As emerging technologies accelerate and competitive pressure mounts, today’s leaders face a pivotal moment in digital transformation. SHRM Chief Transformation Officer Andy Biladeau joins the podcast to unpack how disciplined AI adoption, evolving systems architecture, and the need for agile leadership are reshaping how organizations operate. Learn how to align your culture, mindset, and infrastructure to stay future-ready—and discover what steps leaders can take now to build resilient, adaptable teams. In this episode, you’ll learn: - Why agility, not just speed, is key to successful tech adoption. - How systems architecture is redefining operating models. - The critical skill shifts HR and business leaders must prioritize now.
As emerging technologies accelerate and competitive pressure mounts, today’s leaders face a pivotal moment in digital transformation. SHRM Chief Transformation Officer Andy Biladeau joins the podcast to unpack how disciplined AI adoption, evolving systems architecture, and the need for agile leadership are reshaping how organizations operate. Learn how to align your culture, mindset, and infrastructure to stay future-ready—and discover what steps leaders can take now to build resilient, adaptable teams.
In this episode, you’ll learn:
Resources from this week’s episode -
CHRO Priorities and Perspectives, SHRM, 2025:https://www.shrm.org/content/dam/en/shrm/topics-tools/research/shrm-chro-priorities-perspectives-research-report.pdf
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Jerry: I'm Jerry Won. Welcome to Tomorrowist where we explore the trend shaping the future of work. What if the biggest barriers to digital transformation isn't the technology itself, but the mindset? In 2025, companies are pouring resources into AI automation and emerging tech, but without a clear strategy and alignment across the organization, even the best tools can fall flat.
Here to help us unpack what it really takes to lead effective transformation is Andy Billiau, chief Transformation Officer at SHRM.
Andy, welcome to Tomorrowist.
Andy: Hey Jerry, [00:01:00] thank you so much for having me. Really excited to talk to you and the audience today.
Jerry: Um, I'm excited for this. Um, so let's lay the groundwork a little bit. Um, the 2025 SHRM report says 90% of CHROs expect AI integration in the workplace to become more prevalent this year. And I think that 90% number is low. Um, 87% foresee AI playing a critical role in boosting workforce productivity. And highlighting confidence in the potential of emerging tech to drive widespread organization benefits.
And, and I think, you know, given what we know professionally and even personally on how we use AI and what we hear about ai, those are things that, you know, we'd be willing to bet on. Um, but as, as we mentioned, um, and, and sort of it needs to be both the human side and the tech side. And so to you, Andy, what stands out about the digital transformation conversations you are having, uh, these days?
And what, what shifts have you noticed even just a few years ago or even a few months ago?
Andy: Yeah. You know, we're right in the middle of this right now, Jerry, and I think it feels like it's really the tsunami is hitting the shore in terms of the [00:02:00] impacts on the workforce and skills and the HR function itself and how that's. Essentially becoming, uh, necessary to adopt this technology really rapidly without a full understanding perhaps of all of the implications or applications of where it might be valuable.
Um, and so while we do feel like everything is hitting all at once, because I. If you rewind the clock to a year ago, it was feeling like this was a hurry up and wait situation where there was a lot of media coverage on it. There were some case studies coming out, but nothing to the effect of what we're seeing today in terms of the volume and impact the company's reporting around the way AI is impacting their workforce.
Um, as I think about kind of where this is in terms of the long range implementation of the technology, I still think that we're ver very early on in the journey. Um, and so while it feels like a lot is happening all at once, seemingly every day there's a new story about an advance forward in, uh, the technology or a company leveraging AI in different ways or the [00:03:00] impact on their employee population.
I do think that there is still a little bit of, um. AI washing going on in terms of how much this is directly hitting, uh, kind of the, the p and l statements of organizations. But the way I would frame it up is we're definitely a lot farther down the road than we were a year ago, and yet I don't know that we're, as far as maybe some of, uh, the headlines would lead you to believe.
Jerry: You know, it's interesting 'cause we, what we hear, you know, and we don't hear everything in the news, but we hear the headlines of, you know, executives. Telling their employees, Hey, how are you going to do this better than ai? Or, you know, asking sort of the, um, binary seeming questions of are you needed? And I think it's, it's both the integration of AI into the existing work streams, but also looking at for, for leaders, you know, do we hire, how do we hire, what do we hire for?
And as we've often heard it, it's not that the AI is going to replace us, it's going to, I. Be more [00:04:00] likely that will be replaced by people who know how to leverage ai. Right. And so, as we've just mentioned, it's critically important to talk about the, that the human aspect of it or sort of the, you know, the, the secondary effects, secondary order effects of what AI will do.
