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HR Voices is a scenario-based podcast for People Leaders who’ve actually had to make the call.
Each episode brings experienced HR and People leaders into realistic, anonymized workplace scenarios—the kind you recognize immediately. Performance issues. Messy conflicts. Investigations that don’t fit neatly into a policy box. Instead of talking about their own companies, guests react to outside cases and walk through how they’d think it through in real time.
There are no right answers here. What you’ll hear is judgment: how seasoned leaders balance risk, fairness, legal reality, and humanity when the stakes are high and the path isn’t obvious.
HR Voices is for HR, People Ops, legal, and leaders who want to hear how other smart humans actually handle employee relations—without confidentiality breaches, hypotheticals that feel fake, or a lecture on “best practices.”
riverside_melissa,_weston, gabri..._hr_voices studio
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[00:00:00] Welcome to HR Voices, a podcast where people leaders share their side of the story. We talk about the challenges they're facing, how they're addressing them, and what changes they hope to see as the workplace evolves. This podcast is sponsored by AllVoices, the all-in-one employee relations platform.
Hello, and welcome to HR Voices. I'm your host, Rebecca Taylor, and I'm here for the first time with two guests. Today, I'm joined by Gabrielle Caron, the VP of Talent, Culture, and Growth, and Weston Fillman, the Director, Head of People Operations and Employee Relations at 1Password. Gab and Wes, welcome.
Thank you. Thanks for having us. Yes. Thank you both so much for being here, and thank you for being game to have this conversation together 'cause I think this is like, these conversations are always kind of like very nuanced. I know if you're listening, you haven't heard our scenario yet, so we're gonna get into it in a moment.
But I love the fact that, you know, we're kind of all coming about this from maybe some of the same stances of agreement, but I think when we were prepping, we also [00:01:00] had like maybe some sort of areas where we disagreed a little bit. So I think this will be kind of fun to sort of like chat through what we're going for here.
So it's a looser, more conven- more like less con- uh, conventional episode, a little bit more conversational than our standard format. So for those who are listening, get ready to buckle up 'cause I think this is gonna be really, really fun. So are we really... Are we ready for our scenario? Yes, we are.
Yeah. Okay. Well, 'cause you two picked it, so I think it's also important to note. Well, it's a bit of the topic of the hour, so... It is a topic of the hour. And so this is actually... It is a real story that's been making the rounds. So sometimes we do fabricated scenarios, sometimes we do real-life ones, but today we're doing a real-life one.
So you two shared a Business Insider article with me that has Meta making headlines for firing employees who are faking keyboard activity to appear productive while working remotely. So I'd love to use that as a jumping-off point to talk about employee monitoring, trust, and like what leadership actually looks like when the pressure's on.
And if you're listening to this, we'll make sure to [00:02:00] include a link to the original Business Insider article in the show notes so you can read it. But, as we kind of start to open up this conversation, you know, we're talking employee monitoring, we're talking employees, sort of working for the system, less for the output sometimes.
But before we dive into all that, what stands out to you as the most risky or most unclear when you first read this article? Gab, I'm gonna tap you first. Yeah, you're tapping me first? Okay. Well, actually, what struck me first is just the, to what extent that is a bit of the dilemma of the hour, and also to what extent it speaks to a reality that we're seeing at the moment.
There's a ton of anxiety in the mo- in the market of understanding what, who is using AI, who is using AI well, who is being most productive, who is actually working, and, uh, there's a lot of... The market's really competitive at the moment, and so leaders are under a lot of pressure, and sometimes that leads some of them to move very quickly and to choose certain avenues like this one that probably [00:03:00] had good intent, but debatable on the execution.
And so I actually, before it raised any risk for me, I did have a lot of empathy for a lot of leaders that potential- that were involved in that decision. And so I-- Weston can probably speak better to the risk that spoke to him, but if I had to s- to, to say my first reaction, it was really that. It was like, wow, when you get to the point where you have to make this kind of decision and you make it in that way, there was a lot of dynamics at work, uh, and at play.
Yeah. Yeah. When I think about this example, because the tools that are being rolled out, were to track keystrokes and mouse movements and, you know, screen activity to train an AI model, I think, with the lack of communication or communication breakdown with the why, you know, that's to me kind of what stood out the most.
Because inherently it's not maybe the wrong thing for an AI company to, to, to do, but, but if it's not communicated in the right way, it's, you just lose employee trust, you know? And that's, you know, the mandatory participation and no opt-out with this immediate perception gap, I just think [00:04:00] really just blurs l- you know, leadership intent and, and then employee experience.
I know, as a, as a people manager, folks on my team would be really concerned, you know, about that, you know, ri-rightfully so, you know? And if I didn't have the way to communicate, you know, the why behind it transparently, I know that would, you know, cause a huge loss of trust, you know, between my teams and myself.
