Atlassian Team '26 | Alicia Lenart, Atlassian

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More from Atlassian Team '26

Alicia Lenart

VP of HR

Atlassian

play_circle_outline HR at the Helm: Leading the People-Centered Cultural Shift in the Age of AI

play_circle_outline NORA: Three Non-Coders Built an Onboarding Agent That Answered 19,000+ Questions, Saved 2,000+ Hours and Boosted AI Adoption

play_circle_outline Atlassian Rejects AI Mandates, Encourages Bottom-Up Experimentation and Revamps Recognition for AI-Driven Work

play_circle_outline Builder culture democratizes AI; ShipIt drove non-technical participation

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Alicia Lenart, Atlassian

Alicia Lenart

VP of HR Atlassian

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>> Welcome to Atlassian Team '26. We are streaming live here in Anaheim. I'm Alison Kosik alongside Christophe Bertrand, and we've got HR in the house.

>> I don't know. What did we do wrong?

>> No, we're about to find out. I want to bring in our guest. Our guest is Alicia Lenart. She's the head of HR Business Partners with Atlassian. Welcome to theCUBE.

>> Thank you so much. Thanks for having me.

>> We're really not afraid of you, I swear. We do, however, want to talk about AI, which can be seen differently by whoever is judging AI at this point. And everybody's talking about AI as a technology shift. You're framing it as a cultural one, and I'm curious, what does that change in how Atlassian approaches it?

>> Yeah, and I think it's a really key thing that we are trying to do differently because AI does have a lot of fear attached to it. And really, I think the technology has gone really far, but what's holding a lot of organizations back is the cultural transformation that has to go alongside it. And at Atlassian, we firmly believe that AI is a cultural transformation or a people transformation, and the HR team is sitting at the start of that. And then secondary, it's the technology transformation. So both have to go hand in hand if you want to drive or harness what AI is really going to give you.

>> Right. It's interesting because you wouldn't think of HR as being really technology driven, but you think about it, it always has been company records, employees, payrolls, et cetera, but now it's changing. Now, it's making every individual more in charge of their career, more in charge of what they can do next. How have you implemented... Give us an example maybe of an implementation of AI that you as the head of HR have been able to implement at Atlassian.

>> So I think our number one AI use case that we have implemented is around onboarding. So every company onboards staff. And when you think about onboarding as a non-HR person, you think it cannot be that difficult. But really, it is one of the most complex things you have to do. There are so many departments which are involved. You've got finance and setting up payroll, you've got the legal team, the contract, you've got the IT team, you've got the HR team. And also, that information lives everywhere as well. So we went about six months ago on a journey to identify or infuse AI in our onboarding process. And one of the things that we did was we built an onboarding agent called NORA, which stands for New Atlassian Onboarding Rover Agent. And I think the coolest thing about that was it was three folks in our people team, who have never coded in their life, built this agent on their own. It took them two weeks. And now what we have done is this agent is deployed to every new starter at Atlassian, and it has answered over 19,000 questions for our employees. And it's answered questions all the way from, "Hey, when am I going to get paid? Hey, what are my benefits?" to, "What should I wear to the office?" And questions like that are really important for people. And what it's also done is saved our ops team over 2,000 hours. But what I would say the most exciting thing about this agent that we've built is now we set the standard from the start that people should use AI when they get started at Atlassian. And what we saw was AI adoption skyrocket for our employee base. So our folks that are joining Atlassian under this new or using this new onboarding agent are more likely to use AI than our employees who are already in seat.

>> So AI is really becoming a people story, clearly. It's making something like onboarding so much more simpler than it has been in the past. What do you think other companies are getting wrong right now when they think about AI transformation?