Um, and. You know, we're, we're talking in June now. Uh, we can talk in July and have a completely different conversation because just the, the speed at which the tools are being developed and more so the adoption, uh, particularly at the enterprise level, um, and the startups and the other enterprises that are creating tools for large organizations to use are only going to be, uh, even faster, uh, in, in terms of development and adoption.
Um. You know, when, when we talk about, and when organizations talk about digital transformation, um, obviously it, it's, you know, the tools are, are the things, um, but the people and then the mindset is just as critical, if not more. Uh, what mindset shifts do you believe are most important for leaders and their teams to embrace now?
Andy: Sure. [00:05:00] So I mean, we're experiencing this firsthand at SHRM ourselves, right? As we start to understand and learn more about the technology itself. And then furthermore, the application of the technology or the use cases, or the places in the organization where. We might be able to achieve efficiencies or productivity gains.
Um, so I think that if you break it down, you know, by level of the organization at the top of the house, senior leaders obviously right now have a heavy emphasis and focus on efficiency gains and productivity and output. I. I think those are very valid pieces of the puzzle when it comes to ai. The reality though, is that if you dig deeper within the organization, you're seeing a decentralized adoption of the technology, meaning that across different teams or functions, leaders have put these tools into employees' hands and allowed them to figure out what the best application or use case for those tools might be.
And I think when you do a decentralized implementation. You're also gonna experience places where there's increases in adoption organically because maybe you have some curious people or there's an obvious use case for the technology. [00:06:00] And so you're gonna see rapid adoption there and, and you know, really quick uptake and perhaps those efficiency or productivity gains.
And so, you know, on the bell curve of distribution, yes there, there's definitely going to be spots where you have those early adopters, but I also think you have as any other change, right? I mean, what's old is new again, you have kind of this middle, uh. Portion of the bell curve where I think people are experimenting with it, finding ways to use it, finding ways to apply it, but I don't know that always it's necessarily generating the productivity gains that people assume would go along with it.
Meaning, I'll give you a couple examples, right? The first is if I'm able to write emails faster or if I'm able to generate business cases quicker, or run analysis or do research faster, yes, I can actually. Achieve more output, but in terms of volume and hours in the day, it's not necessarily removed or given us back.
I think the time that we maybe necessarily thought it might, we found new and clever ways to fill that time in with other activities, and so I think that I. [00:07:00] There's a little bit of this false notion out there that, you know, we're gonna get this massive time give back, and that the efficiency gains are gonna give us a remainder of capacity that we're gonna be able to reapply to, to more activities.
Now I think that will come over time, but I think that you're only seeing that in pockets of the organization right now. Um, so I would say at the team and individual level, that's the distribution. And then I think at the far end of the bell curve, you do have. A, a cohort of resistance, right? In individuals that maybe they're not as curious about it, maybe they don't necessarily wanna get their hands on it and try it out, or there's an element to creativity in this, which is, it really is a blank canvas in a lot of ways.
And so if you're not the type of person who's gonna go in and experiment and go back to the tool over and over. Uh, you know, it's probably gonna sit off to the side for you and you're gonna lean on your old workflows or you know, the current workflows that you, you currently own and operate. And so I think that's the distribution that we're seeing right as, as sort of any standard deviation would, would map out to.
[00:08:00] Um, I, I will say though, Jerry, in the early adopters like that, that super user category. Those individuals we found at H rm. And then from talking to other organizations, they're the ones who can actually do a lot of the education and on the ground organic adoption, um, across the organization because they've experienced kind of that change curve themselves.
And so even within SHRM, I see the, the, the easy way to spot these folks is they're the ones running to everybody's desk, showing them what cool feature or use case they've discovered. And so again, it's neat to watch people get excited and enthusiastic about these tools, but I still think we're just at the tip of the iceberg in terms of adoption across the organization.
Jerry: I think you bring up a fascinating point, right, and I think, you know, we should just remind the audience as reminding ourselves when we talk about early adopters and people. Hesitant or resistant. Um, it's not a generational thing, right? It's 'cause sometimes
we think certain types of people are, are more akin to adopting new things.
Um, but that curiosity and that capability run run across the gamut. But I'm, I'm curious to get your take on these two [00:09:00] things, right? Because, um, as a leader at SHRM U are, you know, navigating internal things to build Sherman to a more adaptable and, and future ready organization, and yet we're exposed to so many organizations, whether they be members or, or clients or even peers in the industry.
