incredibly expansive, which, by the way, is like you wake up on one side of the bed on a particular day, it's incredibly disorienting. You wake up on the other side the next day, and it's very motivating. And, you know, practically speaking, I find it to be both. But I will tell you, it's hard to think about a more, outside of the CEO role itself, like a more interdisciplinary job in the C-suite these days. Again, even back in the day, interesting, like, HR, it was typically even separate from staffing. So you have, like, HR, and you have recruiting and now, typically, companies of both sizes, you'll have one CHRO or CPO sitting over the whole thing. And then at a point in time, the people organisation picked up real estate in the workplace, which then became a whole other, it took a whole new level of sophistication with the pandemic, return to office, new ways of working, hybrid work, remote work. And then even more recently, what you're saying, Naomi, you know, think they're thinking about, like, how the company kind of adopts and makes best use of technology. And so, yes, I mean, the role is incredibly interdisciplinary, and I think that's part of what makes it really interesting.
[00:05:57] Naomi: Yeah. You and me both. And, actually, as you were sort of talking, you've worked across multiple disciplines, haven't you, in your past? So, from finance, recruiting, tech strategy, how does that breadth of experience shape how you build teams and align people with business outcomes? And I'm also really interested in whether there is something specific about fast-growth tech companies that lends itself to your work, or do you think were gonna start seeing similar intersections overalls in other industries?
[00:06:24] Brandon: I think we’ll see similar intersections in other industries and other stages ultimately as well. I feel really fortunate to have come up as a professional in largely, like, mid-sized high-growth organisations, and the reason it's been so helpful is that, all of the things being equal, I've been able to be given, like, unusual, sometimes unreasonable amounts of responsibility for where I was in my career at that time. I mean, gosh, I remember my first chief people officer job. I think I was 33 years old, and then the company became a public company a year later. So, 34, public company CPO, so that's a trial by fire for another day, but what a gift. What an opportunity. So, I think for some folks, this small to midsize, this growth story is a growth story for all the people involved, too, naturally. And as it relates to kind of interdisciplinary backgrounds, I do see more and more CEOs looking for this interdisciplinary background for, really, not just the chief people officer role on their team, but other roles in the C-suite as well. Now, Naomi, I know that you also come from a less traditional background into the work that we do every day. I think that was a point of affinity when we first met, and I love to see it. Because at the end of the day, even within the people organisation, there are components of what we do that have direct corollaries to how the business runs overall. So, you think about it. A lot of the things that our teams develop; those are products and services, a hiring process, compensation program, talent development program. You can kind of shape those and build them and improve them, just like our customer-facing product teams develop and improve our own products. And then similarly, yeah, I talk with my team a lot about this notion that, hey, when we're designing something like a compensation program, we can technically be right about all the details. So, the product design, we benchmarked it appropriately, and it follows all the great practices, and it's really well-tuned for the company strategy. So, it can be technically correct, but we can still get it wrong. And then it's like, well, what do we mean by that? Well, that's the go-to-market piece. So, off on the back end, we developed this, like, really well-tuned aligned program, but the way we market it or ship it to our end users, our fellow teammates at Zapier, if we fall down there, then we didn't get it right at the end of the day because that's where the impact is really meant to be had. And so there are product development and go-to-market muscles, like, waiting to be built in any people or HR organisation.
[00:08:45] Naomi: I love that. And our customers work across a variety of disciplines as well. So being fluent in the language of the business is something that I found particularly helpful. And also, when you're hiring other leaders, we look for T-shaped leaders. So, people who have that kind of awareness, I suppose, of the wider business, but can also go deep on their function, is when you get to this point in your career, what you're expected to deliver, right?