>> So I think there's a few things that we do differently at Atlassian, and maybe that works for our culture, but maybe a few things that work. The first thing is we simply don't believe in AI mandates. I think there's some companies out there mandating their way to AI, and maybe that works for them, but we have a really bottoms-up groundswell culture. And I think staying away from mandates helps get away from that fear. If you have a fear-based culture, then that means people don't want to use AI. So firstly, we stay away from mandates, and there's three key things that we think about. One is, what is the culture you need to build AI? And you got to experiment because AI changes every day, and sometimes you do something and it didn't work and then six months later, it does. So that kind of culture of experimentation is really important. The second thing is leaders have to role model. So they have to walk the talk, and that gets away from that fear base. No employee wants to use AI if they don't see their manager using it because they're like, "Something doesn't seem right here." And then lastly, you got to redesign your recognition framework. So you've got to reward the new way of working. So they're the three things that we do differently that I think have been working for us so far.

>> So let's talk about how it changes the nature of the job description and the average employee, take any function. It seems to me what you're saying now is, well, I'm looking for someone who can and will use AI as part of their job, which is such a different story from even a few years ago when, oh no, you cannot use AI because you're cheating when you're using AI. So tell me about that. How's it changing how you actually hire and how you create job descriptions now? Because I think that has to be a central point for you as the VP of HR.

>> Totally. So what we've been thinking about is how do we make sure that when employees are in the door that they're upskilled in AI. One thing that we don't want to do is not everyone... Most people are using AI for individual productivity in their personal life. Everyone's using ChatGPT to look at the things in their fridge, what should they cook for dinner or whatever it may be. But we haven't yet gone out and, as I said, mandated that we have to test for AI during each of our interview processes. For some crafts, it's very important, so we've done that, but we want to make sure that we don't cut out a segment of the workforce by not doing that. So really, what's important for us is making sure that people showed the skills that they could leverage AI. So learning aptitude, making sure that they've got a growth mindset, making sure that they're engaged, they're the kinds of things that we do use, and then we make sure as we onboard them, that we onboard them to the ways of working and the tools that we use. But I think one other thing I would say is candidates are now asking us in the interview process-

>> Interesting....

>> "What AI tools do you use? How can I expense X AI tool for me? And how do you use it in the processes?" And candidates are actively choosing employers who are using AI. So we're also seeing it on the reverse side as well, which I think is super interesting.

>> That's quite the twist, isn't it?

>> Yes, totally. Totally. And it's something interesting to think about because if you're in the tech space and maybe you're not at the cutting edge or you're trying to be at the cutting edge, it's going to be a reason why employees choose you over someone else as well as we go forward.

>> Yeah, so the behavioral shift isn't just happening with employees there, but it's happening on the outside as well. And it helps that leadership is showing that it is exhibiting-

>> Totally....

>> that AI, it's intrinsic in the system.

>> Exactly. And I think what's really important for leaders as well and something that I always think about is you've also got to be really real with AI. Not everything that it does is perfect. Sometimes you use it and you think, "This isn't something I would go with." And being really open and honest with employees and saying when an AI output comes and saying, "This isn't actually what I expected," or, "This isn't actually up to scratch. Let me go back and try again. Or actually, maybe AI shouldn't be used for that." I think that vulnerability and that being open and transparent about AI is really important. If you're a leader that talks about it, but never uses it, red flag. Or then if you say everything is perfect, also red flag because it's not for everything that it produces.

>> So everybody's becoming a builder. Clearly, you had three of your staff build the onboarding tool, and that's probably just one of the many tools you have in mind. I imagine there are plenty more. It must be interesting internally to see how you're the ones leading. It's coming from HR. It's not coming from engineering or you would imagine a technical team.

>> Exactly.

>> So tell me about the builder culture. What does that mean? We talked about the profile of new employees or employees choosing you because of the use of AI, but build a culture, to me, means you want to be exploring versus following the rules exactly. How do you reconcile that with certain jobs where you cannot need people to follow the rules?

