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In today’s episode, we speak to Debbie Lovich, Managing Director & Senior Partner, Boston Consulting Group.

Debbie has decades of experience in making work, work, and recently wrote the stellar HBR article “How Gen AI Can Make Work More Fulfilling,” based on her team’s research about AI & Joy at Work.

In this episode, you'll learn:

• How AI Can be Used as a Forcing Function for Organizational Reinvention
• Why to Prioritize AI in High-Toil, Low-Engagement Tasks
• About Leadership and Manager’s Involvement as Being Crucial for AI Adoption
• How Co-Creation Drives Better AI Solutions and Employee Buy-In

If you’re in the midst of rolling out AI or are just getting started, this episode is a must-listen.

Key Insights from Debbie Lovich

Here are the actionable key takeaways from the conversation:

‍1. AI as a Forcing Function for Organizational Reinvention

AI is more than a productivity tool—it is a catalyst for rethinking work structures entirely. 

As Debbie shared, technology is coming in to disrupt the table setting anyhow...so you have to rethink how work gets done to include employee joy alongside customer value and shareholder value. 

And increasing joy delivers, as BCG research shows employees who enjoy their work are 50% less likely to want to leave a company, while people who spend over 4 hours per week on ‘toil’-type work, people start looking for a new role. 

View AI as an opportunity to fundamentally redesign work processes, boosting productivity and increasing employee engagement and satisfaction.  

Just as Matt Kropp, BCG X’s CTO said in the first episode of this podcast, this is a chance to align technology with human needs, making work more fulfilling.

2. Prioritize AI in High-Toil, Low-Engagement Tasks

AI implementations should eliminate repetitive, time-consuming tasks that drain employee energy.  

Debbie shared that the average office worker spends a day and a half each week on soul-sucking admin work, and the average manager spends about a full day. That's a great place to point Gen AI, allowing employees to focus on work that sparks joy.

Target AI at low-satisfaction, high-toil tasks that consume time and energy so that you increase productivity and enjoyment. 

You do this by sitting down with employees and looking how they currently spend their tasks, and what part of that time is toil. 

Automating these tasks increases efficiency and allows employees to focus on more meaningful work, reducing attrition and burnout.

3. Leadership and Manager Involvement Is Crucial for AI Adoption

AI tools will only succeed if managers actively use them and foster an environment where employees feel supported in exploring new technology. Leadership needs to lead by example for them to do so. 

As Debbie said: “Don’t ask your employees to do anything that you wouldn’t do yourself.” She mentions the example of getting reverse-mentored by a junior employee on building her own GPT to write social copy.

Debbie’s research found that teams with AI-engaged managers are 4x more likely to adopt AI tools. In particular, Debbie shared that teams using AI the most had managers who:

• Used it themselves
• Cared about their employees (creating a safe environment to experiment) 
• Explained why AI was being introduced. 

Ensure managers are well-versed in AI tools and can lead by example. 

This includes using AI in their work and creating a safe, open environment where teams can experiment without fear of failure.

4. Co-Creation Drives Better AI Solutions and Employee Buy-In

AI adoption is much more effective when employees are part of the solution-building process. 

Debbie quotes former Red Hat CEO James Whitehurst who said that “if you have do change management, you’ve failed in how you do the work.”

In an effort to not disrupt people, companies are introducing AI through small teams on the side, with little input from those who actually have to use it.

Companies need to “design for adoption” by co-creating AI solutions ensures they fit into the workflow and increases employee ownership and enthusiasm for the new technology. 

Involve employees early in the AI design process to ensure the solutions align with real-world workflows. This will lead to higher adoption rates, fewer operational disruptions, and more meaningful results from AI investments.

And remember Debbie’s tip: as your first course of business, get a junior team member to tutor you further on AI. 

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Transcript:

Daan: Last time we talked about joy at work and how to increase it and why it's important. And then actually you referred me to your colleague, Matt, who was the opening guest for this podcast.

And he talked about how AI can play a role in increasing joy and, maybe even more importantly, decreasing toil. Maybe for everyone listening, can you give us a sense of the work that you're doing and why you focus on joy and toil, and perhaps even a peek into the role of AI for that? 

Debbie: Absolutely. So I've been on a mission for many years now to make work work better for employees, and it really got triggered by COVID and seeing how we could work fundamentally differently. And it was good for some people and worse for some people, actually. Like extroverts and really struggled mental health perspective, but we saw during COVID, you can completely reshape how work gets done. And guess what? You could still deliver.