[00:09:10] Brandon: I would agree. I think having some of these other experiences that you and I have had before we came into the CPO role it's also just a good empathy build. I found it helps me, like, build better, faster connections with my peers. The CPO-CFO relationship is such a critical one, I mean, it's in both directions. So, with the CFOs, I've been really fortunate. Every CFO I've worked with has been a remarkable talent leader, and thank goodness. And similarly, some of the feedback I get is, okay, well, Brandon can think like a CFO. He understands the economics of this business. He understands our operating plan and where we're trying to go, dollars and cents. And, therefore, like, basically, it's a translation there. We have a shared language when we're approaching some of the bigger questions that we're trying to navigate with the team.
[00:09:54] Naomi: I love that. And then, of course, in from left field comes AI to kind of challenge all of us to think differently about the scope of our role. So, I'd love to dig in a little bit on AI, because I know it's a component of your product, but it's also obviously part of your role. So, we've talked about the value of creating, not just consuming AI, and that's increasingly important for young people, but also, I think, for everyone in the workplace. And I know the Zapier team are just hotshots when it comes to using AI at work, and I've heard some examples. Emily gets a lot of kudos for her work. But if you had a 100, let's kick it off with what sings out for you from your team. So, if you had 100 bonus points and a gold star to award this week for an example of AI usage that you've seen, who would you give it to? For what, and why?
[00:10:42] Brandon: I would put it this week specifically. I'd give it to our talent ops team. This is our recruiting operations unit, small but mighty, and they are completely redesigning two things over the last few weeks: our referral program, so how we refer folks into the organisation, and also how we do reference checks. So, it's kind of that both ends of the recruiting workflow, referrals at the beginning and then references at the very end. And the things that earned them the gold star, one, before they started thinking about AI or how AI could help with both of those practices, they started by really crisply defining what the business opportunity was, like, why focus on a redesign here? Is there a problem to solve that's worth prioritising? Is there an opportunity to seize that's worth prioritising or some combination of the two? Usually, it's a little bit of both. There's some pain, but then there's also an opportunity. And with the AI work we're doing inside of Zapier, we have a new-ish, just maybe six months old, framework for impact. And I saw our recruiting officer do a really nice job of centring that framework when they were scoping a redesign of both referrals and the reference process. In that framework, by the way, is, hey, when we are redoing a way of working with AI, there's obviously the opportunity to make it more efficient. That's where a lot of organisations start, make it faster, make it cheaper. And there's a lot of impact to be had there with some of these opportunities. That's great grouping. Let's just start. It's like, well, let's not stop there. So, the second part of the framework is quality. So, let's make it faster, cheaper, but let's also, at the end of the day, make it better. And that could be, like, higher customer satisfaction scores, that could be higher product reliability, whatever the case may be, not just faster or cheaper. But there's actually a third piece of that framework, so more efficient and higher quality. Let's make sure that by the time we do redo this way of working, we've made the experience of doing the work for the humans involved better, and we call that employee experience. So, the three-part impact framework for AI use at Zapier is efficiency, quality, and employee experience. And the recruiting ops team at Zapier, they've done a really nice job from the onset saying, hey, there's an opportunity here as it relates to how we do referrals in recruiting and then how we do reference checks at the end, and we're gonna make a nice step forward, if not a pretty big step forward on all three of these areas. So, that's the first reason they get the gold star. The second reason they get a gold star is that they ask for help. And so you mentioned Emily earlier. Emily, famously now, is the Senior AI Automation Engineer for HR at Zapier, developed from within the people team, started at the company on our learning and development team, and then this year was moved over and promoted into this role. And one of the things that Emily does when a team like our recruiting operations group sees an opportunity is they can raise their hand and say, we have a really sharp understanding of the work to be done here. We need a little bit of help thinking in a like a really big way about how to technically build the new way of working. And so, for the last 6 to 8 weeks now, Emily, our Senior AI Automation Engineer, has been co-building these new ways of doing referrals and reference checks with our recruiting operations team. So, not only are they developing a solution that is likely to be more impactful than if they hadn't raised their hand and asked for help, but Emily is also teaching them some new ways of building with AI that would have been harder to come by if they weren't co-building together. So, we're getting the more immediate benefit of a higher impact new way of working in these two areas, but we're also gonna end up with a more capable recruiting operations team when it comes to their own AI fluency.