And I do- That's the first thing that I thought of. Go ahead, Gab. And I will add for, for, and I will add for just for us, when you think of, like, the potential of losing trust, that becomes very scary, especially for a privacy and security company. Trust is, one, it's just how we like to lead here at 1Password, but it's also just critical.
That is the, the foundation of our, our product, and so obviously that also comes to mind. Then when I hear something like, when I hear Weston share his perspective on it, I'm like, yeah, that's something that we would definitely wanna stay, make sure we do very thoughtfully, Yeah. Yeah, I always like hear these kinds of announcements, and I always think of them.
I react to them first as like this outsider who's like, "Well, I don't work there," so you know, here's sort of the perspective of someone who's not in the thick of [00:05:00] it, right, and can have so many more opinions than those that are kind of s- maybe stuck with it, right? But then I immediately go to what would be my reaction if I were an employee versus an HR person?
'Cause I come from HR myself too, and so many times I've had to, institute policy changes or things that I didn't necessarily agree with for so many different reasons, but I'm stuck doing. So it's like, you know, I'm curious for each of you, did your reaction change depending on whether you thought as like a leader who might have to own this change versus an employee who this change is happening to?
N- recognizing that even as a leader, you're also an employee who this is happening to. I go very quickly. I definitely wear that hat all the time, right? Like, and I think that's how I look at this because I know that, how I would feel, you know, if I was a, a Meta employee, as a former person that has worked there.
You know, I know how I would feel with, with that rollout. Like, you know, but then putting on my HR hat, you know, like I would definitely feel, differently, you know, if I were, you know, if I were in, you know, in charge of implementing this on my team. And I, and [00:06:00] as I've approached the conversation around AI with a lot of my, um, direct and indirect reports, you know, I've centered on like I understand some of your concerns about the usage of AI, just in general, right?
The environmental impact, the social impact, the, you know, what this means for the future. So I've tried to acknowledge that 'cause I do share some of those anxieties with them. But then also, you know, thoughtfully acknowledging, okay, well, what are the ways that, our work can change for s- so much better as HR folks, you know, um, you know, with, with using tools.
So I think it's just, you kinda have to have that balance and be able to put yourself in, in both, both spaces. I think it's the only way we can really approach this complex topic that's rapidly evolving and changing the way we work. Yeah, and at the same time, whatever hat you put on, there's pros and cons to each, and I'm someone who like likes to think a lot about all the ways that you could approach and be thinking about certain things.
And so s- in a way, if I think about it as an employee, one, it's really scary. Two- Potentially questionable, because you're like, is this how they actually define my work?" Or like, "How do they actually know [00:07:00] what value I'm bringing, and have they actually put that into consideration as they look at these, these metrics and data points?"
And so it raises questions in the, like, what and how. But then at the same time, I can't help but I guess that that's a bit of the leader's shoe, but to put myself in a different scenario and tell myself, "Wow, if this would've been explained properly, I actually think there's a ton of value if done well, and if, uh, privacy and, you know, i- if the, what they're doing with the information is, is, uh, correct."
I think it could be really inspiring. Like, if we all thought that our LLMs would be trained based on our own context and reality, how much more efficient would that LLM be? How much less bias could we potentially introduce into that LLM? That's inspiring to me. And so it, it depends on how you're, you're thinking about it.
At the same time, when I think of, like, tracking and, like, tools and stuff like that, sometimes we try to explore collaboration. How are people partnering across, especially in the remote world, sometimes we don't do a great job at collaborating across departments. And so when I think of, like, tool tracking and, like, maybe less mouse clicking and stuff, but there's a lot of analysis that could be done with [00:08:00] those types of data points taken from different angles.
And so again, I'm like, "Oh, well, if we wanna encourage more collaboration, that means that that matters to the company, and, and I think we can get better work done and better partnerships, stronger connections." And so I don't wanna sound like someone who's only wearing pink glasses. I know there are poorly-- things that are done with poor intent and done in the wrong way with this kind of stuff, and we hear so much about that these days that I think it's normal that people are scared.
But gosh, what a missed opportunity at the same time. And I think when we were chatting before, I've said this, but, like, those are things that are really hard to recover from for leaders. You know? When you break that trust and when you go forward with these things, it could've been the most amazing and best intended idea and scenario and- It's hard to after that backpedal and be like, "Wait, wait, wait, I actually had such a great idea with this.
Uh, you would have benefited from it." People are just at that point are just gonna be like, yeah. "Are you sure about that?" And, and then good luck, right? I think that's the really hard part too, is kind of just like this could be a good idea if the reason behind the decision is clearly [00:09:00] communicated and done in the time that it takes for people to actually be bought into something, then there could be a lot of potential, right?