So I've really tripled down in that area to think about how to make work work better for employees. And as we talked about in the last podcast, I really honed in on the concept of enjoying work. Like people say, engagement. Oh yeah. You're talking about engagement.

I'm like, I'm not talking about engagement. Can you define engagement? Dan, are you engaged today? No, like you're already married, right? and so I wanted the term to really be accessible. So that's why I talk about joy at work and enjoying work. So it's not like some people say joy is so fluffy, but it's really about enjoying work.

We didn't talk about this last time because I had more perspective and done more research since then. But what I realized was that when I joined the workforce in the late eighties, it was all about shareholder value. That's everything we did. I was in consulting back then too. It's how we deliver more value for our clients and shareholders.

And then somewhere around mid-mid-nineties into the two thousands, it became all about shareholder value and customer value. Amazon's empty-seated every meeting to say that's the customer. What are they saying? And Satya Nadella turned around Microsoft with customer obsession and stopped being so inwardly focused, and customer value got elevated to shareholder value.

So I could argue that efficiency. Productivity is all about shareholder value. Effectiveness is all about customer value, quality, and innovation. But until now, everyone thinks about employees as a means to the ends, right? We're really robustly focused on our customers, but for our employees, it's just about salary and hours.

And we treat them like an input. And what I'm arguing is that companies have to move to being radically employee-centric, meaning not instead of customer value and shareholder value, but it's one executive I was talking to who said, Oh, my God, Debbie, it's like the third leg of the stool we've all been looking for.

So what I'm trying to get people to do like we did in COVID is just rethink work and how work gets done to focus on efficiency, effectiveness, and employee joy or enjoyment. If people don't like the joy word too much, because it feels too Debbie-fluffy. You're like, okay, I'm sure you're thinking, What does this have to do with Gen AI and AI in technology?

What I'm super excited and super worried about is, let me start with the excitement because I am an optimist. Technology is forcing people to rethink work anyhow. So if there was no technology entering the stage, I would just be pushing people. You have to disrupt what you do, empty the table, and reset it with employee joy in addition to shareholder value and customer joy as a goal. And you would set the table differently, but I have to force people to unset the table and reset it. And why should they do that? The table set is just fine. And by the way, we're in the middle of a meal and eating, so it's really disruptive.

But technology is coming in to disrupt the tablesetting anyhow because companies have to rethink work to take advantage of technology. For the efficiency and effectiveness part. So, I'm super excited that Gen AI and robotics and automation RPA are getting people to fundamentally rethink how work gets done with the technology.

So, that's a huge opportunity to slide enjoyment in there, which is why I love Matt, who is our chief technology officer. He's amazing that he thinks about this stuff because he's really smart and is bringing the joy and toil lens in because what I shared with Matt early on is the same research. I shared in our last podcast.

The people who enjoy their work are half likely to be looking for a new job. So you could cut your attrition in half. That's amazing! And especially around technology work, there is such a shortage that my colleagues put out about how there's like a worldwide shortage of engineers—a huge shortage of engineers.

So if you're dealing with talent shortages, and by the way, there still are talent shortages, even though the labor markets for some what people call knowledge workers—I hate that term—have gotten a little looser, there's still a talent shortage. And so if you're resetting the table for technology, you can slip joy in there. As you reset the table. So that's the optimistic part of me.

The worse cause I'm also like an optimistic warrior. So the worry in me worries that, and I have all the evidence to make me worry, people are going to deploy technology in the pursuit of productivity only. And if you're using the technology, because that's how everyone's talking about it, this is going to get you productivity; it's going to cut costs; you could cut jobs; you could do things faster, better, and cheaper with technology. It's going to make employees worse off.

So it's both an opportunity—a huge opportunity—but also a huge risk. And this is why Matt's been such a good thought partner around saying, Okay, as we go into work with clients on their technology transformation, their gen AI productivity unlock, we have to raise from the very beginning, how do we make this a joy unlock too?

So, I try and literally go in and measure how employees spend their days and their weeks. We have people look at their calendar the week before and say, Okay, these are the types of tasks you do in a typical week: focus work, administrative work, collaborative work, training, coaching, whatever. And how much time do you spend on each of those tasks? How effective are you in each of those tasks? And how much do you enjoy each of those tasks? Because what you want to do is sling Gen AI at the toil.

