Don’t Automate a Bad Process, Obliterate It | with Live from HR Tech, Pt. 1

0:00You don't automate a bad process. You obliterate. You completely look at it from a different lens of what is the current state? What should be automated? Because it's deterministic every time you do something. If it is probabilistic, let AI help the organizations with the data points to make the decision and human make the decision. and finally if it is consequential then let the human make the decision. And I believe that how organizations don't use AI is just as important as how we do and is a reflection of our culture and our values. And the litmus test that I use to think about AI usage is if every company in the world did what we're proposing at my company, if that happened at scale, would the world be a better place?

1:00You're listening to the Modern People Leader podcast, where we go behind the scenes with today's top HR leaders and work experts. We talk to them about how they've gotten to where they're at, what they do every day, and what they see coming next for the future of work. Hope you enjoy.

1:21Kieran, welcome to the podcast. I'm really excited for this one. This is our most official setup that we've ever had at an HR tech. Usually we're like, you know, running around, pulling out our computer, we'll like bring a mic with us. And so this feels very official having the full setup. How's your HR tech going so far? Awesome. So this is my first HR tech. I'm having a great time meeting a lot of thought leaders and experts of the industry, and I'm learning a lot. It's going to be a good HR tech. Well, we start every episode with something that we call good news stories, where each of us share something positive that's happened in the last week or two.

2:03Could be work-related, could be personal, whatever's come to mind for you. And I'll let you start. All right. Well, I did this yesterday, so it's easy. But I'm so glad you're doing something with a positive note because we all can use some of that, you know, during these times. Personally, for me, put my house on sale. I'm moving back to Dallas where I live most of my life. Thank you. I'm so excited that we're going to be moving back in the next week. I'm looking forward to that. That's great news. All right. What do I have? So, I mean, my good news is what I started with. This is our first time recording live in an official way at HR Tech.

2:46And this is just the start of my day. We're recording four episodes. And then I'm moderating a panel later today and then a panel tomorrow. And so it's a busy week for me. And there's been a lot of preparation that's gone into this. And I'm just excited to actually do the thing and have the fun. So that's my good news. I am so excited for you, and I'm honored that I'm the first one that you're doing in an official setup like this. Thank you for being the guinea pig and letting us do all the mic checks and everything. It's really cool. Of course. And so I want to start with the question of, you know, what's the hardest people problem that you're seeing companies try to figure out right now around performance, pay, or trying to keep their best talent?

3:31Absolutely. Where I sit at the intersection of technology, people, process, and most organizations are looking at use cases in AI automation, I view the world a little differently. Interesting. To me, it's about how do you design the work with technology in the mind, and the power comes from using the tool where you allow the employees and managers to have the experiences they are expecting in this world, and also provide the decisions that the manager should be making and let them make the judgment call to think through all aspects of pay, performance, and talent development, all the different aspects.

4:30Today, organizations may be viewing all of them differently, but to me, AI comes with collaborating everything together and putting together something in front of the manager to make the decision. Paint a picture for me. Like, in an ideal world, what does this look like? Well, if I am managing a frontline worker, to them, every penny matters. Yeah. I can't have once-in-year pay conversation, once-in-year performance conversation, once-in-year safety conversation. The first thing that we as humans need to do, in my opinion, and especially as leaders, your responsibility is to keep your people safe.

5:19So that means your frontline worker needs to have the trust that you got their back. And if they're going above and beyond, it was interesting yesterday that somebody was talking about if you're a driver and you're dropping off something at a customer site, Can you have the conversation about, hey, this is a product that is fast selling with your competitors. Have you considered bringing something like this? How powerful that is. For that conversation to happen, the employee needs to feel engaged. They're recognized and they're incentivized and paid appropriately to the market. So that is where you invest in them, so they will invest back in the organization.

6:11And where, you know, and this isn't just specific to your company, but where do you see AI actually changing how companies make some of these decisions or some of the processes that they have? Well, the most successful organizations, in my opinion, they're not going to take AI and buy a bunch of tools to implement them. And also, it's mostly about work redesign and not automation. So back when in early 2000s, I attended a webinar where I learned about you don't automate a bad process, you obliterate. You completely look at it from a different lens of what is the current state? What should be automated?