[00:14:21] Naomi: I love that. So, it's essentially an enabler rather than just teaching someone. You're actually scaling what you're doing, aren't you, and scaling what Emily can do. And I will also really like the fact that it talks directly to that intersection between humans and technology because the humans are bringing something very specific, but they're using technology to do it. So, it's real, and it's believable, and it's the kind of thing the boards like and leadership teams like, but it's also very human. So, it's something that the people within the organisation can get excited about. And given that you're leading both people in AI transformation, how do you build systems that enhance human creativity and decision-making rather than automating it away? I think you've just talked about one example, but how do you think about that? Is it your efficiency quality, human experience kind of triangle, or are there other things that you think about to ensure that it's not just a kind of slick, let's lose the human?
[00:15:17] Brandon: Particularly when it comes to talent work, we think that human connection is going to end up being more distinctive even than it is today. If you think about it, when you're applying to an organisation or when you work at a place that has just like unusually effective managers or unusually talented leaders, that's already a talent advantage for the organisation. You get more out of your employees when you work in an environment like that, and of course, naturally, over time, they're more likely to stay. So, more likely to be their best, more likely to stay with the organisation, those are both really valuable benefits to the organisation and that's always been the case. My hunch is that with AI, companies that are able to maintain or even enhance the kind of humanity of their organisation are gonna be even more distinctive. And Zapier wants to be one of those organisations. Like, call it top 5% in that dimension, we think it has very tangible benefits to things that are really good for the business, also happen to be really good for the people involved. Interestingly, I think the same thing is gonna be true in our customer-facing work, and this is a question that all organisations are gonna have to ask. We all have customers. We have to make decisions around where we're going to maintain the humanity and the work, or customer service interaction could be a good example, where maybe we'll pull back on that in service of efficiency, for example, or some organisations, they're going to find a way to enhance the humanity in their customer-facing work somehow. So, there's some opportunity here to actually raise the ceiling for what's possible if organisations find that that becomes an advantage for them. And I think on a relative basis, it really could be if they have peers in their part of the market, they're actually pulling back on those human touch points or personalisation, you know, these things that really are related to customer satisfaction and depending on what the thing is, especially if it has anything related to services, actually, can have a direct relationship to actually be perceived quality of the thing being offered.
[00:17:06] Naomi: I love that. And for reference, for anyone listening to this, Brandon and I have talked quite a lot over the past few weeks, and I strongly believe that being human is the differentiator in an increasingly automated world. And that's part of the premise of the podcast, really, is to find other people and to connect on that point, and you've just described exactly that. And I think also, sort of leads me on to my next question, really. We know how important those human elements are in terms of building trust and connection for high-performing teams. And, Zapier, I'm right in saying you're also remote-first. Is that correct?
[00:17:43] Brandon: Remote first indeed. And since we started fourteen years ago, remote only as well. And so it’s kind of remarkable. I mean, fourteen years ago, when Wade, our CEO, and the two cofounders, Mike and Brian, started Zapier, they started it remotely from the very beginning. They never had one square foot of office space.
[00:18:01] Naomi: So, let's talk a bit more about that. So, how do you maintain that kind of human-oriented mindset and the closeness in a remote only automation powered company? And I also would love to hear any practical tips or practices you have in place to sustain async work because I know you're very thorough and kind of engaged and on it, aren't you, when it comes to that?