'Cause, even in the article it talks about how it-- they're tracking these like keystrokes and mouse clicks specifically to train their AI. So it's like, okay, maybe let's think, let's think of like the positive light, right? Like, maybe they're trying to train AI based on how people actually do interact with different tools, and that's kind of like what they're trying to see here.
But then it also makes me think like, you know when you're going to an airport and you're walking through TSA and they have like the dogs, like the bomb dogs, and they're like, "Walk, just walk at a normal pace and just walk, like don't look at the dog." I'm like, "What's nor- now that I'm being watched, like, what's normal?
Like, how do I walk normally?" Yeah. Right. So it's kind of like when people know, I mean, people know they do need to know if they're being monitored, but once you're being monitored, is what you're getting really authentically how people are using those tools? Or are they keeping themselves just in what they think the expectation is?
'Cause it's like, I don't know, it's like as soon as you realize you're breathing, you forget how to breathe, right? That's an [00:10:00] interesting point. Uh, and one thing Gab has been working on, um, at 1Password has been our like AI, you know, usage, uh, kind of standards across the company. So Gab, I'd love your thought on that.
Yeah. Yeah, because at the same time I'm try- I was trying to think of like how do you teach people- How do you train in general, right? I mean, like- Right ... I think, again, when we were having our conversation before, we were talking about, like, do you remember the good old days when we were all learning HR, and, like, there was one of the learning models was shadowing.
You've got job shadowing, so someone sits ne- Yeah. ... sits next to you and watches you do that job, and that was, like, a real thing, and probably similar feelings, right? The first time you heard somebody was gonna be watching you, you were gonna be like what are they gonna observe?" And is somebody else- Yeah, what are they doing here?
asking them... Yeah, what are they gonna report out on? And, like, and it was uncomfortable. Like, don't get me wrong, having someone sitting next to you, watching your, all your, your moves is not comfortable. And so I can't... I think thinking-- I think you have to think about, like, being very clear about what you're trying to do with this and be mindful of, like, what are all the things that could go [00:11:00] wrong.
What are all the, the in- inaccurate usage of these, uh, of AI tools or inaccurate, uh, data information. I think you think of, like, all the things that could go wrong, all the things that you want to go well, and you kind of have to mitigate for all of those things, think through those things, whether it's through the system usage or the clearly communicating and the guardrails.
And it's again, it goes back to, I guess maybe that's been, uh, something that's helped me be successful in my career is the overthinking, right? Sometimes overthinking's not a good thing, but I think in circumstances like this, when you're going through delicate projects or, or new innovations, to really overthink and think of all the things that could go well, all the things that could go wrong, and really plan for that, making sure that you're building policies around that, building trainings around that, building a communication strategy that goes around that, that as much as possible so that people feel like they've got as many answers as possible.
And when you don't have the answer, you're clear that you don't have the answer, but this is the intent. This is the direction or the guiding principles, you know? Yeah. Mm. I think that's what we try to do as much of. Especially when it's like-- Yeah, and sorry to cut you off, 'cause I, I'm like- Mm-hmm ... I'm excited about what you're saying, 'cause especially when you [00:12:00] think about this is sort of a prime case for overthinking, where it could be overthinking as a benefit, because as HR, you're trying to think about all the different competing pressures, and you're trying to make sure that everybody who's gonna be at all different scales of onboardness are gonna react to kind of like how this is sort of coming through.
And, you know, there's- And you have to assume that your employees might be overthinking this. Mm-hmm. It's a tough market right now for humans. It's a tough- Yeah ... market for humans being employed in non-trade jobs, in jobs that are actively working side by side by the AI. And so oftentimes when you are in a difficult situation, the human nature is to overthink, is to question, is to self-doubt or see things as...
and so we have to embrace that. We can't hide behind that- Yeah ... and just say it is what it is, you know? Yeah. Yeah. Yeah. And I think there's like the-- what's kind of, you know, talking about the market, it's like it is a hard time to be a person in a job, especially in a tech job, in a job like Meta or any kind of desk job, right?
Just because of what AI is doing to disrupt [00:13:00] kind of everything that we do. But it's also sort of necessary to remain competitive. So there's like, there's this tension between like business competition and competitiveness and employee care, and I think that's kind of a representation of some of the pressure that this particular scenario kind of raises, right?
So when we look at an article like this, you know, we look at a company like Meta, it's kind of famous for setting new workplace standards for a lot of places. So what does this signal to you as... Is-- could this be an example of where the market is heading? Like expectations internally can look like this?
Or, is it more, I guess, like I'm gonna stop the question there. Like does, does this go bigger than just what's going on with Meta? I think, I mean, I think that is a very valid point, having start, spent nearly a decade working in, in big tech. A lot of times what our largest, you know, tech companies do are, it trickles down.