7:09Because it's deterministic every time you do something. If it is probabilistic, let AI help the organizations with the data points to make the decision and human make the decision. And finally, if it is consequential, then let the human make the decision. So that's how I view it. If the organization is simply taking a process and automating, it's not going to give the result. But if they try to scratch all of that and look at it through fresh lens and redesign the jobs and put AI where it really can augment human decision, that's going to be even powerful. Okay, so I'm going to make sure I got all of that.

8:00So it's more of a work redesign. And there's three buckets. there's the consequential decisions that humans should always make there's the probabilistic decisions where you're maybe leaning on the ai a little bit more for the data and then deterministic and what did you say for those that's like a what was one equals to two always the case ai can you know you can automate that with ai okay i like that it's a good little frame for how to view this new work design. Okay, so I'm almost imagining a company looking at every workflow or process and going to that exercise of figuring out which bucket a piece of work falls into.

8:51Is that sort of how you think about it? I know in reality at a company, probably as large as yours, it's not that easy. How do you even go about doing that? Well, you know, there's different tools this day and age. Historically, we always looked at job descriptions. You know, it's a giant, you know, paragraphs of English talking about what people do. But now it's going a level deeper and understanding what are the specific tasks that somebody does in that job? And how do you break it down into the skills? and do we have the right skills for the future with AI in place? And what can be provided to the leaders for them to continue to improve their talent internally?

9:45And as a whole, the organization then is looking at, can this task now be automated because it's deterministic, probabilistic, or you need the human to always make the decision? So to me, it's about AI is going to help make the decision, but is never replacing the decision maker. I see. I see. So for decades, the main way that you would reward great people is by promoting them into management. I feel like this model is being flipped upside down in the last 12 months, and I imagine that's going to continue, or maybe it'll stabilize eventually, and we'll go back to normal. I don't know. Do you think that model is broken?

10:38Any thoughts on that statement that I just made? Well, I wouldn't necessarily say broken, but it was relevant for the past. Yeah. What was relevant for the past may not be relevant for the future. You touch on a great point about, you know, traditionally you go to college, get an MBA, now you became a management graduate, maybe get some consulting experience and now you do the next level. Is that the only path for pay increases and promotions and whatnot? I think what AI has done is put a lot of power in the hands of every human being if you can intelligently fetch that information. So it's like having access to 1 ,000 MBAs at your disposal, but you have to ask the right question.

11:29So the traditional models may or may not be relevant anymore. In the future, in my opinion, if you are a builder or you are a thinker, if you are able to problem solve more efficiently and if you're bringing 2x, 10x, whatever the value is to the table, organizations will tend to move more towards incentivizing for their output, not necessarily about the title and the degree that they had in the past. I really relate to that. So as a business owner, where I'm the solo full-time employee, there's only so much that I can do in my day. And so I've had to get really good at using these tools and extracting information.

12:21And so I won't bore you with all of the details, but we're in the process of launching something new, a new product. And I've interviewed 40 people over the last couple of months. and in the past if I was going through that process I'd have to like manually go through all of the data or maybe put it into like a spreadsheet and figure out how to look through all of this qualitative feedback and like make sense of it now I can have a note taker in every meeting which results into a transcript I can then put each of those transcripts into a clod project and then I can tell that project what it is I'm trying to achieve and I can ask for recommendations based off of the data that's available and I feel like that one little example could be applied to anything at least like in the knowledge workspace I know it's probably a bit different for frontline workers but even then maybe maybe there's maybe there's an equivalent of that so yeah a lot of what you said really resonates with me.

13:23Yeah. The one area where I want to be extremely careful with is these AI models keep changing every few months. Can't keep up. Can't keep up. And they're getting smarter and smarter. And where a human needs to be careful is not being biased that AI is always is right and make your decisions based on what AI has given you. So be careful and always put on your hat of, is this right? Validate it, process it, and make sure it is relevant because it's always about the context that you're providing. So validate before you make the decision. That's a good call. Some of the recommendations that I get, I'm like, I'm not going to do that.

14:11Like, good, good tip, but no, thank you. Not for me. Just curious. You know, you're here in Vegas again. I think you said you've been here countless numbers of times over the last few years or in your career. What brought you to HR Tech? Like, is there anything in particular that you were hoping to get out of this week? Any, any like insight you're looking for? Yeah, what's the goal while you're here? Very good question. I've been in the HR tech space for a quite long period of time, say about 25 years. And traditionally, when I started, the technology that I was on, that is what was relevant at that time.