Um, they're probably early adopters and. Hyperactive users who are probably using tools that their team leaders don't even know exist. Right? 'cause there's a new, uh, not even a new hundreds of new, uh, apps that are coming up every day. And then you have on the other end people who are probably hesitant, not because of their reluctance to learn, but probably as a matter of self survival, right?
What if the thing that I am learning or being asked to learn replaces me one day, right? In, in some of the more clerical tasks or things that they are hesitant, right? And, and, and we see this a lot across other. Uh, whether it's technology or tools, as people get closer to retirement or at the end of their tenure, they are hesitant to learn things because they believe or they were told by somebody that, that it will accelerate their exit.
And so how [00:10:00] do we build this sort of trust on both sides of, um, encouraging people to use, uh, testing new things? Um, being wary of testing out too many things on one end for the hyper users and on the other end, you know, giving people some sort of peace of mind or reminder of, you know, um, psychological or even organizational safety as they are asked to, you know, adopt new things that they weren't, uh, you know, that they spent decades perhaps, uh, working in without.
Andy: Yeah. Okay. So two things you said that I would love to unpack, right? The first one is around kind of this, this generational piece. Um, again, I can tell you both with SHRM as an internal case study and having talked to many clients about this. You know, that is absolutely not the way adoption is breaking down.
As along the generational, uh, categories, we're actually seeing a lot of usage by more tenured employees. And I think you said something really insightful as the reason why behind that is sometimes individuals who have been in the [00:11:00] organization for a longer period of time just have amassed more institutional knowledge.
And so they're actually able to understand the mechanics of a lot of the processes and how work actually is getting done and executed. And so they're the ones who are able to identify and spot the places where AI is gonna have the biggest impact or drive the most efficiency. And so I think it's a complete misnomer that this is a, a, a generational adoption, uh, challenge that, that organizations are having.
Um, so that's like piece one. I think piece two is your question about how do people who are maybe a little bit hesitant to use the tools. Because they don't wanna work their way out of obsolescence. And I, I think it's related to the mindset point around if you really, truly view your job or your role as a set of tasks or activities, I think that's a very limited view of the impact that you can have on an organization.
And instead, if you were to flip it to. I'm going to get into this tool. I'm gonna learn how to use it so that I can develop a skill that's then transferable to any number of other [00:12:00] tasks or activities. Right? And that's going to make me more valuable, both internally and in the external market. And so that mindset shift that you're talking about of, for those who are maybe a little bit resistant, I would encourage some of those individuals, if they're listening to this, that.
Look at this as an opportunity to develop a new skill that might be applicable in ways you never thought you would be able to provide value to an organization. Meaning if you are a super user of ai, you're gonna be able to help other individuals find pockets of knowledge that they could automate or exp speed, uh, or, uh, expedite using ai.
And that's gonna make you really valuable and indispensable to the organization. I can tell you what is potentially gonna make you less valuable to the organization over time as being a process owner or a workflow owner or a task owner, because again, those are spots where AI is just really ripe to disrupt those types of, uh, types of areas.
Jerry: On the part of the audience or the [00:13:00] population that wants to test out everything, um, the. Introduction of new tools is, is, uh, almost, I don't wanna say vertical. Yeah. But it, it's pretty, you know, hockey stick esque in, in terms of what's available today. Um, you know, I, how how would leaders and how do you advise leaders on balancing, uh, you know, competitive advantage by being the first to adopt or even acquire?
Um, as we're seeing a lot, um. AI tools or companies to make things proprietary for advantage reasons, um, versus the FOMO of, you know, an unproven technology. Um, something that could, you know, really put the, uh, institution at risk for dependence on something that may, you know, for a lot of different reasons, whether it's who owns the data or, you know, what, what it takes to get the job done.
Um, how, how do we when, when people are judged again on. Sort of a quick timeline of a quarterly performance basis as many of our, you know, listeners are. [00:14:00] Um, that's gotta be an impossible balance of sort of figuring out what the right is. Um, how, how do you deal with that and how do you advise clients and, and sort of navigating that balance?
I.
Andy: so as part of my role, I oversee technology for the organization, and that is certainly all of our systems, tools, applications, infrastructure. I. And security. And so when we started our AI journey, we deliberately sat down with legal and had an extensive conversation around what are the guardrails that we wanna put around the intake of these tools into the company?
Because I think you're exactly right that you are seeing a lot of startups show up on the scene with a great demo or a great offering, um, their ability to scale, right? It still remains to be seen, but if they get in front of a business leader or someone who has purchasing power. What's that vetting process to make sure that we don't, through procurement, bring something into our ecosystem or our architecture that's gonna put us at risk.