[00:18:24] Brandon: Well, absolutely. And I could see the thoughtfulness behind this distributed model from a mile away, even when I was getting to know the company before I started. It was almost five years ago now. And I liked so much what I was seeing. I thought I was learning a lot just by getting to know the company, much less actually working at the company. It's one of the reasons why I came to Zapier in the first place, because I saw this team, which now has 900 people working in 42 countries. It's just remarkable for a company of under a thousand people. It has some ways of working out and never encountered before. And some of them, it turns out, are pretty effective. And so to get to the first part of your question, though, around, like, how do you maintain that human connection with such a distributed team, well, hopefully, not ironically, in person human connection is part of the recipe. So Zapier, for example, has an annual all-company summit. It's a week long. We bring not only the entire team from all over the world together for an entire week, but also a bunch of our customers. And we spend a lot of time with customers, hearing from customers, actually co-building and sometimes solving customer problems live right then and there, as well as spending more time with our own product at the very edges of what the product can do. But, of course, in doing good hard work together, work that matters to us, in doing it in person, you build connection, you enhance connection, and then, of course, certainly in the evenings and things of that nature, there are things that are just purely social as well. But I think this focus on customer and product is actually a very durable foundation for connection, rather than the ping pong table or the coffee bar or whatever, because maybe those feel good. Like, I like going, I went to LinkedIn's office and met with one of their talent leaders earlier this week, made a coffee on the Top Floor of their really nice office. That's a nice experience. But human connection, for the most part, at work, happens in, like, doing good hard work together and, hopefully, most of the time, winning together, learning together, doing hard things together. And that's the model that we have at Zapier. But, interestingly, the cornerstone of that is in-person connection. We also have a program we call Solutions Sprints. And Solutions Sprints is effectively a budgeting model whereby cross-functional teams who are about to do a kickoff a new product development effort or getting, like, the beta of a product ready for GA or whatever the case may be, they can, in a fairly lightweight way, request that the 5, 7, or 12 of them get together in person for three days, five days, whatever the case may be, to get that thing kicked off or to get it over the line. And we call those solutions sprints, and we provide some, like we remove as much of the friction, both budgeting and logistically, as possible, so that folks can just, I've got an idea, we're gonna go get this thing done, here's why. And, again, they tend to be very focused on their purpose, they tend to be pretty focused in size, probably like 5 to 12 people, and they tend to be very cross-functional because just like I'm sure is true at Mews and so many of our organisations, a lot of the most important work being done in the company is not within, like, individual functional silos at this point.
[00:21:22] Naomi: Yeah. It's interesting, though, because I also think that one of the criticisms of remote practice is that it can drive silos. Whereas, actually, the more I talk to remote work practitioners, they often say the opposite, because I think they tend to be very focused on execution. And when you want to get things done, you need all of the right people, not just functionally your function in the room. You need all of the people in the room to drive things over the line, as you've just said.
[00:21:52] Brandon: I would agree. I don't believe that in-office versus remote is the characteristic that on which pivots, like, the Accenture's organisation are siloed or, you know, actually on the opposite end of the spectrum, like, really cross-functionally oriented. For example, go into any major city in the world, to one of the top five companies that have big offices and go into those offices and see how many of them, what percentage today, still seat their employees by function? That is a physical siloing of the workforce, and it's pretty deterministic of how the work actually gets done. So, with a remote team, you don't have these issues, but you still need to solve for it. So, the tendency towards siloing, you know, we like to affiliate, like to have a tribe to feel like we belong in this label of I'm on the people team, I'm on the finance team, I'm on the sales team, is just part of our humanity. At Zapier, one of the specific practices that we have is that we organise a lot of the work we do into what we call working groups. Some companies will call them tiger teams. Some companies will call them all kinds of things, right? But the bottom line is, at Zapier today, if you ask a lot of folks, like, who do you work with most closely, it will not be uncommon for folks to affiliate with a working group, cross-functional group, a very mission-oriented group, it'll be just as common for you to hear that than it is, you know, I work with the sales department or whatever the case may be.
[00:23:14] Naomi: Yeah. It's interesting, isn't it? Because I think increasingly, the people in our organisations ‘cause couple of characteristics I've observed. One, they tend to be highly intrinsically motivated and almost as a result of that level of intrinsic motivation, they're less interested in traditional categories of role. They're more interested in the skills that they can develop. And we're pushing very much that skills-based agenda because it allows for a degree of agility and flexibility in career development that historic notions of a job, a job description, and a role do not allow for, I think, is my view.