>> Totally. So we definitely have a belief at Atlassian that everyone should build. And I also believe that with AI, we're lessening the gap between technical and non-technical. And as a proud non-technical person who does not have an engineering degree, I think AI should be for everyone. So what you've got to do, though, is you've got to build the environment and you've also got to build the culture and you've got to meet people where they are. Building a course or an upskilling initiative that fits for an engineer will not be fit for a HR person or a finance person. So one of the things that we do do is we have a quarterly innovation event called ShipIt, and we recently hosted that a few weeks ago. And we did a really dedicated push to get our non-technical folks to participate because traditionally our engineers have participated. So what we did see was about people teams, so folks in the HR team, we saw a third of them participate. Last time, we saw less than 1%. So encouraging folks, giving them the tools where they are, telling them it's okay to experiment and fail is what drives that culture of building. We had 20% of our folks in finance participate. And maybe why does all of this matter? Why do we care about being a building culture? Because right now, I think most people or most companies have cracked that individual productivity bit for AI, most people using in their personal lives, but the real magic happens when you unblock team-based workflows like onboarding. And to unblock team-based workflows, you need people who actually do the work at the job level unblocking the workflow. It's not just the engineers, but the people in every team like onboarding. So that's why it's important for everyone to be a builder.

>> So you talk about rewired work. So I'm curious, what's the difference between that and just being more efficient?

>> It's a good question because I think there's a big push with AI that everyone's going to be more efficient. And I think when you start by telling people, "Be more efficient with AI," a lot of people put their hands in the air. 99.9% of people are working as hard as they can, and their manager coming over their shoulder and saying, "Please be more efficient," isn't terribly motivating. I think rewiring work, though, takes a lot of work. You have to get down to the role level. You have to change how the jobs are done, and that requires rewiring workflows. And that's really hard to do and it takes a lot of work. We do have one example at Atlassian where we've rewired work. We have a role called the design technologist. That's a role that sits in the center of the software development lifecycle. So when you're building software, you have a design, you have a product manager, and an engineer. And by leveraging AI in the process, our design technologists can now build faster AI prototypes. Their role is to build a prototype. The team look at it and they think, "Is this something that we would invest in?" And we've seen a 35% month-on-month increase in prototypes that have been built. That's 12,000 prototypes. And the team, look, they are working faster. I will say that. But the best thing about the rewired work is because they can work faster and because the prototypes can be produced more easily, instead of before they would say, there'd be a moonshot idea, they'd say, "We just can't get to that," they're now getting to those moonshot ideas and considering on their merit. So I think that's the magic versus the speed that also comes along with it.

>> Right. As a reformed product person, I have to say, I wish I'd had a team that could do that for me. Lots of features I think we would not have shipped. This being said, let's talk about the elephant in the room. Is AI a friend or a foe? Is AI going to replace people? And that's number one, first part of the question. Second part of the question is, are you now the VP of HR and agents, human and agentic resources?

>> Great question. So taking your first line, is AI a friend or a fo? It is absolutely a friend. And I firmly believe that what the world will look like and what teams will look like in an AI-enabled world will be AI and humans in the loop working together. I think there are going to be very few processes, sure, there'll be some, but I think there's going to be very few processes where they're going to be entirely replaced humans. You're still going to have humans reviewing. You're still going to have humans looking over things. So I truly believe it's a friend. I believe it's an accelerator. And I also believe there's places where AI shouldn't go, but I truly believe it's a friend. On the second thing, is the role now leading team of AI and agents, I think every leader's role is now leading AI and agents. And I actually think that what we're going to see is most individual contributors become managers in the sense that actually they also lead a fleet of agents as well.

>> So let me follow up on that. That's a very important point because I don't think that most people see themselves... A lot of people don't want to be managers. You know that. Certain type of people-

>> Totally....

>> who can't do it or want to do it. But now, everybody has to be a manager to a large extent. Do you think that's really going to work for everybody that they have to be a manager of agents? Or are we going to be looking at agents becoming more like extensions of the individual? And in that sense, you're not really managing. You're just delegating stuff that's easy to delegate.

>> It's totally... I think about the second thing you said because I think the word manager on the way that we have it today means I manage a group of humans. That's not what it's going to be like. So maybe we need to coin a new term or think about it, because individuals will be managing a set of agents. They'll be directing, they'll be using... I think that's more what it is than becoming "what we say a manager." But I think the kind of thing that I want to say here is individuals were used to working on their own doing work. They're now going to be working with a fleet of agents or a number of agents to get their work done. Will they be managing? No, maybe they'll be orchestrating. Maybe it's the choice of word that will be there, because I agree with you. Some people quiver in their boots to think, "I'm going to be managing. I don't want to do that. Gosh, that's the worst thing I want to do."