And so I know from my research that the average office worker desk job spends a day and a half a week on soul-sucking admin work. That's a great place to point gen AI. The average manager spends a day a week. But they also like the focus work managers enjoy. So don't take that away. What you're looking for is the Venn diagram between where you can get a productivity lift because this is about efficiency and effectiveness for sure. But where can you also get an enjoyment lift?

And those are the places to target your Gen AI interventions in what you do. And if you find a productivity lift, but that activity is a source of joy, identity, and fulfillment for an employee, be very careful about how you point the Gen AI at those activities. And it doesn't mean don't point it at it.

If you think of focused work for a while, and one of the things we found in our research is that managers really enjoy their focus work and individual contributors are neutral on it. It's what I call meh. They're meh on focus work. And so we have a couple of hypotheses about why I see our individual contributors are meh on their focus work.

One could be that they love coaching and learning and they're not real in the moment on the job coaching. So that could be one part of it. The other part could be, just think about it: when you're a junior person and you're doing focus work, there's a lot of grunt work to do. You have to clean the data, but by the time you're a manager and you get served up the analysis to review, it's beautiful, it's engaging, and it's thought-provoking.

So maybe with individual contributors, we could find ways to use Gen AI to give them in-the-moment coaching and help when they need it; we could find ways to use Gen AI to take away the grunt work and serve up the data as beautifully as it is when the manager gets it. And that's a way to take something that's meh, take the toil out, increase the joy, the coaching, and elevate that to be more enjoyable for employees. Okay. That was a very long ramble to your one opening question.

Daan: It's super interesting. I think in the HBR article that you and the team recently wrote, you mentioned some numbers. You've actually quantified at what points there is too much toil, and what is the minimum amount of joyful working? I think it was like 4 and 10 hours. 

Debbie: Yeah, exactly. So if you add up what people say about how they spend their time, because one of the questions we ask in our research is, are you looking for a new job?

Daan: Because this again goes back to retention. Would you want to stay? 

Debbie: Exactly. And what was depressing first of all is there is a lot of meh time at work. Like more than half the time, I think is just meh time. So, there's a lot of gray area that you can turn either joyful or toilful.

But then we also looked at how much toil it takes to trigger someone from not looking like I wouldn't even take a call if a headhunter called me to look in, and yeah, if it gets over four hours a week of toil, which means people will take 5-10% of toil.

What's fascinating is since we wrote that paper, and that paper was with office-based workers, what other people call white collar or knowledge workers. So office-based workers, desk jobs. We since did that work with frontline workers, what I call deskless workers, others called blue collar.

But people who are tied to physical location and equipment. So nurses, hotel workers, factory workers, truck drivers, scientists in a lab. And what we found in those roles is that they put up with a lot more toil. They have a lot more toil in their job, and they're willing to put up with more toil.

Why? I think it's sad. It's the nature of the job. So if four hours is enough to take someone from not looking to looking, it's double for a frontline deskless worker. It's 8 hours of toil that takes them from not looking to looking when you get above 8 hours of toil. That means you hate on average one day a week. That's, I think that's a sad state of just societal issues.

That frontline jobs are assumed to be more miserable. That's not okay, but that's where the psyche is. This is just research. They will say no to a job for up to 8 hours. If it gets above eight hours, they start looking.

Daan: Other opportunities for Gen AI as well in the deskless worker segment. So if you're looking at gen AI, most of the studies that are coming out are about “knowledge workers, desk jobs.” They're about, okay, how can we bring AI to the people who are already sitting behind a computer where you can bring in AI quite easily? Do you see an opportunity to bring it to the deskless workers and help them improve their joy?

Debbie: Yeah. And listen, I'm not a technologist. You need to get my colleague Matt back on the podcast for that. But even what I said about on-the-job coaching, like you're in a manufacturing plant and you have an issue. A colleague of mine, Christie Woolsey, who'd also be very interesting to interview. She's an expert in VR. And she's like, Can you, with your glasses, take a picture of the problem and have coaching come out right for how to deal with it on the manufacturing line?

So getting on the job, help, and coaching. I could imagine a combination of technologies that could bring coaching right to the moment when you need it. So you could grow and deliver. I could imagine a combination of AI and automation taking away some of those 8 hours of toil that shouldn't be there. And leaving parts of the job. There's so much going on with digital twins, robotics, and automation, but that then requires us to invest in upskilling the workers that are displaced by that.