[00:23:56] Brandon: Especially these days.
[00:23:57] Naomi: Yeah. Exactly. And so you've talked about this idea of talent renaissance, which is a really lovely description. Can you explain what you mean by that? And I assume that AI plays a part in that, but I'd love to hear you talk it through for us.
[00:24:12] Brandon: It's a lovely question. When I first wrote that, it was in the pre-Gen AI era. So, I meant it before AI. So, I'll describe what I meant then, and then I'll tell you, like, how I'm thinking about it now. So, I wrote that within my first twelve months at Zapier. So, this would have been, like, fall of 2021, spring of 2022, around that time. And what I meant at the time were a couple of things. One was actually, to your point from earlier, inspired by, like, greater availability of remote and distributed work. And folks would be surprised to hear me say, I actually don't think remote work is a great match for every person. I don't think it's a great match for every company either, depending on your size, stage, what you're trying to do in the world, just orientation of the founding team, or what have you. No. But what I do feel really strongly about is that it's good and right that people, including founders, as they think about how they wanna start their organisations, have choices. And so I feel very strongly that this all-remote model exists in the marketplace because the more of us are running our companies these days, the more we are learning and getting better and sharpening it, which makes it an increasingly attractive option, not the right one in every situation, but an increasingly attractive option in more circumstances for more people. A whole other conversation to be had about what remote or distributed work means for me and my family at this time in my life. It's a wonderful, like, being able to work this way at this stage is very meaningful for me and my family, but another time and a place wouldn't make as much sense. So, that's one thing that I meant when I was talking about a talent renaissance. The other thing I was starting to see, and you spoke to this a moment ago, is that at least in some cases, like most progressive employers thinking more flexibly and creatively about what great talent looks like for roles in their organisation. So, hiring from less traditional backgrounds, dropping the traditional degree requirements for most or all jobs. These are some things we were starting to see more commonly that I think are very positive. Positive for businesses because when we think in a more sophisticated way about these things, like we're able to make better matches and have folks that are more capable within our organisations, which means organisations grow more and they win more. It's also good for people. Like, I've hired folks under the people team here at Zapier into their first tech jobs. It's probably 35%, 40% of the people team at Zapier. Zapier is their first software company. But to do that, our people leadership team, like, we've got to have sharp thinking. What are we really looking for here? And kind of getting away from, like, specific degrees or I'm only gonna recruit from these five companies, those shortcuts exist for a reason, if that makes sense. Like, I understand why these are typical ways of hiring into a company. But for teams that are able to get a little more specific about what they're really looking for and really thoughtful about how to see that in between the lines of someone's resume or LinkedIn profile, we will be able to find and attract talent that a lot of other companies are missing. I think that's one of the few talent advantages to be had these days. So that was before Gen AI, certainly in the time since, like, you and I have talked about within both of our organisations, examples of how folks are levelling up what they're capable of in ways that are really good for their performance at the company, but also really meaningful for them personally. And you could just add that as, like, the most recent coat of paint on this notion of talent renaissance.
[00:27:29] Naomi: So interesting. I think what you call the Renaissance, I call it the social contract. And what's interesting to me, I was just sort of reflecting as you were answering, I feel like as an industry, the tech industry has come full circle. Because I entered the tech industry 25, 27 years ago, and I have an English degree. I have no technical qualifications, I have no HR qualifications, and yet, I've built a career in these organisations, and I love them, and love my career, and love my job. And we went through this moment where it was, right now, everyone's got to have a marketing degree or some kind of relevant degree, whatever that looks like. And we've come back out of that now, and the social contract has shifted. And I think, I agree, I think that's eminently possible because that degree of optionality is something that is very native to a tech organisation. It feels very natural to a tech organization who we've just kind of grown up with this stuff, and allowing that optionality to continue just feels more natural somehow to where these organisations come from.