>> You did say there are some areas that AI should not go. Can you maybe give us a few of those?

>> Yes. And we've been thinking in the people team about what those should be. And I think when you talk about AI and you talk about the people team and you talk about people data, that is a really high-risk area. And around the folks I speak to in the people team, we're nervous about some places. This is people data. I think there's two places where we feel at Atlassian that AI's not going to go. The first is making hiring decisions. So I definitely think AI will be in the hiring process. So things like it will schedule candidate interviews, things like it will make sure that your write-ups are where they need to be, but I genuinely don't think AI should make a decision about who you bring into an organization because that is a serious decision that you make and I just don't think AI has that judgment. So that's number one. And then the second thing is around performance reviews. So again, I think AI is right at the front of the stack. It's helping you write your peer feedback, it's helping you as a manager look at the rubric, but it's not making that decision about a performance review. So it's really where AI is making the decision about people or performance or hiring, I think it's firmly a people thing to do.

>> Maybe one last question on the topic of compliance. The other risk is, of course, people using AI to start looking at potentially employee data they should not access, financial data, et cetera. It feels to me like right now it's a bit of a Wild West situation and not everything is nicely siloed the way it should be. So there is a compliance issue. From your standpoint, what are you doing specifically to avoid non-compliance, to really put those sort of limits around what can be done?

>> It's a good question. I think having a really strong governance framework is number one importance. And I think with people data, you've got to err on the side of caution. So generally with AI, I'm like, "Go build, go try all the things." But with people data, you've got to err on the side of caution. And then I think the thing we've been doing at Atlassian, one, we have a responsible AI framework and a responsible AI committee that meets, because the thing is everything is changing so fast and maybe something that was okay a few months ago isn't, or maybe something that isn't was, and making sure you're constantly meeting as a group. And that group has folks from the HR team, it has folks from legal, it has folks from compliance, and making sure that you're keeping that front and center and always talking is the way to go, in my opinion.

>> Thanks so much for your time and stopping by theCUBE.

>> Thank you so much.

>> Loved this conversation.

>> Thank you so much. Great to chat with you.

>> Thanks. And you've been watching theCUBE, the leader in live technology coverage and enterprise technology analysis. We'll be right back.

Alicia Lenart, Atlassian

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>> Welcome to Atlassian Team '26. We are streaming live here in Anaheim. I'm Alison Kosik alongside Christophe Bertrand, and we've got HR in the house.

>> I don't know. What did we do wrong?

>> No, we're about to find out. I want to bring in our guest. Our guest is Alicia Lenart. She's the head of HR Business Partners with Atlassian. Welcome to theCUBE.

>> Thank you so much. Thanks for having me.

>> We're really not afraid of you, I swear. We do, however, want to talk about AI, which can be seen differently by whoever is judging AI at this point. And everybody's talking about AI as a technology shift. You're framing it as a cultural one, and I'm curious, what does that change in how Atlassian approaches it?

>> Yeah, and I think it's a really key thing that we are trying to do differently because AI does have a lot of fear attached to it. And really, I think the technology has gone really far, but what's holding a lot of organizations back is the cultural transformation that has to go alongside it. And at Atlassian, we firmly believe that AI is a cultural transformation or a people transformation, and the HR team is sitting at the start of that. And then secondary, it's the technology transformation. So both have to go hand in hand if you want to drive or harness what AI is really going to give you.

>> Right. It's interesting because you wouldn't think of HR as being really technology driven, but you think about it, it always has been company records, employees, payrolls, et cetera, but now it's changing. Now, it's making every individual more in charge of their career, more in charge of what they can do next. How have you implemented... Give us an example maybe of an implementation of AI that you as the head of HR have been able to implement at Atlassian.