Not the whole frontline world is going to be automated tomorrow. There are needs for human interactions, but as we automate, it is looking to take away the toil and amplify the joy, and so things like coaching and learning. Those are joy amplifiers or even just connections. There's a problem. Let me connect you with a colleague around the world who actually solved this problem last week, and all of a sudden you meet someone just like you around the world, and so you could just, I'm making it up. But you could imagine a lot of really toil-reducing, enjoy-creating applications in the physical job world as well.

Daan: One of the other research studies that you and the team have released in the last couple of months or so was around supercharging people. So actually augmenting people with new skills because of Gen AI. So you could totally see it in both dimensions of the desk jobs and the deskless workers. Can you now give someone new abilities that they wouldn't have had?

Because yeah, they can submit a picture and immediately get a read on it. Therefore, they can directly answer a customer or directly consult a prospect rather than having to ask it to the back office team or advisory team that's sitting somewhere behind a computer. So, it's making work more interesting in that sense too.

Debbie: Yeah, exactly. It makes it less rote. It makes you feel less helpless. Yeah. Augmenting is the right word.

Daan: On the desk workers, on the knowledge workers, on that segment, on the other side, there is now also some research because obviously Microsoft and everyone else who's trying to sell this stuff are saying we've done the research and people are more productive and they're happier. 

But there's also some research coming out now that Upwork has studied recently. That shows that some people are actually saying that AI is making them less productive because now they have to learn this whole new technology. And it's really not as intuitive as some of the vendors are trying to position it as what are you seeing there in terms of, the joy of getting a new technology, or is it just another thing that now I need to learn and I need to get, and I don't even understand why.

Debbie: That's a wonderful question, Daan, about: Where is technology making work harder for people? So we talked a lot about what technology can do. It's really important. And I talk about this in the HBR article to talk about how to bring technology into the work.

So let's say you identify a place where technology could be helpful. How do you bring it in? All right. The worst thing to do is have a small team off to the side, figure it out with limited input, and then roll it out everywhere because people will organ reject it because it won't work right because it doesn't fit the reality of day-to-day work. You have to co-create the solutions with the teams for the teams, and even if they're not tech-savvy, they need to feel a part of it.

So they feel ownership, but also because they could test it along the way. They could tell you what the reality of the day-to-day work is. They can proselytize to their friends back on the line or back in the office. Oh my God, I'm developing something really cool next week. Can we get a group of you together to try it out? because I want your feedback.

How you deploy technology and people. I see this all the time because we're doing a ton of this work. They want it really fast, and they want to not disrupt people because they got to keep the business running. That is really penny-wise and pound-foolish because you need to actually take the people who will ultimately be using it and bring them in and create it with them.

It's something I call and I've called for almost a decade of design for adoption. And there's a great quote from a business school classmate of mine and former colleague, Jim Whitehurst, who was CEO of Red Hat. And he wrote a book called The Open Organization. After he went from being COO of Delta Airlines, turning it around after 9/11, a very commanding controller you can imagine, and then went to be CEO of Red Hat, an open source software company where people love being part of it; they even have Red Hat tattoos. Imagine loving it like what an employee-centric organization employees love it so much they tattoo Red Hat on their bodies. That's a little.

Daan: I'm sure after 30 years of BCG you must have at least one BCG somewhere. No, not, still not. 

Debbie: Zippo. I'm not a pro-tattoo person. But he wrote a book because when he got there, he's like, How do I lead here? He realized the power of co-creation, and he had a line in his book when something like this: if you have to do change management, you failed in how you do the work.

I love that because what you do is you have the small team for expediency and not to disrupt working on the technology solution. And then you roll it out, and you assign a change manager to tell people why losing their job is good for them. This will be great. And then, by the time you finish using it, we could fire everyone to your left and your right. And if you're good enough, you get to stay right.

Doesn't make sense. Do the work the right way. So, I've no doubt in the studies that show it's not working back to your question. I digress a lot, but I remember back to your question. I wonder if they did the work the right way.

Daan: So it's not so much as technology itself. So the promise is there. It can help people with desk jobs or deskless jobs. It can help people. But the moment that you have to explain to people and train people extensively and make them not feel scared about a technology, then clearly you're not rolling out the right way. Your point of view is that's exactly where the co-creation comes in.