It's, it's similar to higher education, you know, in the US. Like what a handful of universities do, you know, trickles down across the, you know, throughout the industry. That's... I used [00:14:00] to work in higher ed. So, so I do think that is a really valid point. I think in my opinion, that's, and this is my personal opinion, I think that's maybe the hardest swing of the pendulum that, you know, but that makes sense in some ways because they are a company, you know, developing, you know, um, an LLM and, and developing, you know, AI capacity and, and their own AI product.
That's where, you know-- So I think maybe, I don't-- I think maybe it won't be that much, you know, like, like we'll see at all companies. But I do think, to your previous point, it is really important for us as like people leaders and, and managers to, future-proof our teams, and that's really where I've been driving the conversation around AI adoption and usage, you know, within within, you know, my operations team and my onboarding team and policy folks, because it's really, I want them to think about how their role will evolve in the future, b-by, by utilizing it, and future-proof themselves, you know, because that's, you know, you know, I have a lot of deep care as a, as a people manager, you know.
And you know, I really, you know, want my folks to thrive and both thrive whether it [00:15:00] be at 1Password or thrive, in the next move if, if even if that's not here. So I think that's, you know, the one thing I've, you know, been focusing on communicating and building that trust. You know, it's like th-this is the reason why.
It's, you know, it's because w-we are making change, but I'm-- it's also a benefit to you, you know, in the future. Yeah. Because you're not gonna go to another, you know, um, you know, do this, an HR job without using AI, unfortunately, in the future. It's, it's just, it's the reality that we have to accept and sometimes feels weird, but, but I think it's, it's important for us to keep the compass on that.
Like, let's future-proof ourselves, and let's do higher value work, you know, in-instead of a lot of the repetitive things that we've groaned about doing, you know, for a long time. It's been great to see Weston's team is doing gre-great. We had our, uh, people all hands just today, and some of his team was showcasing the great work that they're doing, and it's beautiful to see how inspired they are.
Like, they're-- some of-- one of them- Yeah ... that was presenting was really, like, shining. He was like-- he seemed really actually a renewed energy almost, and, and I think that's gr-- those are great stories to hear and see for the rest of the [00:16:00] department because we hear a lot about the energy suck, and it's real.
Don't get me wrong. But, ... I think then when people get to grasp it and have wins it's great to see, and it does create renewed energy. I think three things. I think it's not where it's going in itself because I don't think that their approach, like to their point, like people are, are potentially gaming the clicks.
The jobs are evolving so fast that however the human is using those, that AI, like it can train the LLM, but I just think it's gonna hit a plateau, and I, I don't think that it's like... My instinct tells me that that approach isn't fully thought through, for now at least. So I'm not sure that that's where it's going.
I do think, like, we're-- part of our product is securing device trust, right? Is it's securing the platforms and all of that. So I do think making sure that y- as a company, you've got a sense of what are people using, when are they using it, what's the movement to keep things secure. I do think that's def-definitely high value and definitely worth exploring.
But, like, in the weeds of the details of, like, what they're inputting and things like that, less [00:17:00] so. And the third, I think right now, though, where it's, where it needs to go is exactly what Weston's doing. Empower your teams, teach them, make sure that they're using it, um, make sure that they're being creative about how they're using it and so that they add value, making sure that they're inspired through it versus creating more resistance.
I think faux pas, if I can call it like that, like we're not at Meta, so I don't know how it was received in like the re- like in the, in reality. But what could seem like a faux pas to a certain extent, That doesn't necessarily help you accelerate. That sometimes actually brings you behind, because then you've gotta re- try to rebuild that trust, like we said before.
So I think from the beginning, be transparent, create that trust, energize people, trust them to, to use the tools, excite them, to themselves tell you about their wins, right? Create the room for the human to be proud of what they've done, and don't make them feel like you have to go in and check exactly how they're using it.
Um, we're embedding it in our performance reviews. Tell us about the great ways that you're, that this is allowing you to, um, achieve your goals. How did it help you accelerate what you achieved or achieve even more through these tools? And so I think [00:18:00] creating a platform for that is an even more inspiring way to do it.
Yeah. I love that, and I love that, you know, you're kinda talking about the way that things are communicated and how that kind of get-- that leads to trust, because it's one of the hardest things to earn and one of the easiest things to break. And I think, like, I go back to my own change management certification, which is still to me, like the greatest certification I've ever gotten.
I don't... because it just says so much about sort of human psychology in every single kind of way. And the biggest thing is just kind of establishing a what's in it for this person. So like, what do... You know, sometimes it can be very, very tempting to just talk about the policy and like, "This is what it is.