>> So I think our number one AI use case that we have implemented is around onboarding. So every company onboards staff. And when you think about onboarding as a non-HR person, you think it cannot be that difficult. But really, it is one of the most complex things you have to do. There are so many departments which are involved. You've got finance and setting up payroll, you've got the legal team, the contract, you've got the IT team, you've got the HR team. And also, that information lives everywhere as well. So we went about six months ago on a journey to identify or infuse AI in our onboarding process. And one of the things that we did was we built an onboarding agent called NORA, which stands for New Atlassian Onboarding Rover Agent. And I think the coolest thing about that was it was three folks in our people team, who have never coded in their life, built this agent on their own. It took them two weeks. And now what we have done is this agent is deployed to every new starter at Atlassian, and it has answered over 19,000 questions for our employees. And it's answered questions all the way from, "Hey, when am I going to get paid? Hey, what are my benefits?" to, "What should I wear to the office?" And questions like that are really important for people. And what it's also done is saved our ops team over 2,000 hours. But what I would say the most exciting thing about this agent that we've built is now we set the standard from the start that people should use AI when they get started at Atlassian. And what we saw was AI adoption skyrocket for our employee base. So our folks that are joining Atlassian under this new or using this new onboarding agent are more likely to use AI than our employees who are already in seat.

>> So AI is really becoming a people story, clearly. It's making something like onboarding so much more simpler than it has been in the past. What do you think other companies are getting wrong right now when they think about AI transformation?

>> So I think there's a few things that we do differently at Atlassian, and maybe that works for our culture, but maybe a few things that work. The first thing is we simply don't believe in AI mandates. I think there's some companies out there mandating their way to AI, and maybe that works for them, but we have a really bottoms-up groundswell culture. And I think staying away from mandates helps get away from that fear. If you have a fear-based culture, then that means people don't want to use AI. So firstly, we stay away from mandates, and there's three key things that we think about. One is, what is the culture you need to build AI? And you got to experiment because AI changes every day, and sometimes you do something and it didn't work and then six months later, it does. So that kind of culture of experimentation is really important. The second thing is leaders have to role model. So they have to walk the talk, and that gets away from that fear base. No employee wants to use AI if they don't see their manager using it because they're like, "Something doesn't seem right here." And then lastly, you got to redesign your recognition framework. So you've got to reward the new way of working. So they're the three things that we do differently that I think have been working for us so far.

>> So let's talk about how it changes the nature of the job description and the average employee, take any function. It seems to me what you're saying now is, well, I'm looking for someone who can and will use AI as part of their job, which is such a different story from even a few years ago when, oh no, you cannot use AI because you're cheating when you're using AI. So tell me about that. How's it changing how you actually hire and how you create job descriptions now? Because I think that has to be a central point for you as the VP of HR.

>> Totally. So what we've been thinking about is how do we make sure that when employees are in the door that they're upskilled in AI. One thing that we don't want to do is not everyone... Most people are using AI for individual productivity in their personal life. Everyone's using ChatGPT to look at the things in their fridge, what should they cook for dinner or whatever it may be. But we haven't yet gone out and, as I said, mandated that we have to test for AI during each of our interview processes. For some crafts, it's very important, so we've done that, but we want to make sure that we don't cut out a segment of the workforce by not doing that. So really, what's important for us is making sure that people showed the skills that they could leverage AI. So learning aptitude, making sure that they've got a growth mindset, making sure that they're engaged, they're the kinds of things that we do use, and then we make sure as we onboard them, that we onboard them to the ways of working and the tools that we use. But I think one other thing I would say is candidates are now asking us in the interview process-

>> Interesting....

>> "What AI tools do you use? How can I expense X AI tool for me? And how do you use it in the processes?" And candidates are actively choosing employers who are using AI. So we're also seeing it on the reverse side as well, which I think is super interesting.

>> That's quite the twist, isn't it?

>> Yes, totally. Totally. And it's something interesting to think about because if you're in the tech space and maybe you're not at the cutting edge or you're trying to be at the cutting edge, it's going to be a reason why employees choose you over someone else as well as we go forward.

>> Yeah, so the behavioral shift isn't just happening with employees there, but it's happening on the outside as well. And it helps that leadership is showing that it is exhibiting-

>> Totally....