We've seen this now in a couple of very prominent case studies: the Moderna case study, the Microsoft HR case study, and we recently had the CHRO, Jose Bonitas from Humane AI, on a webinar. And we talked about how his HR team actually built all kinds of AI solutions. And he really left it to them. To say, where is AI going to play a role, and especially around where can it help me do the things I like to do, more and better?

And where can it remove some of the things I don't like to do, which of course in the recruiting team and the TA were all about scheduling and things like that? It's manual reports and all that kind of stuff. 

So when you go to people, they actually welcome it, at least in his case. But then you hear the other side too, where companies say, or a company leader says, Well, I don't want to burden people with that process, and I don't even really know how it works. So what am I going to explain to them? How am I going to bring them in if I don't even know where it is? So there seems to be some resistance to getting everyone involved. What would you say if a client comes with that kind of scenario? 

Debbie: Yeah, like you just like really triggered another Debbie soapbox. I don't really know how it works.

Do not ask your employees to do anything that you wouldn't do yourself and couldn't do yourself. You should be playing with Gen AI. Literally, you know how I write my making work Mondays? My team said, Debbie, we could draft them for you. We know what you want to write about. I'm like, yeah, but I'm a very like colloquial writer. Like I write, how I speak.

And they're like, no worries. We'll make a digi Debbie, and they took everything I've ever written and put it in ChatGPT, custom ChatGPT, and it does the first draft of my making work, work Mondays.

And who hasn't played with ChatGPT? It's super fun. And I've played with it, but I've never created my own custom GPT. So literally, as soon as they told me that I'm like, okay, block an hour on my calendar. I want you to show me how to do it.

And so yesterday this wonderful member of my team, Anjali Agrawal, took me through. She is actually a co-op. She's still in college. So she's at a school where they have co-ops programs. So she's spending time with me, teaching me how to make my own language model. So, I could use it, right? and so we've got to be willing.

So that's my soapbox. You have to always go to work and do the work and be able to do the work. And you don't have to be an expert at it. Like I said, I'm not a technologist at all, but I have to be able to play with the tools. So anyhow, I think that's critically important when you're asking your people to do it.

I think the other thing is if someone says, I don't want to bother people, like I'd bring them up to the macro level. Let's zoom up 10,000 feet. We know we're going to need more technologists and fewer non-technologists. Involving your people is a great upskilling opportunity. Like it is better than making them take a webinar or course on technology or ChatGPT, involve them in building it, involve them in doing it.

There's nothing like doing real work to build the skills they need in the future. And so that's another reason to involve your people, because let's look at the conversation I would have: Okay, we're going to use technology. I've used it. It can do some really cool things. Let's all think about how to deploy it in our day-to-day to take the stuff we hate and enhance—you know, the stuff we love or the stuff we're mad about—make it stuff we love, and in doing it, let's learn new skills, and will we need to change how we do work in the next 5 to 10 years?

Of course, but will these skills be valuable to all of us? Of course. So let's do them together. That's the narrative I'd love to have with my team if I were in my client's shoes.

Daan: I think this was one of the insights in the HBR article that you wrote to recap your study. Managers have a huge impact on how people pick this up, 4x. So share a bit about the data. It's really insightful. 

Debbie: What we were doing is BCG; just like our clients, we're rolling out Gen AI and tools. And so I worked with our administrative staff because anytime you do something with consulting staff, everyone's yeah, but that's not really regular employees. They go from project to project. And there are all these, type A whatever, quick learners. So you have brilliant administrative staff.

We call them the business services team. So I took all of our executive assistants and administrative assistants and took the tools that we're rolling out to help them in their day-to-day work. And we did the baseline survey of how do you spend your time? What do you enjoy? What do you not enjoy? What are you effective at?

Would like to get the data to help understand how we can deploy tools to make their jobs better? And so before we even started, we found in our baseline data that there were teams grouped by manager that were already using Gen AI because we rolled it out in December of last year, already using Gen AI four times as much as those using it, the least.

So already without, we saw a great distribution of how people use Gen AI without any support. And that was a 400% difference from bottom to top. And when we looked at the scatterplot of assistants, it was really driven by what team they're on and who their manager was, which was very interesting.

Then we double-clicked on, okay, so what is it about the managers where the teams are adopting these tools more? Number one is they use it themselves. Back to what I said, like you don't ask someone to do something you want to do yourself. So number one, the manager's using it themselves. Number two is in the separate question in the survey; we asked, Does your manager care about you?