You can't opt out of it. We're communicating this. That's it." But I think, like, when you start to kind of communicate sort of what the opportunity is or what the, why the decision kind of got here, and then quickly follow up with wins that kind of show, "Hey, because we're monitoring this, look at what we did that made your job easier," or, "Look at this, like, really cool win that someone had."
You know, we even at AllVoices, like we're using all kinds of AI across our different tech stacks [00:19:00] because, you know, sometimes it's like we're a small lean team, and we wanna be able to optimize our outputs. But it's like, you know, at first it's kinda like, do I want every single meeting recorded? Do I want these AI note takers in everything?
Or how do I wanna sort of like govern that? But then when you start to see how much of your work kinda gets surfaced because it's just been documented or, you know, because you can go back and sort of ask questions about across all these different emails and conversations that you've had, and it can surface sort of insights, it's like, okay, this does actually make my job easier, so I can get over the initial maybe weirdness of it happening.
And sometimes we skip the this is why this is good for you, look at how this is actually helping you part, and we just lean too much on the this is what you have to do. Yeah. I think, I think that you've made such a good point there. I think it's- You need to see the value in your own work stream, you know- Mm-hmm
for yourself, I think. And so we just have to help people get to that, 'cause that's what I think has, you know, driven adoption. That's what drove, my deeper adoption, you know, was once I realized I could use my Zoom note summaries and feed them into like a tool that we have, like a operating system tool we have, you know, and ask it to [00:20:00] scan my Slack and my meetings and tell me what I've committed to today, what I've been in meetings- Yeah
six hours. Like, you know, that's been invaluable by preparing to go out for two weeks and, you know, so, and, and leveraging those tools to, to make it feel a little less overwhelming, you know- Yeah ... to, to, to, prepare for a, a, you know, lead transition. Um- Yeah ... yeah. So I think we... But we have to see that for ourselves and we need to encourage our folks on our team to see that for themselves.
'Cause I've, that's how I've seen someone go from scared to now like an intermediate user, you know, in just a few short weeks, you know? But it's, it's, but they've had to see that, the benefit for themselves and their work stream. Yeah. I find that what you're saying is like the 2.0 version of change management.
I've actually had a... I was chatting with a leader recently and he's like, "Where's our change management strategy on all of this?" And I was like, "Well," "change management in the age of AI needs to be like we are the change management strategy." Like everybody- Yeah ... doing it. Yep. It's something that has to be con- It's not like a paper or a framework that comes after announcement that's- Yeah
stage gated and all of that. It's not those good old like theories [00:21:00] that we learn in the playbooks. It's like bringing to life that. It's like being the- Yeah ... change managements at all time- Mm-hmm ... by, by- Mm-hmm ... advocating for it, by a- g- providing that clarity, by providing the space, um, by, yeah, you need the FAQs, you need maybe the office hours.
Like you still need all the, the good stuff that we had that we used include in our- Yeah ... change management strategy, but it's like there's no time to do it on the side, right? Yeah. There's no time to do the project and then bring the humans. It has to be the project with the humans. It has to be communicating the change as you do the change constantly.
And so, it just makes it all faster and like it has to be much more tied together. But, um, I'm glad that- Yeah ... you raised that. It made me smirk because- ... you do still hear some leaders that are like, "Yeah, we'll do this thing, and then after that we'll have the change management, and then we'll figure it out."
And you're like, "Mm, no, no." Yeah, it's like, no. I wish. No time. We're still... Yeah, no time. We were still doing that from like going remote during COVID. Like we would still be going through that change management process if like we were- Yeah. Mm-hmm ... really doing it sort of the old way, right? Exactly. And I love that you're saying that we are the change management.
It's also like- I always say it's about learning out loud too. [00:22:00] It's sort of like- Yeah ... creating spaces where, you know, from a culture perspective, it's like, if you can create a perspective where people are safe experimenting with different tools, they feel confident kind of knowing within what boundaries they can make mistakes, right?
Because- Mm-hmm ... there's a s- you know, there's always a certain, there's always a certain amount of wiggle room that someone can make a mistake in something that's like fixable or, you know, there's n- not everything is sort of doom and gloom. But like being very open about what that is and communicating failures as much as you're communicating wins is I think another thing that we've seen a lot of people kind of doing is like, "Hey, I asked the AI to do this.
Look at this crazy thing that it did." Yeah. "Like now I have to figure out how to fix this, but ha ha, isn't that funny? Let's move on to sort of the next thing." That's the kind of stuff that kind of keeps the iteration going and keeps it, keeps the change kind of live, 'cause then people aren't feeling like, you know, everyone else knows what they're doing, but they don't.