14:52If I can take care of my job, there ends my job. But I think for the past couple of years, I don't know if it's the professional maturity in my career, or this is where the world is going and I want to make sure I stay relevant in the market, I need to act as a trusted technology partner and an advisor to the CHRO. That is different than I need to deliver technology needs of the organization for HR. There is this talk track about how CHROs are going to play a very powerful role in the current AI work, bringing people together, redesigning the work, AI fluency within the organization. There's so many aspects where the CHRO need to play a very critical role, partnering with the legals, the finance, and the technology teams and so forth.

15:53I feel that is a critical component. And for the CHROs who traditionally looked at people process, not necessarily technology as much. And for me as a full-time job, keeping up is so hard. This is where I need to be the trusted technology partner to the CHRO. So I can help them think through all the different aspects. And instead of going to the traditional, here is the technology we are using, let's go to that conference. I wanted to be at HR tech. So I look at it from an organization or an enterprise lens and what different organizations are doing in different technology partners are innovating and take those learning back, learnings back to the organization and see if we can apply them and not fall in the trap of let's go automate use cases.

16:45Yeah, that's yeah. And you got here yesterday, right? I got here. Yeah. I mean, I lost track of time. And yeah, this is my third day. Third day, okay. Yeah, I was here for the executive strategy summit also. Anything interesting that you've learned so far? Yeah, I mean, as simple as AI fluency, if the organizations are looking at, oh, let's get them trained on blah, blah, blah, that may or may not work because they don't know what they don't know. And the second reason is I have my day job and this is yet another thing that I need to spend time on. But if you redesign the work and make AI as part of their process, they're automatically learning this stuff.

17:27You have to learn. So create that healthy friendship where the folks are forced to learn the tools that are needed for the next generation or the upcoming years. Not necessarily push them into learning. As simple as that. And another very interesting thought I heard, you know, during that strategy summit is create your kill company. That raises a lot of eyebrows, but I think... Say that again? Create your kill company. Your kill company. Yes. That is exactly the reaction I get. I already know what that means. Yeah. Sounds scary. Sounds really scary. But if you think about it, and I'd be interested to see your reaction after I answer the question.

18:07So what he explained is create a small team within your company that acts like a startup that's competing against your own company. how powerful is that? I think there's a, I'm so bad at remembering the names of books, but I think there's a book that came out in the last like year or so. I think the author is maybe like a startup founder, like four or five time founder. And that's how they've been operating the last like year or two. They constantly have like this kill company that's trying to beat their current product. Yeah. Where did you get that? And so you got that idea from one of the executive strategy.

18:46Yeah, I forgot the name of the gentleman who had that in the slides, but it was from the strategy summit. That was one where you take a picture of the slide. You're like, I need to take that back. Yeah. And so your goal is to, I guess, broaden your horizons as it pertains to what's out there and what you can do versus just defaulting to using the tech you have and automating everything. Is there anything else that you've learned that you're like, I need to take this back to my CHRO or like I need to tell them about this one person or have them read this one book? Any other good nuggets? Yeah. Yesterday, there was a keynote and the speakers were from Cisco.

19:31They walked a lot about how they are transforming Cisco. It was really mind blowing. I had some great nuggets from their team that I do plan on taking it back to our team to see, let's brainstorm and explore what is relevant to our organization and how can we apply that to one. let's focus on enhancing the HR team members one AI fluency to make their jobs relevant for the future and then think about it broadly from an organization standpoint the most important thing that you know they taught me yesterday is trust is the key before you push any technology you got to be you got to meet your employees where they are you don't want to put too much fear and let that burn the company at the same time you got to be honest with them so that's one thing that really resonated with me and the second thing they mentioned about is don't let AI dictate the governance make sure you have a solid governance in place before you start putting in all these different AI automations in place.

20:48Those were the two powerful messages that I would like to take them back. And I connected with a few of them that are willing to share their governance model. So overall, it's been an extremely insightful conference for me. One last question. Is there anything that you believe to be true about the world of work, but don't yet have the data to support it? Well, there's quite a few things. But we all heard about humans are going to be extend by X amount of, in X number of years. It keeps moving up too. First it was like 15 years, then it was 10, now they're like next year. Yeah. Look, you know, we all can control what we can control.