[00:28:36] Brandon: I think that's right, Naomi. I think it's kind of in the DNA part of what I get curious about. You know, I grew up in the American Midwest right outside of Detroit, where, you know, I like to joke when I go home, like I will in a couple of weeks for the winter holidays, they're like real companies, real jobs. We're talking about, like, auto parts suppliers, obviously, kind of the big three American automakers in and around Detroit and so on. It's like real companies, real jobs. And I get really curious about how some of the things that we've seen in tech, some of these new ways of working, thinking more flexibly about how to match and develop talent. Maybe it's the next act in my career, one day is thinking about how to bridge some of these possibilities and practices from software into a much bigger fraction of companies and types of work.
[00:29:20] Naomi: Interesting. We could go deep on blue-collar working and the class system, couldn't we? Off the back of that, let's talk a bit about performance and how you think about the quality of the output of people in your organisation. Is AI changing how you think about the performance of your people, and how is the way in which you measure performance changing? I know it might be interesting to hear about the AI Copilot plans, for example, is what I was thinking here.
[00:29:48] Brandon: That would be a great example. Yeah. Let's go there. So, what do I have to say? Maybe it's provocative. I don't know. Maybe you can tell me, Naomi. We are not planning to update how we evaluate our team members' performance based on their adoption of AI. Here's why. The adoption of AI or the adoption of any technology is a way of achieving high performance. It is not by itself high-performance. And so we have put it on our kind of, like, AI scrum teams inside of each organisation to kind of pioneer and develop new ways of working with AI that can lead to higher performance. And our customer support team, for example, is exactly what they've done over the last 18 months. And that story is probably a good example of what I mean in practice, that a couple of small teams within customer support figure out how AI could help the support team do the job it already has and the performance metrics it already cares about, and how to do that even better, right? In customer support, classically, it's typically something around how quickly can you solve a customer's problem, and how well can you solve the customer's problem? Same thing at Zapier. And sure enough, these small teams that were wayfinding, they went out onto the horizon, they did find some new ways of working with AI that measurably improved speed and quality, and so with that new standard in place or new way of working, they then did a retooling and retraining period across the whole global support team. And only then did Lauren, our customer support exec, raise the bar for performance expectations. This is like we have seen what is now possible, and we have invested in making sure we can all perform at that level. Now that is the new performance standard. And so the customer support team at Zapier today is not performance managed or evaluated on their adoption of the new ways of working. They are performance managed on the new expectation, along with the two KPIs they have always been accountable to. Now, this is part of where we also put the burden on leadership for the change management. If we do an even halfway decent job of explaining not just the benefits to the business or to the customer of the new way of working, but also how it results in a better job for people, which, by the way, efficiency, quality, employee experience, there's the employee experience part of the framework again, folks are going to adopt that new way of working. And I guess, technically, if we don't require it. If, technically, you can meet the new performance standard, if you wanna work twenty more hours a week and not use the new way of working because you're a glutton for punishment, or we know whatever the case may be, then that is technically allowable. We just don't see it.
[00:32:14] Naomi: Yeah. Why would you?
[00:32:15] Brandon: Right. And why would you? So, that's kind of and the same thing is actually true for some of our other, you know, we take a more market-based approach to a lot of our new AI ways of working, whether it's using AI Copilot to help actually, ironically, help craft performance reviews or aggregate performance evidence so you have a more holistic base of facts on which to self evaluate or to evaluate a direct report. We're really interested in the adoption rates for these. We may standardise to them at some point in the future, but for now, we wanna see both how high quality is the new way of working, and how well we communicate its benefits to the individual, such that folks will choose to pull it off the shelf and use it. And a really important piece of learning that we jump right over it if we say, this is the way we do this now, you must use this AI assistant for this particular use case.
[00:33:02] Naomi: I think we're doing the same thing, whereby we're leading with enablement to facilitate people's enthusiasm, and that then sort of does the job of AI adoption for you. You don't need to force it on people because they understand for themselves the benefit of the adoption, and they get to experience that very directly, and then the choice is it's no choice at all, right?