'Cause that's the worst thing- Yeah ... that we could all be feeling right now, 'cause that's just not true. We're all figuring it out. That makes sense. Yeah. That's such a good point. Like one of the things I've done with our broader, um, people, partners, and operations team is just host like [00:23:00] a weekly session where I'm not an expert on anything but like, you know, AI.
But, but where I'm just hosting a session where folks can come share what they're stuck on, what they're working on, maybe an idea of something they wanna do, just to create like a safe space. And it's, you know, for the folks that were hesitant or struggle to carve out time, you know, in their day to, to experiment and play with tools, this g- gives us like concrete examples versus like, you know, when a company rolls out a new, you know, a new, AI platform, and it's just like, "Go use it," you know?
That can be a lot, you know, for, for folks when you're busy and you're, you know... In a lot of our people roles, you know, we're spending a lot of time in like meetings with the clients, client groups, with employees, so it can feel hard to carve out that time. So, but being able to create some intentional safe space there has, you know, where it's like no question is a dumb question, you know, and, you know, I think is just really, really important for, for building that trust and, and the ability to experiment.
Yeah, I-- So I really like that point. I think that's like the crux of, you know, if someone's listening to this and they're an HR person who's [00:24:00] in the middle of kind of figuring out, excuse me, how to introduce maybe not monitoring software, but maybe AI tools that someone's not as comfortable with. Like maybe, you know, we're just sort of in this space because I think the Meta example might be an extreme version for some folks, but we're all kind of dealing with something that's kind of in the middle of that, where we're introducing a lot of new software that employees don't trust.
So as we're kind of like thinking about this, like, do you have-- I know we've kind of been sort of giving, you know, sort of perspective and tips and tricks, but do you have sort of, you know, specific advice that you'd give to HR people who are trying to communicate sort of these broader changes or things that maybe that worked for you that helped to establish that sense of trust and how you kind of get employees to kind of follow along?
I mean, Wes, it sounds like you all had some really big wins on your team meeting today. Maybe there's something from there that your team is just like, "Yes, this is what we're really great at, and this is why this worked for us." I mean, I think-- I don't know, I'll pass to Gab, but I think just in the context of like my team, like, you know, a, you know, a, you know, group, as a group of like 10 [00:25:00] or 12, it much more has been focused on just creating that safe space for, for usage because, you know, we rolled out an AI agent, you know, building system and tool.
So it, it was like a lot for employees. It could feel, you know, overwhelming 'cause I, I didn't build agents, you know, myself, you know, before that. And so we have, you know, a lot of-- there's just a lot of change and a lot of things that are new. So, um, I just think, you know, mine is probably on that smaller side example, but Gab can probably s- can speak to it since he has oversight, you know, just for us as an organization.
Yeah. So when we started, I-- So the first, my first tip to be the HR, HR leader would be d- familiariz- familiarize yourself with the tool. Get in there, play in there, understand it, put on that user hat, right? Experience. And I think that's the first... Especially some of us are less technical, and so being able to jump in there, I think it gives us a good like-- it's a good bar for like how the average person might receive it in terms of like the, the technical point.
Um, and so familiarize yourself with the tool or the, the-- or even the change. Like if, if there's a way for you to kind of pilot that change, if it [00:26:00] is something into like, tracking and things like that, like really try to put yourself in that shoes and-- or literally experience it. That's the first. The second is, is communicate.
Understand the why. Figure out why are you even doing this? What's in it for them? Also, I like to connect it to like our mission, our like, our overall vision. What are we trying to do? For us at 1Password, we've been securing passwords for years, then we, we went into securing devices, and now we need to secure agents, because if we don't secure agents, like someone needs to secure agents, right?
They're out there, and so if we're not using AI, if we're not understanding agents, if we're not part of that, how can we ever aspire to secure that? And so it connects directly to what we're doing at 1Password, what we show up at work. Whoever you are, whatever department you're in, this is, this is our, our mission.
And so- Connecting it to that, connecting it to how it will help in their work. And I think it's important to take multiple angles because people have different motivations. People will-- Different aspects will speak to different people. I'm very, like, bigger [00:27:00] mission driven. I like to believe that I'm having impact on the greater good and the greater society, and so, and so that speaks to me.
But I think also just understanding, like, we wanna... Weston said something that's also something that I bring up a lot is, AI is here to stay. I will be incredibly proud if everybody that's gone through 1Password while we were leading the people function leaves 1Password better equipped to use AI, better under, uh, understands AI better than they did before they joined.
Has more skills. Uh, it just feels more equipped to continue in the workforce, to remain a relevant human and an important human in that ecosystem. I mean, that's a huge win, I think. And so, again, connecting really the why and from all sorts of angles, connecting it to the bigger purpose of your company.
And then after that, thinking about what needs to be true, what needs to be put in place. And so there's the space to experiment, there's the FAQs, there's the training sessions. People learn from different ways. Access to the tools. We have channels where we create... We have an open forum where people can ask questions, share stories, connect it to our all hands.