21:25I'm not sure if there is enough data to prove one way or the other. I live with the mindset of let's focus on what we can do, not necessarily on the result. And two, there's always going to be good and bad and good will always prevail. So if that's the case, how are we going to responsibly, you know, my earlier comment about the goal with AI is not to replace the decision maker. It's to help augment the decision. With that in mind, let's establish the trust. Let's improve the decision making process. Let's enable the decision maker and enhance our employee and manager experience. With those guiding principles, you know, I don't have enough data to say humans are going to be extinct one bit.

22:18I love that. Well, the way that we end every MPL episode is with something that we call one word or phrase close. Just whatever is coming to mind for you as we wrap this up. What's going through your head right now? Humanity. I can't get over create the kill company. I love that. Well, thank you so much, Kieran. This is a lot of fun. Thank you for being our guinea pig and our first recording, our first official recording at HR Tech. Thank you so much and enjoy the rest of your conference. Well, Daniel, thank you so much. I totally enjoyed our conversation here and wish you the success in what you're doing.

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24:11If you want to schedule a free consultation with Manifest, just click the link in the show notes. Jacob, welcome to the pod. How are you doing? Thanks for having me. We start every episode with something called Good News Stories, and it's just like a fun little positive way to kick off every episode. And we prefer for our guests to go first. So do you have anything? Could be work-related, could be personal, whatever is coming to mind for you. So personal good news is I'm getting out of Vegas this weekend and going to Zion National Park, which I think is a good antidote to all the lights and being indoors all week.

24:44I've been saying that I feel like Vegas like sucks the life out of you with all of the slot machine light a little bit goes along the rest yeah so yeah I feel like I need like a nature weekend the problem is my wife will only go glamping and so you'll have to tell me how it goes glamping out in Zion but that sounds amazing yeah on a professional note I think one thing that I'm really happy about is ServiceNow just gave us our first two agents live across our HR ecosystems. So that was a big milestone for us. Well, if we're able to, I would love to talk about that a little bit. My good news, what is my good news?

25:24You know, this past weekend, I was in Destin, Florida for one of my best friend's weddings. This is a friend that I've had since we were like 15 16 years old we didn't go to the same high school but we both went to the University of Texas in Austin and we became best buddies there and I've I've gotten to see like his evolution from like dumb college kid to very mature like serious adult and I just like love his wife like they're the perfect couple and so it was a blast of a weekend I feel like I'm still kind of recovering from from a long weekend like that but it was such a good time so that's great it's fun to watch people's evolution from dumb college student to successful i was dumb college student i feel like i've seen a couple people here at the conference that i haven't said hi to because i don't even know if they remember me but if they do remember me they're like wait you do a podcast and you have a media company like what like i would have never expected that Yeah, totally.

26:33And I feel like that's an example of the journey we're all on. Like, we'll look at the way we approached our work two years ago as like our dumb college student. Oh, especially with all this technology that's coming out. I feel like every four or five months, there's a newer and better way of doing things. And so so let your friend be an example that we can all learn. We can all learn. If Michael can do it, then then we can all do it. And so I want to talk about, well, you know what? Let's start with the two agents with ServiceNow. Tell me more about that. Yeah, so Rivian is a large, complex enterprise.

27:06We've got employees in manufacturing facilities, in sales and service centers all across the U.S. And then we hire some of the most competitive talent in the Bay Area for autonomous driving and AI and machine learning. So rolling out anything for our full employee population is complicated. Yeah. And we get inquiries from employees, you know, across the whole spectrum of requests. And so we are implementing agents to really help us deflect as many cases as possible. So we've got a huge knowledge base and some agents have started responding to a limited set of queries that our employees give us.

27:44We have an agent to route cases to the right person. And we're just starting to get into agents that autonomously answer some of the lower risk, high volume cases. So we're starting our hygienic journey using our ServiceNow platform. Oh, that's cool. I'm actually right after this, around like one o 'clock, doing a panel with the director of talent acquisition operations at Ford and Eightfold. and through the prep I learned a lot about like what the process looks like getting anything rolled out at a company the the size and scale of a Ford or a Rivian and he was explaining to me that it was a year process just to get the tool approved and there was a lot of negotiating and making compromises and after a year they finally get it approved they're now in their pilot.