And so working hand in hand with our legal function, [00:15:00] identifying what are our requirements for bringing any type of new tool or technology into the organization that has an AI component to it. So that was, that was very foundational to everything that we did, and I think that served us really well because it gives us a baseline for when there is an application that's put up for intake, we have some sort of sounding board to bounce it against to say, this meets our standards, or it does not.
And so I think, you know, outta the gate, that's, that's a very important thing to establish. Now what I will say is because these tools are very freely available, right? It is very difficult to have a tight firewall around anything. Um, that someone can go swipe their credit card for, to your point, right?
And so I think you have to have strategies around how you mitigate that risk. Um, so that's kind of the, the security and infrastructure side of it. Um, I think when you talk about this competitive differentiation, how does a company leverage this technology to give them a competitive advantage in the market?
Um, you know. What I see happening right now is that the way that our [00:16:00] organizations have been historically structured around these teams and functions and domains, so sales, finance, marketing, operations, supply chain, human resources. All of those respective domains have built systems to support their function, right?
And so within finance and supply chain, you are heavily dependent on your ERP system. Within sales, you're heavily dependent on your CRM system. Within HR, we love our HCM system and all of our tools that support our, our functions like learning development, talent acquisition, total rewards, talent management.
So what you've seen over the past 10 years is companies build their technology footprint aligned to these vertical domains, and they've solved for the horizontal collaboration challenge through integrations, which I think was the only suitable solution that we had available to us at the time. But if you look down the road at where this is going, Jerry, all of those. Functional systems are starting to merge together, right? [00:17:00] And so that does a number of things that have, it has a few knockdown effects. From a technology perspective. We need to be really smart about where our data lives, where it flows, who's consuming that data, who's generating that data, what are the security protocols around that data?
Because as these systems merge, that's gonna be the fuel that is going to go provide solutions to the end user to do the transaction that they want to execute. Or they wanna automate. So I, I think you have to be realistic about, okay, if these systems are merging and we have to really understand the data flows and data integrations around them, how is our architecture set up to be flexible to enable that so that we can be AI ready?
So from a systems perspective, that's how we think about it from a human perspective, right? From a a skills, capabilities perspective. You start to realize that as those systems come together. So do the skills across those different teams and your operating model also has to start to function in a much more integrated way.
Right. And so if my expertise and [00:18:00] value to the organization historically was that I knew how to execute HR transactions in the HCM system, and that system is now merged with four other enterprise systems. I have to operate much more as a generalist and I have to understand those other areas of the business.
So I, I can pick up on the upstream and downstream impacts of what I'm doing in my part of the system. And. I think what you're gonna start to see over time is this turn into the need for HR and other functions to just operate in a lot more collaborative fashion, right? Because if we agree that all of these systems are going to integrate more smoothly over time, well, that means that our teams are gonna need to be a reflection of that and our org structures and our operating models are gonna need to reflect that.
It's really interesting because the first 15 years of this enterprise architecture development was the organization configuring architecture into their systems. I think the next 15 years, the architecture of the systems is gonna [00:19:00] dictate the org structure and operating models of organizations. And so that's a massive shift in terms of the way people think about their roles, think about the, work that they execute, how they interact with other teams.
And I think it's gonna pose a lot of really new and interesting challenges for HR over the next, call it five, ten, fifteen years.
Jerry: On that note, what, what is the advice and what are you seeing in terms of both, you know, re-skilling or, um, adding new skills to existing workforces? As the workforce and organizations turn, as you just mentioned, Andy, sort of this, you gotta be a, a Swiss army knife. You have to know a lot of different things and you're not gonna be a domain expert in one thing.
And, and maybe we're, we're seeing the last of sort of a, a vertical ascent, a a. Strictly vertical ascend in terms of function, expertise. Um, and as organizations look towards adding new people to the organizations, you know, here we are, right? In the graduation season, right? Like, what, what can, what can we do?
And, and advise [00:20:00] both people in the workforce now and people just entering, uh, when, when we've been historically taught that you gotta learn one thing really, really well, and then you're gonna want to become the best at that. And, and now the technology is forcing us. To, to be more generalist and to, you know, play, uh, better, not nicer, but better with others, and understand a, a more breadth of expertise.
Um, how can we do that in a quick way that also doesn't take away from our domain expertise and being really great at what we already know.