And so a-after [00:28:00] that, it's like the rest of, like, maybe the good old change management strategy. But from the beginning, it's like, be the user. You have to know this stuff. And then after that, connecting it to the bigger purpose and, um, thinking about it from all angles. And so far, it's been serving us pretty well.
Like, we, we started out, uh, on some of our enterprise tools just, like, six to nine months ago, or, like, maybe September last year, and we're at, uh, we're at 98% adoption. Uh, people are using it constantly. That's awesome. Yeah, exactly. And, and we've been really happy to see. That means, I guess, we're empowering and eq-equipping people well.
We just wrapped up our experience survey. Um, we score above 70% on the majority of how people feel around it- Yeah ... it allowing us to do a better job at their work. There are some question marks. There are some dimensions that are lower than others. But on average, all of the results scored 70% and above, and so that's like, that's huge when you- That's great
think of the state of the world. So there's a lot more work to be done. Things are moving fast. We-- There's no time to put our foot on the brake, but we went on the brakes, but at the same time I think, uh, I think the strategy's been working well for us. And we're [00:29:00] starting to see, like around the company, like hackathons have been popping up.
You know, and, and n- nearly every large org has been, you know, doing something concerted like that to to focus on solving real problems and also getting people to like the middle, you know, of, of, you know, that kind of AI capability framework. Um, we're, we're-- we've just kicked off today in our people all hands the plan for ours, um, that we're gonna do when we're all together in June in Toronto.
You know, I think we're cr- creating intentional opportunities there for-- 'cause it has some scaffolded learning, you know, that folks need to do ahead of time. You know, we'll have everyone survey themselves on, on, you know, how they're feeling about AI, how, you know, how they're using it in their workflow.
Um, and then start sourcing, you know, real problems, you know, that, that pop up between our teams 'cause we want-- we're cross-functionally, and there's things that, you know, efficiencies that we can certainly solve. So- Mm ... you know, creating those spaces I just think are really important, you know, once we've, once we've, built this, you know, this broader culture of adoption and trust.
Yeah. I love that. And you called out something, um, that I think is worth sort of just mentioning again, is just signals. So the [00:30:00] signals that, that you're looking for when you're trying to gauge engagement. Like you can do, you know, you can do surveys, you can do engagement surveys. And another thing that kinda complements that it sounds like is also just what is their AI adoption rate for the tools that they're using.
Yep. So adoption rate really does say a lot, and from where we are, it might not need to be more complicated than that. It's like, you know, how can we best support the 70% that are, maybe not flying yet, but are kind of getting there. Everybody's sort of incrementally working their way. And then what do we need to do for that 30% that's kinda still figuring it out, and like get to sort of the root of what that is.
'Cause this is a-- we're actually doing, we're doing a bunch of conversations and webinars about what are the metrics that we look for in HR now- Mm-hmm ... and how have they changed. And I think like adoption of tools kinda just says a lot be- before you even ask people what they think. It's like, are you using it or are you no?
100%. The using it is definitely the question because after that, I think all other follow-up metrics are irrelevant if you don't have the usage. But also the caveat I would put is that it's moving so fast, so we've, [00:31:00] we were at adoption, measuring adoption, and we're already like, "Okay, what's next?"
Because, I mean, adoption is great, but if it's not allowing people to feel better about their output or, a- and, and- Yeah ... we are seeing that the majority of folks do feel better about it. But still, if it's not time that they can reinvest in, in potentially themselves- Yeah ... in learning, in, in, or in taking on different work or then we'll plateau again.
And so that's the scary, but I think we-- but, uh, can be also exciting part of AI and like- Yeah ... how fast all of this is moving, is like staying on the ball of like, all right, this is metric is, this metric is great. Now moving on to the next just to make sure that, again, you're, we're, we're staying close to the evolution, that we're keeping our people in the flow of that and that we're, we're We're allowing them to thrive in that environment and, um- Yeah
and it sounds so baseline, but like we're all asking ourselves are we gonna be relevant, so I would just like- Yeah ... to make sure everybody stays really relevant and thriving. Same. But ... Yeah. No, same. I'm with you. Like for sure. I mean, like development learning, that's all like 100% core to my heart too, 'cause I think it's just like, I don't know, it [00:32:00] is what keeps us relevant.
It's what keeps us just kind of engaged in what we're doing, and help us to find purpose. Like learning's good for us. Growth is good for us, and that's- Yeah ... kind of like the part about this- And wins ... that can be really cool. Yeah. Yeah. Wins are great for us, like we saw- Wins are great ... today on Weston's team.