28:41I think they're doing, they're like on month three of the pilot and they started with a small group and now they're looking forward at what it looks like to scale this, the entire company. Does any of this feel like, does it feel like a similar experience? It does. So that's the, the dichotomy that I feel when I come to an event like this, is we talk about how the pace of change is so quick and how the technology is evolving. And then I go back to my day job and I realize how slow it can be to roll out these solutions across a large, complex enterprise. And for your listeners who are in smaller organizations, you likely have the ability to iterate and make those innovation loops faster.

29:22But for us, it requires so much scoping, prioritization in an already really swamped people's systems queue, a lot of development between multiple different stakeholders, complex testing. And so it can take, to your point, months to get through a procurement and risk assessment process, six to 12 months to get through an implementation and testing before employees really see the benefit. So that is the dichotomy that I feel. Yeah. And sometimes I wonder if we should just leapfrog kind of these traditional systems that we use into a new reality. Explain what you mean by that. I mean, we're using a lot of legacy systems that existed in the pre-AI era.

30:08And I know that there are so many AI native solutions popping up. Yeah. And then the other tension that I feel is that the people team, we understand these legacy systems role in compliance and security and privacy for sensitive HR data. So we want to buy these systems because of the moat that they have around our employees' data. But our IT team thinks that they can build everything. And so we've invested years in configuring these systems and IT is pushing us, well, let's just build our own solution. But we're less confident they understand all the compliance and privacy and security things.

30:43So it's always a question of like, what are we investing in? What do we continue buying? And then what can we build internally? I guess on that note, when you think about all the categories of tech in HR, I mean, I look around, I see like hundreds of vendors. I mean, maybe I'm exaggerating. There's a lot. which categories do you feel like have the biggest moat right now? The biggest? The biggest moat. Biggest moat. Systems of record, for sure. I think companies should approach with a lot of caution building those internally. Yeah. Yeah. Interesting. Interesting. But the rest is fair game. If it's not a system of record, I mean, I think it's legit to try and build those internally.

31:29And so when you say building it internally, everyone's vibe coding these days. Is that the route? Or I mean, I guess even engineers are using cloud code. Like my wife's a machine learning engineer and that's what she does all day. And she's like, I'm actually kind of tired of like being in cloud code all day. Like it doesn't feel right. But yeah, I mean, who on your IT team is building these internal tools? Are they just trying to create better versions of what you've used in the past that are custom built for Rivian? What goes into that process? Yeah, so I think of it in a couple of buckets. So there's our IT team who are building replacements for SaaS products that we've historically bought.

32:11But that hasn't always been IT's role, right? That's kind of like a new development. That's a new development, Kai. And what I want to make sure is they're thinking about how do you not just build the initial tool, but then who's responsible for adding upgrades? Yes. Keep it, you know, making sure it lives in a place that lives beyond the employee who designed it. How do you ensure sustainability and enhancements and improvements over time? I think that's the challenge with building. and then you know one of the things i do for the people team is lead ai fluency sessions where i teach everyday employees how to vibe code their own tools so you're a teacher as well i'm a teacher as well i grew up in lnd so that's your bread and butter yeah part of my bread and butter and so we have all these you know custom vibe coded tools for project management and reporting and but again how do you make them sustainable so that they live beyond the person who built them Like, where is that code living?

33:10Where's that Apps Script living? How do you onboard other people to use it and give visibility? Like, those are like governance questions that I think my organization is wrestling with. I mean, it's hard. Like, I mean, we have a, I'm the sole full-time employee of MPL, but we have three contractors now. And over the last six months, the way that I've been thinking about it is they have their workflows that they own. They have access to tools to build better tech for themselves. And so it's now their responsibility to maintain these tools over time. time it's hard on our small team I can't even imagine at the scale of Rivian like how many employees does Rivian have?

33:5616 ,000. 16 ,000 dang that's a lot and so tell me more about these fluency sessions what's on the curriculum? Yeah so we call them the AI playground. I like that. I've been running them you know I've been at Rivian for five months I'm pretty new so I've led a couple sessions at this point so one was just around like basic AI fundamentals and principles, like introducing the concept of human in the loop, introducing the concept of bias and how it manifests, how to handle sensitive HR data and employee information. And then we did a tutorial on how to vibe code. So like literally, how do you open up Gemini or Claude or ChatGPT?