[00:33:25] Brandon: I think you nailed it. And so to put a bow on how we think about it, we don't performance manage folks to the adoption of AI, we performance manage folks to actual business outcomes. We are very curious about adoption on the less, so we measure it. The adoption rate of core AI tooling, adoption of new ways of working with AI, we're very curious about that because that's a key way we can learn what makes the difference between folks who are early adopters versus later adopters? The difference between folks who adopt and maybe the few that don't, what can we learn there? Really useful learning opportunity. We just don't consider that, like, an explicit aspect of individual performance, the adoption piece.
[00:34:01] Naomi: Nice. Super interesting. I like how you frame that. So, AI is embedded in your workflows. It's embedded in all of our workflows increasingly, but particularly at Zapier. So, I'm gonna go at it from a slightly different angle. What human skills do you think will grow in importance over the next decade as this sort of thing happens, and how should we think about nurturing those human skills?
[00:34:21] Brandon: I know from what you just shared a moment ago that not only do you and I come from nontraditional backgrounds into HR, but we were both liberal arts majors at the university. And so I lead off there to acknowledge some liberal arts graduate bias. But I don't think we're the only two people who would argue that the answer to that question is kind of what's old is new again. These, like, broad-based critical thinking skills, like, a lot of this right now when things are changing quickly, it is answers to some of the questions where we need to be asking, are gonna be hard to come by, but they're only possible to answer if we ask good questions, right? So, that is the first thing you made me think about, is, like, what do we look for when we're interviewing folks? By the way, interestingly, we now assess AI fluency for all candidates for all jobs at the company. And if you look at Zapier's AI fluency framework, which maybe we can put in the show notes, family, you will find that it is not all, quote-unquote, AI technical skills or hard skills. It's not all prompting and things like that. And there are two reasons. One, a lot of these methodologies around how you use or build with AI, they're changing quickly, quickly, quickly, quickly. Two, they're not the only thing we mean when we say AI fluency. You know, again, AI is a means to an end; it's not the end itself. And if we believe that, then a reasonable fraction of what we should be looking for when we're talking about AI fluency, what does it mean to actually get impact with AI is, well, how do you know the difference between a problem worth solving with AI and one that maybe isn't, like, top three things you should be rebuilding with AI at the moment? So, just being able to circle an opportunity to understand the shape of it. The other thing that still matters today, practically speaking, is craft. For example, we could put our most talented AI builder from our solutions architecture team here at Zapier back on the people team working with that recruiting operations team we were talking about earlier. Their ramp-up time to be able to be helpful to that team and their co-build of the referral process and the referencing process, it's gonna take them some time because they have these incredible builder skills, highly technical in that sense, but they don't deeply understand the workflows being redesigned.
[00:36:31] Naomi: So that sort of empathy, which I would argue as well to your point about being a liberal arts major, it's like, you know, people ask me how you develop empathy. And it's like you read books and you read fiction, essentially. Because if you wanna understand how other people think, that's where you learn it. And I think that empathy and curiosity, as you say, are absolutely critical skills. But also, as you were talking about, that ability to discern and make judgment calls is incredibly important. Big up for the liberal arts majors amongst us. I'm gonna ask you now a series of more sort of rapid-fire questions. So, what's one people strategy myth you wish every leader would stop believing?
[00:37:16] Brandon: I don't think that employee experience is its own, like, team function or role. I think employee experience is, like, a thing you design for and deliver with everything you do in the people organisation.
[00:37:29] Naomi: Amazing. Wanna go deeper on that. What's one belief about culture that has guided you throughout your entire career?
[00:37:38] Brandon: To quote the title of a book that I think describes this really well, what you do is who you are, not what you say.
[00:37:44] Naomi: Actions, they count. And maybe this is the same answer. What's a small leadership behaviour that instantly boosts performance culture?
[00:37:53] Brandon: Being able to say, I don't know or we don't know yet. Let's go find out.
[00:37:57] Naomi: Yeah. And what's one thing AI can do brilliantly at work and one thing it should never try to replace?