Yeah. I was just really inspired. Yeah. Yeah, and it's natural, right? Like I think it's like if we look at HR, you know, as like an industry, like how it's shifted. You know, like it used to be much more transactional. It was a personnel department, right? Like- Yeah ... we, we did talk about the role, you know, always of like the HR business partner being, you know, a strategic advisor.
Like just things like that, right? Like so it's, it's just- Yeah ... a natural part of the progression of this work and this field, you know, as, as with any other field. So, you know, like I, we saw a decade or more ago, you know, this big push around, you know, people analytics, you know, and like, and bringing data science- Mm
closer to HR. I worked at Google like, you know, in that era. And like, you know, it's, you know, this is now we are in the AI era. You know, we are to the data science era now. Yeah. And, and so it's, you know, it is kind of natural and I think, you know, the cool thing about our field is, we're able to, you know, change the way we work and show [00:33:00] up, I think in, in really fundamental ways, you know, um, you know, maybe compared to some other fields.
So, that's one thing- Yeah ... I ... And use our human judgment, you know, in an even better- Yes ... and more important way. Yeah. I also find a lot of people, some of the criticism we hear nowadays is, um, that it feels like you're, we're often pivoting. We're often, uh, like yes, on some things there's a pendulum for sure, and it's swinging multiple ways.
But I also think that in a way this is like a journey, and I don't know what's the next phase of the journey, but if I think of your, your comment, Weston, like years ago HR was this personnel department. Well, back then we understood that, that allowed us to learn the interactions, that allowed us to learn some of the dynamics, and so we were maybe more observers and s- and somewhat facilitators, but still like observers of the transactions, let's say.
Then we brought data science and we're like, "Wait, right now we're only hearing the qualitative side." So then we brought the data, the data science- Mm-hmm ... then we rounded it out. And then- You bring those two things together, and then you bring AI, and I just find like it's like that next evolution. Then you- Yeah
thanks to the fact that we understand the interactions, thanks to the fact that we understand data, we're actually better prepared now for [00:34:00] AI. So I guess if I take a step back and I think of all of this, I think our, our success for the future is like, let's lean into these phases. Let's lean into it- Yeah
and figure out how we can upskill ourselves, how we can thrive, and know that whatever-- leaning into this phase well prepares us for whatever's up next. Yeah. And, and it will be great. Oh, it's so perfect. Because this phase is happening whether we lean into it or not, right? So it's like with- Kind of is.
Yeah. It's either gonna be happening with us, or it's gonna be happening to us. And I guess like- Yeah ... you know, I always say everyone has the agency to choose which one of those they wanna, you know, adopt, but it's your- Yeah ... it's up to you at the end of the day. But just know that it's happening whether you're in it or not.
So I know we're actually at time, which is crazy to say, but so I'm gonna leave you to, I have one que- one last question for each of you, 30 seconds each. What's one assumption about HR that you think needs to be challenged? Like just one general assumption that everybody says about HR that you're like, "No, we need to challenge this."
And I'm going to let whoever wants to go first, go first. I won't call on anybody. HR is not HR. We're [00:35:00] people strategists. Yes. Yeah. ~Um, I'm blanking. Um... Sorry, Wes, I put you on the spot. Yeah, yeah. I didn't warn you. Yeah, yeah. No. I feel passionate about this one. I-- when people say HR, I'm like, we can cut this piece out, but I'm like, "Rawr."~
Yeah. Yeah. I think maybe mine is, is like HR, we, you know, humans at, that work in HR are still humans, right? And like it's, I, I think that's just something that we have to remind ourselves and like remind our clients, you know, that, you know, that, yeah, we are part of the company too, right?
And I think that's something that there's always this perception- So true ... that like HR is, is not part of the company. It's like back to the office, you know, like if you will. Yeah. Like, you know, Toby not being part of the team or the office. Like I think- Poor Toby ... you know, that's my point is that we're, we're still, you know, part of the organization and, and want it to thrive.
Yeah. That's very true. I love that. Love that, and it is so, so true. And like it's the, and you just could not say it better myself too, so thank you. Thank you, Wes. Thank you, Gab. Thank you both for this conversation. This was a lot of fun. I could definitely keep on going, but for the sake of- Yeah ... you know, everybody having lives and jobs to do, I'll stop us here.
And if anybody's listening to this, we'll put a link to the Business Insider article that inspired this conversation in the show notes here. And please definitely feel free to reach out to [00:36:00] me, to Gab, to Wes if you're curious to learn more about 1Password or AllVoices as you're kind of figuring out your own sort of stage of where you are in your own AI journey.
You know, we're cool, we're fun, we're easy to talk to, so don't be shy. Yeah. And thank you both for being here, and I hope everybody- Thank you ... who's listening has a really good day. Bye. All right. Thanks. Thank you.