>> that AI, it's intrinsic in the system.

>> Exactly. And I think what's really important for leaders as well and something that I always think about is you've also got to be really real with AI. Not everything that it does is perfect. Sometimes you use it and you think, "This isn't something I would go with." And being really open and honest with employees and saying when an AI output comes and saying, "This isn't actually what I expected," or, "This isn't actually up to scratch. Let me go back and try again. Or actually, maybe AI shouldn't be used for that." I think that vulnerability and that being open and transparent about AI is really important. If you're a leader that talks about it, but never uses it, red flag. Or then if you say everything is perfect, also red flag because it's not for everything that it produces.

>> So everybody's becoming a builder. Clearly, you had three of your staff build the onboarding tool, and that's probably just one of the many tools you have in mind. I imagine there are plenty more. It must be interesting internally to see how you're the ones leading. It's coming from HR. It's not coming from engineering or you would imagine a technical team.

>> Exactly.

>> So tell me about the builder culture. What does that mean? We talked about the profile of new employees or employees choosing you because of the use of AI, but build a culture, to me, means you want to be exploring versus following the rules exactly. How do you reconcile that with certain jobs where you cannot need people to follow the rules?

>> Totally. So we definitely have a belief at Atlassian that everyone should build. And I also believe that with AI, we're lessening the gap between technical and non-technical. And as a proud non-technical person who does not have an engineering degree, I think AI should be for everyone. So what you've got to do, though, is you've got to build the environment and you've also got to build the culture and you've got to meet people where they are. Building a course or an upskilling initiative that fits for an engineer will not be fit for a HR person or a finance person. So one of the things that we do do is we have a quarterly innovation event called ShipIt, and we recently hosted that a few weeks ago. And we did a really dedicated push to get our non-technical folks to participate because traditionally our engineers have participated. So what we did see was about people teams, so folks in the HR team, we saw a third of them participate. Last time, we saw less than 1%. So encouraging folks, giving them the tools where they are, telling them it's okay to experiment and fail is what drives that culture of building. We had 20% of our folks in finance participate. And maybe why does all of this matter? Why do we care about being a building culture? Because right now, I think most people or most companies have cracked that individual productivity bit for AI, most people using in their personal lives, but the real magic happens when you unblock team-based workflows like onboarding. And to unblock team-based workflows, you need people who actually do the work at the job level unblocking the workflow. It's not just the engineers, but the people in every team like onboarding. So that's why it's important for everyone to be a builder.

>> So you talk about rewired work. So I'm curious, what's the difference between that and just being more efficient?

>> It's a good question because I think there's a big push with AI that everyone's going to be more efficient. And I think when you start by telling people, "Be more efficient with AI," a lot of people put their hands in the air. 99.9% of people are working as hard as they can, and their manager coming over their shoulder and saying, "Please be more efficient," isn't terribly motivating. I think rewiring work, though, takes a lot of work. You have to get down to the role level. You have to change how the jobs are done, and that requires rewiring workflows. And that's really hard to do and it takes a lot of work. We do have one example at Atlassian where we've rewired work. We have a role called the design technologist. That's a role that sits in the center of the software development lifecycle. So when you're building software, you have a design, you have a product manager, and an engineer. And by leveraging AI in the process, our design technologists can now build faster AI prototypes. Their role is to build a prototype. The team look at it and they think, "Is this something that we would invest in?" And we've seen a 35% month-on-month increase in prototypes that have been built. That's 12,000 prototypes. And the team, look, they are working faster. I will say that. But the best thing about the rewired work is because they can work faster and because the prototypes can be produced more easily, instead of before they would say, there'd be a moonshot idea, they'd say, "We just can't get to that," they're now getting to those moonshot ideas and considering on their merit. So I think that's the magic versus the speed that also comes along with it.

>> Right. As a reformed product person, I have to say, I wish I'd had a team that could do that for me. Lots of features I think we would not have shipped. This being said, let's talk about the elephant in the room. Is AI a friend or a foe? Is AI going to replace people? And that's number one, first part of the question. Second part of the question is, are you now the VP of HR and agents, human and agentic resources?