[00:38:05] Brandon: I find AI to be a pretty brilliant coach, especially when the type of coaching I want must take into account, like, huge bodies of work. So, Naomi, you and I were talking earlier, speaking of podcasts, right? It's like I've been doing a lot of podcasts, and articles, and interviews, written interviews this year. One of my pre-holiday projects is to put that all into one data repository and then put a pretty lightweight coaching layer on top of it. This is very hard for humans to do. If I ask someone who is otherwise a brilliant human coach to give me a bunch of, like, very specific with examples, like, summative feedback on all of the external-facing speaking I've been doing this year, it just kind of breaks our brain. It's very hard for humans to do. This is an AI superpower. So, that's one thing I think it's unusually good at. One thing I would never ask AI to do, I would not ask AI to stand in for me in, like, a moment that matters with anyone in my work life or my family life. I do use AI to help me get ready for some of those conversations, but I think for me, that's a bright line is to do the substitute in. I think part of what makes these human moments matter is that people appreciate that some of those conversations or moments are difficult, and they see you kind of in the arena even though it's uncomfortable and difficult, and they see you there anyway because you care, and that, I want to say to them.
[00:39:24] Naomi: I love that. And I think, actually, we've got to be careful with AI that we don't become gloss, that these moments of imperfection, it’s like human. And I think these moments of imperfection really are what make us human and make us relatable to each other. And so if you could give one piece of advice to leaders trying to build these sorts of terrific, high-scale, high-growth, superpowered, but human workplaces in the age of AI, what would that advice be?
[00:39:58] Brandon: The number one thing I can say is that all of us, our organisation's number one thing, still needs to be the number one thing. Our organisations have missions. We have end users, students, customers, whoever that we wake up to serve every day. AI cannot shake us off that foundation. AI might be a way to take a big step forward towards that mission. So, my biggest encouragement for all of us is the number one thing is still the number one thing, and then my encouragement for leaders, like a leader behavior, would be to get hands on keyboard, to be able to ask our teams to think about new ways of working, to achieving our organisation's missions with whatever the case may be, new technology, new market, whatever the with them may be. We need to model that wayfinding that we're asking of our teams and do it in public, where folks can see us, including falling on our faces and whatever the case may be. That's human.
[00:40:50] Naomi: Yeah. And I think that a couple of weeks ago, you did your public all-hands, and you had something insane, like 10,000 people sign up for it. Like, you must have been like, oh my God.
[00:41:01] Brandon: That was more public than we were anticipating, but I was glad to see that it was a timely topic. Goodness.
[00:41:05] Naomi: But it's brilliant, and it's brave. And I think that that is really to be celebrated. I think those moments of boldness are really quite powerful, and people love to see it, obviously, 10,000 people thought so. So, we're almost there, and so take us home with what ultimately gives you optimism about the relationship between people and technology?
[00:41:25] Brandon: With AI specifically, something that gives me optimism, like, above and beyond other tech transformations, is that AI is the first technology I have ever used deeply where one of the best ways to learn it is to use it. And that gives me a lot of optimism as it relates to who AI can be for and who it can help, from just the accessibility and inclusion point of view.
[00:41:47] Naomi: I love that. Thank you, Brandon. That has been so illuminating. I knew from our previous conversations that you would have some wise things to say, and I just really enjoyed how much you shared about how AI is really an enabler, which I think will help. It helps me think about how we overcome that fear that is inevitable in the face of, really, a tidal wave of technology. So, thank you for sharing. Thank you for being so open, and I hope you have a great day.
[00:42:15] Brandon: This is great, Naomi. Thank you.
[00:42:18] Outro: The Future is Human is brought to you by Mews, the cloud-based hospitality platform. If you want to learn more about what we do, visit mews.com. And if you'd like to listen to more conversations like this one, find us on Apple Podcasts, Spotify, YouTube, or wherever you listen. Subscribe so you don't miss future episodes. Thanks for listening.