34:36How do you paste code GS and index files into an app script? How do you share it? How do you refine and iterate. And what we found is that that really unlocked this burst of creativity across our people team. And we realized that we actually had to start storing these artifacts in a central place. So we created like the AI playground hub, where if you vibe code something, put all the code on this centralized hub and let other people use it. And that's our way of making sure these products live beyond the person who made them. And that's what I was going to ask about. So for us, we use a somewhat obscure vibe coding platform.

35:17And the reason we use them is because they've created like this playground of sorts or this, they've found a way to connect all of our profiles. And so you can see active builds and what people are building. You can go contribute to that build and it makes it easy to add new people onto the team. It's almost like Google workspace, but for vibe coding. And I think eventually like all of these platforms are going to have that built in internally if they don't already. But that's super interesting. So in these, what did you call them, AI playground sessions, what do you find that people are either the most surprised by or blown away by?

35:54I'm curious what the reaction has been. Hands down, what people are most blown away by is when somebody who's a vibe coded a product has a chance to showcase it. I go, here's what I did. And we have so many advanced AI users on the HR team, particularly the L &D professionals who support really technical functions. They have built some incredible vibe-coded products that are way beyond even my skill set to develop. And so when we showcase what we're building, there's light bulbs that go off across the team, including in me, about, wow, I didn't think AI could have an application here. but now I'm inspired to go try and build something and if I don't know how to do it I can actually ask the tool for guidance yeah are you able to share any of these use cases that maybe you wouldn't have expected yeah I think so there was one use case where our L &D team had to build this like super technical curriculum with like two days notice and they had within two days they had vibe coded their own like course authoring tool dang they had created a whole series of agents and sub agents to perform specific aspects of curriculum design and minimize token usage and so what they were able to do in two days was to to achieve the outcome and get the token usage down from something like 40 or 4 million tokens to execute this to 120 ,000 using sub-agents.

37:32And it was just, you know, we didn't understand even the concept of sub-agents. Yeah, when I hear you say that, I'm like, I don't even know what that means. Yeah. And, you know, one of the things I learned is like I use my AI tools to create a second brain where I throw in all my documents, all my emails, all my slacks, all my meeting transcripts, and I use it to identify patterns. And what I found is that my Cloud token usage kept getting exponentially larger. I'm like, why is this happening? Turns out the Cloud MD file that I was putting all that in, 70 % of my tokens were used just on that context window.

38:10I didn't know that that consumed tokens. Yeah, it consumes a ton of tokens. And so I've started to shift the way that I manage my context window as a direct result of being inspired by some of these products that our team showcases. A few weeks ago, we had somebody on the show named Andy, and he's the chief people and agent officer at Kantar. And he talked a bit about this idea that there are four beneficiaries of AI. And I'm probably going to butcher this. So if I forget one, sorry, audience. You have the employees, you have the shareholders, you have customers, and then you have society. Wow, I actually remember it all for it.

38:53And when we were about to hit record, you were like, I really want to talk about this idea that in addition to thinking about all of the efficiencies gained, we should also like take a look in the mirror and see if what we're deciding on some of these very big decisions are actually good for society. And so tell me more about that. Yeah. So I try to stay up to date on podcasts that talk about AI. And I think one theme that I have took away from these podcasts that is a larger theme in history and in life is this concept of balance. And that for every step forward, there's also a step back. For every net positive gain in technology, there's always a dark side.

39:41And these dark and light sides of technology are always held in balance. So, you know, five years ago, we were asking the question, has social media been a net positive or negative? because we started out in this burst of optimism and then now we live in the toxicity and negativity that these platforms have provided yeah and i think ai is no different and whether you think ai is a an alien super intelligent brain that is a fundamental shift in humanity or it's just another software tool we have to be honest about the upsides and the downsides and i think what I worry about is that some of the ways that HR professionals talk about AI, it might not play well in five or 10 years.