>> Great question. So taking your first line, is AI a friend or a fo? It is absolutely a friend. And I firmly believe that what the world will look like and what teams will look like in an AI-enabled world will be AI and humans in the loop working together. I think there are going to be very few processes, sure, there'll be some, but I think there's going to be very few processes where they're going to be entirely replaced humans. You're still going to have humans reviewing. You're still going to have humans looking over things. So I truly believe it's a friend. I believe it's an accelerator. And I also believe there's places where AI shouldn't go, but I truly believe it's a friend. On the second thing, is the role now leading team of AI and agents, I think every leader's role is now leading AI and agents. And I actually think that what we're going to see is most individual contributors become managers in the sense that actually they also lead a fleet of agents as well.

>> So let me follow up on that. That's a very important point because I don't think that most people see themselves... A lot of people don't want to be managers. You know that. Certain type of people-

>> Totally....

>> who can't do it or want to do it. But now, everybody has to be a manager to a large extent. Do you think that's really going to work for everybody that they have to be a manager of agents? Or are we going to be looking at agents becoming more like extensions of the individual? And in that sense, you're not really managing. You're just delegating stuff that's easy to delegate.

>> It's totally... I think about the second thing you said because I think the word manager on the way that we have it today means I manage a group of humans. That's not what it's going to be like. So maybe we need to coin a new term or think about it, because individuals will be managing a set of agents. They'll be directing, they'll be using... I think that's more what it is than becoming "what we say a manager." But I think the kind of thing that I want to say here is individuals were used to working on their own doing work. They're now going to be working with a fleet of agents or a number of agents to get their work done. Will they be managing? No, maybe they'll be orchestrating. Maybe it's the choice of word that will be there, because I agree with you. Some people quiver in their boots to think, "I'm going to be managing. I don't want to do that. Gosh, that's the worst thing I want to do."

>> You did say there are some areas that AI should not go. Can you maybe give us a few of those?

>> Yes. And we've been thinking in the people team about what those should be. And I think when you talk about AI and you talk about the people team and you talk about people data, that is a really high-risk area. And around the folks I speak to in the people team, we're nervous about some places. This is people data. I think there's two places where we feel at Atlassian that AI's not going to go. The first is making hiring decisions. So I definitely think AI will be in the hiring process. So things like it will schedule candidate interviews, things like it will make sure that your write-ups are where they need to be, but I genuinely don't think AI should make a decision about who you bring into an organization because that is a serious decision that you make and I just don't think AI has that judgment. So that's number one. And then the second thing is around performance reviews. So again, I think AI is right at the front of the stack. It's helping you write your peer feedback, it's helping you as a manager look at the rubric, but it's not making that decision about a performance review. So it's really where AI is making the decision about people or performance or hiring, I think it's firmly a people thing to do.

>> Maybe one last question on the topic of compliance. The other risk is, of course, people using AI to start looking at potentially employee data they should not access, financial data, et cetera. It feels to me like right now it's a bit of a Wild West situation and not everything is nicely siloed the way it should be. So there is a compliance issue. From your standpoint, what are you doing specifically to avoid non-compliance, to really put those sort of limits around what can be done?

>> It's a good question. I think having a really strong governance framework is number one importance. And I think with people data, you've got to err on the side of caution. So generally with AI, I'm like, "Go build, go try all the things." But with people data, you've got to err on the side of caution. And then I think the thing we've been doing at Atlassian, one, we have a responsible AI framework and a responsible AI committee that meets, because the thing is everything is changing so fast and maybe something that was okay a few months ago isn't, or maybe something that isn't was, and making sure you're constantly meeting as a group. And that group has folks from the HR team, it has folks from legal, it has folks from compliance, and making sure that you're keeping that front and center and always talking is the way to go, in my opinion.

>> Thanks so much for your time and stopping by theCUBE.

>> Thank you so much.

>> Loved this conversation.

>> Thank you so much. Great to chat with you.

>> Thanks. And you've been watching theCUBE, the leader in live technology coverage and enterprise technology analysis. We'll be right back.