And those managers scored much higher than the teams that were using Gen AI the most; their managers scored much higher in the care, which means there's a trusting relationship and safety.

Like you can mess up. You can get it wrong. You're not going to lose your job. I'll be honest with you. Caring was higher. And then the third thing we found is they took the time to explain why.

Explain why we are doing this. What's in it? So that I found that so insightful, even without any special effort, if you want anything to happen, you have to start with the manager. And then you could look above the manager and the manager's manager. Change has to come from the top, and people have to look up and see things differently before you ask them to do it themselves.

So if your manager is starting to send you things, they do this with ChatGPT, and by the way, I did this with ChatGPT. You're going to be more curious, you're going to want to engage your managers, and you're probably also available as a coach. And so I think there's some really important insight again, back to that how you drive change.

Daan: So first of all, it has to be quite obvious that it's going to help you. That's going to aid you. You're not introducing a technology just because we need you to click certain boxes or do a certain workflow.

This is here to help you. Let's co-create it together. But it doesn't work if a manager just passes on information saying you guys should do it. I'm not a tech person. The managers need to jump in. They need to build their own GPTs. They need to understand how at least the basics of these things work, and they have to find opportunities in their work to apply the technology.

Then you create the environment with care and safety. That people say, Yeah, of course I'm going to pick this up. Of course, I'm going to find opportunities where to use this. 

Debbie: And because it was co-created, it works. So back to the examples where it's actually not helpful. But it is actually not helpful because it wasn't created to work in the nuances of your day-to-day or they didn't think about how you change the day-to-day routines so that it works more.

Daan: Then if it's tailored to your particular workflow, to the things that you need to get done anyway, then that should also be something persistent. So even if people maybe stop using AI, like you said, the AI was just a forcing function to rethink the way you do work. It's probably much more about the structure than it is necessarily just about technology. I know in that article about augmented employees, as your colleagues call it, people use this AI as an exoskeleton, but maybe when you remove that exoskeleton, then the skills have also disappeared. But it sounds like this would be transformational even if you later took out the technology.

Debbie: Exactly. Because it's forcing us to rethink what we do, how we do it, and what's valuable. Like every so often you get to clean out your closet and be like, Do I wear this? Does this spark joy? Marie Kondo?

But not that extreme. But look at our work and say, Is this adding value? Is this enjoyable? Are there better ways to do it? And I think another problem that Matt and I talk about is that people are really incremental with their thinking. Let's look at the current processes and let's, take, fix the current processes.

But there's also bigger thinking of if I had a magic wand, what would work look like, so back to my setting the table analogy, maybe we don't even need to have a meal, maybe we have a bunch of mini-meals, or it doesn't have to be at the breakfast, lunch, and dinner, right?

Maybe we have a different pattern. Maybe there's a better way to get nutrition. Maybe we shouldn't be cooking things. So, if you can fundamentally rethink the work too, and so there's got to be two levels where that one is everything we've been talking about, how do we look at what we do today and what can we make joyful? And how can we take away the toil, and how do you co-create and how do you deploy?

Yes. Absolutely. But there's got to be at the same time saying, Wait a minute, what if we totally rethink it? Know what we need to get done? Are there different ways to get it done? And technology could really unlock some step-thinking.

Daan: So there are much bigger things to come than just letting AI transcribe our meetings. That's exciting too. Wonderful. We've gone to the end of the time. So I'll ask you the three rapid-fire questions. And number one is going to be your favorite AI tool. Although now I think it's going to be digital, Debbie.

Debbie: Yeah. So fun, digital Debbie. Also, actually, I really love the images. My team has made some really fun pictures of digital Debbie with a big hose squirting joy everywhere. So it's very cute.

Daan: Okay. Then, one unique use case for AI in your daily routine. 

Debbie: So, I do a lot of research. I'm part of our BCG Henderson Institute, and I put a lot of questions out there to get me the basic data and facts. And even that Jim Whitehurst quote, I wanted it for something. So I literally went and got the quote—the actual quote, not Debbie's memory of the quote. So, I find that super handy in my research role.

Daan: Okay. And then, one thing that business leaders should do tomorrow, if not today, to get themselves and their teams and their organizations onto the benefits of AI.

Debbie: Like I really enjoyed what I did yesterday with Anjali, find someone super junior who's doing cool stuff and make them sit down and teach you how to do it.

Daan: Sounds perfect. Okay, awesome. Thanks so much for being on. It was great once again.