40:33Same word. Have you ever seen those, like these videos before the 2008 financial collapse of banking executives talking about... Raise your hand if you think that these are all really bad. Yeah. Everybody raises their hand. Yeah. And then five years later, you're like, oh, we saw this coming. That didn't play well. And so I think as HR professionals, for many reasons, we're incentivized to talk about the upside of AI, because we're the ones tasked with shaping it. We're the ones tasked with designing the workforce of the future. And if there are job changes and job losses, we are going to be the ones to manage those.

41:12And so we have to, for our own sense of purpose and well-being, there is some moral reasoning that goes into how we think about AI purely because of the nature of our role. And that's not good or bad. It's just the way that it is. It's how humans work. And so when I hear these HR leaders talk about the power of AI and how it's good for employees, that may well be true. But we also need honest acknowledgement of how it could lead to disenfranchisement, how it could lead to further stratification and inequality. And we need to be honest about the implications of some of the decisions that we make in the short, medium, and long term.

41:56I feel like a lot of the decisions that companies are making are pretty short-sighted. Yeah. And I get it. Like, you have to maximize profits and you have shareholders and there's a lot of pressure on the executives and then that's going to, you're going to feel it all the way at the bottom. And so I get it. I have been surprised at the extent to which I've heard HR professionals relatively glibly talk about taking away employee privacy, using data from private Slack messages, emails to get intelligence on employees. I don't like that. So we take employee listening to a new level with AI. And, you know, when this leader I was listening to talk about this, they framed it in terms of like, oh, this will give us great data on skill validation if we look into everyone's private and public communication on company channels.

42:51But there's like this elephant in the room of like, well, that could also be used for some really nefarious purposes within an organization. but we're incentivized to talk about how it could help employees not how it could lead yeah it's like with social media the same same example it's like you can make yourself good you make yourself feel good about social media by saying i'm getting like the best recommendations or you know now with muse like now i have this personal agent that knows literally everything about me yeah but at the same time, like, do you really want? Yeah. Yeah. I don't know.

43:28So one thing that's really important for me when I started my role at Rivian, I first thought I joined Rivian because I wanted to do AI work at a company that I didn't feel like I had to apologize for working at. Yeah. And I wanted to do it at a company with a human centric values based culture. And our CEO, RJ, literally talks about wanting to make the world a better place for his children. Yeah. And so what I do with leadership teams at Rivian is lead AI ethos sessions, where I ask these leaders to reflect on our company values and our company mission and ethos, and then build a set of principles for what those values mean for how we do and don't use AI.

44:10And I believe that how organizations don't use AI is just as important as how we do, and is a reflection of our culture and our values. And the litmus test that I use to think about AI usage is if every company in the world did what we're proposing at my company, if that happened at scale, would the world be a better place? Oh, yeah, especially here in the US. Yeah. So we talk about eliminating entry-level roles. Every company in the world did that. What condition are we leaving our children in? How are we building experience and skills? Also, think about all of the untapped potential. How are we?

44:55Yeah. These are the people that are going to better understand how to use these tools than anybody else in the workforce. Yep. If we move towards surveillance, what impact is that going to have? So it's I think and this is always HR's challenge is the CFO wants to maximize efficiency and shareholder value, which is a requirement in the society we live in today. and it's our job as people leaders to provide the foil and the counterbalance and to help the organization find that right balance of getting the ROI from the tools that we invest in as we should, but also not sacrificing our culture and our values and our future generations at the same time.

45:37So how do we expand the view of the impact from just our employees at our company to our communities and our world at large. I love that. It feels like you have a very clear point of view on what we can gain from this technology, what some of the concerns should be, and also just like an understanding of how hard it is to make some of these changes at a company like Rivian. And so I'm curious, when you come to a conference like this, where you have hundreds of vendors, you have all of these speaking sessions, what are you hoping to get out of it? Are you here on a mission? What's the goal? I think what I have in the past two days gotten the most out of is connecting with people and just hearing about others' AI journeys and just building my own vocabulary and fluency around what organizations are doing in AI.

46:43Because I don't know about your listeners, but when I'm in my day job at Rivian, every day I dive in at 7.30 and I come up for air at the end of the day. And I have had, you know, I've had eight hours of meetings. I'm trying to cram in work in between. And I just can't keep up with what's going on. And so I feel that deep in my bones. And we're just a tiny little company. Yeah. And I need time. Like I just, my company just rolled out this new AI tool. I need like a good day to just like play with it and figure out what it can do. If we're asking employees to vibe code. That ends up being time on the couch at night, vibe coding or time of the weekend.

47:25And so there's this thing where as AI makes us more productive, which I do think it has made me orders of magnitude more productive in my role. The expectations of my role also increase. And so I'm just like doing more and more work faster and faster and faster. Yeah, it's like it never ends. Like companies are always going to want more. Yeah. Or should they? I don't know. I guess that's part of the question you're asking yourself. Well, I think the tension in companies is that we're seeing that individual productivity gain is somewhere between three and ten times more. Wow. For people who use AI effectively.

48:02but organizational ROI is not, or organizational productivity is not doubled or multiplied by 10. And so it's kind of like, it's this idea that you have all these individuals who are moving really quickly in different directions because the organization is not set up to maximize the individual productivity gains. And so that's where the fundamental workflow redesign a process redesign, rethinking decision rights, rethinking spans and layers. All that work has to be done by an organization, which, by the way, requires a really strong, capable, AI-fluent people team, which requires investment in the people team.

48:47Yeah, yeah. And so that's your role, right? You're doing all of those things. That is my role. Yeah. I mean, I'm doing the base level, like task mapping, workflow redesign, process redesign, managing demand into our people systems team, trying to build AI fluency at scale across the people team, and then trying to create an AI ready enterprise by upskilling our HRVPs and our OD professionals. And by the way, trying to do it with this moral, ethical, socially conscious framework. That makes it a lot harder, honestly. Talk to me a little bit more about the task and process mapping, what does that entail?

49:29So I think like a lot of companies, we have thrown headcount at processes that just have not been designed with streamlining and efficiency in mind. Yeah. So across hiring and onboarding and offboarding, every team has their own manual tracking spreadsheet. Every team is taking data from one system and moving it into a spreadsheet and then moving that into another system, we have very little visibility into where new hires are at in their onboarding journey. And as we talked about earlier, the pace of new technology adoption and configuration and utilization is slow in large enterprises. And so I'm kind of stepping back and trying to just identify what are the most broken processes that take up the most bandwidth on our team?

50:23And how do I untangle them and rebuild that process with the outcome in mind, with an AI and automation and technology lens? So I don't want to just automate a broken process. Yeah, I want to like rethink the process end to end. So I just did a lot of workshops with our talent acquisition team using appreciative inquiry to imagine what could our TA process look like? let's not think about our tools right now. Let's not think about system limitations. Let's just think, ideally, what would this look like? And then we can go to market for the right build and buy solutions to enable that process. So that's the fundamental work that I think has to happen before you go into AI tooling.

51:08Whereas before, five or 10 years ago, you maybe had a few different options when it comes to solutions and you're like having to reverse engineer your process to map the technology. Yeah. Now you're starting with the process and mapping backwards. Yeah. Every, a lot of people start with tool first, like, oh, this tool is going to solve my system. It never does. And every new leader comes in with their favorite tool. Yeah. Which creates all this tool churn. Like how many ATSs have we gone through in the last five years? I won't say publicly, but that's because we fundamentally have to think differently about systems enable our process.

51:48And if we don't have a clearly defined, efficient process, we can't make good decisions about tools. Well, Jacob, this was so much fun. Thank you for agreeing to come and talk to me. We end every episode with something called one word or phrase close. It could be anything that's swirling through your head right now as we wrap this up. Do you have anything? I guess my one word is gratitude to be here. I mean, there are so many smart minds in the room. There's so many people to talk to. And I don't take it for granted that my company put me out of my busy day job for a week to come here and just be present and learn.

52:25And I think I'm left with how important it is for those of us leading AI to go to these things like every quarter just to keep up and be in a community of people who are doing this together. I'm going to say we have an obligation to create a better future I think that's my main takeaway from our chat thank you so much that power comes great responsibility the Spider-Man principle I love that on that I think that's a perfect way of ending thank you thanks for tuning in to another episode of the Modern People Leader we really really appreciate it And if you enjoyed the show, please leave us a five-star rating.

53:11It would mean the world to us. And connect with us on LinkedIn. We want to know what you think about the show. And you can find links to both of our profiles in the show notes. Thanks again for listening and see you on the next episode.