Andy: Yeah, I think Jerry, that's a really big question that we're all learning our way through, and I think it goes back to reimagining our talent, our approach to talent development as organizations. Because you know, there were always historically two alternative approaches, or a blend of two approaches in terms of talent development, right?
It's either I wanna develop someone vertically through that functional career ladder, and at each level they deepen their technical skills, but they also build. Requisite leadership skills to take on larger and larger remits. That, [00:21:00] that's model A. Model B is I wanna do rotational programs, I wanna get people exposed to all different areas of the business.
So there's, they're very well-rounded and what they may lack in technical depth in any one specific area they actually make up for in their ability to spot patterns and connect dots across the enterprise. Um, so two different models of career development or talent development. And I think over the past five or 10 years.
HR has been really forward thinking about how do I blend those two talent models to create career lattice for individuals to get both technical expertise in their functional area, but also breadth across the organization. What this technology is gonna do because it's moving faster than the organization can evolve, is I think it's going to force HR leaders to figure out how do I take someone who has neither technical depth nor cross-functional exposure yet, and I.
I do need them to have technical expertise because I think you build a lot of skills by going deep in a specific function or [00:22:00] domain, right? Uh, I, I think anybody who has spent time on mastery or trying to learn a specific area realizes that by going deep, you actually go wide because you have to go through this complex problem solving process.
So I think that's the challenge is how do I give somebody that experience of getting. The technical expertise that's gonna make them an expert on the other side when information comes through the system. But then how do I build a, a generalist who can connect dots and be a pattern recognition machine to say, based on my expertise in this area, I know there's a downstream impact, three teams over.
Um, and have the ability to make that, that connection. I think that's gonna be the talent development cha challenge that HR is gonna have to solve for over the next 10 years.
Jerry: And, uh, it will evolve, right? Because everything will, will change. And, um, you know, but I'm glad that we're talking about things that aren't necessarily tools based, right? As we mentioned sort of at the top of the talk, um, the, these are challenges that organizations and [00:23:00] leaders have faced for a long time.
It just seems that the, even the, the. Pace at which we are having to adapt and evolve even in talking about this is being accelerated. Um, you know, two more things as we wrap here, Andy. I think, you know, technology is again accelerating at a pace that we haven't seen before. Uh, leaders wanna make sure that they're on top of it.
And even after all that we've talked about of vetting it and making sure that we are either developing it internally or buying an outside system, um, you, you want there to be adoption. And so, you know, or most organizations go through, you know, transformation campaigns, right? Hey, we're going to this new platform, we're changing into this thing.
Don't put your hours there, expense it here. Um, and. At, at the rate that things are going. Um, how do we hedge against or prepare for transformation fatigue? How do we make sure that we are, you know, um, the, the story that we grew up with, right? The boy who cried wolf, like, this is the next thing. That's the next thing I know last quarter we said that.
And, um, that that can burn out leaders and its [00:24:00] teams. Um, how do we balance that? And again, this is a, um, impossible balance between, uh, risk, right? Speed. Versus having security and knowing that you're making the right bets. Um, how, how do you balance that?
Andy: Jerry, it sounds like you grew up in the same world of transformation. That I did. Um, and I, I affectionately describe it of, you know, point A to point B transformation where, you know, I, I started my career in management consulting and, you know, transformation. Um, that meant we're gonna go to a client and we're gonna implement a new system and we're gonna build, you know, a project plan and there's gonna be a go live date and we're gonna change the operating model and there's new processes and we've gotta train people and we've gotta communicate to 'em.
And I think that really was the old model of transformation. I think the new model of transformation exactly to your point is technology's moving so fast that we don't have, you know, a six month runway to go live. It's go live every week in terms of something new, right? Or some new requirement. And [00:25:00] what it requires is back to that mindset piece.
You know, leaders don't have all the answers right now. They don't necessarily know what's around the corner. Right. And I think they're getting a lot of. Conflicting input and ca and counsel on when this impact is going to hit. And so I think what it's forcing leaders to do is operate in a truly agile fashion.
Now, when I say agile, what I mean is I. It implies that you're able to make quick decisions and you are, but it also requires you to make those decisions based on data in front of you of I'm making choice A or choice B in terms of prioritization. And I think the companies that are gonna succeed over the next few years implementing AI within their companies are those that are recognizing when they're making those choices that they're saying no to things and being very conscientious and intentional about saying no to things because.
Agility doesn't mean saying yes to everything. It means I make the best decision in that moment in time based on the information that I have and where I think we're moving. But I also [00:26:00] reserve the right to change that decision or go in a different direction because new information comes up on a regular basis.
I. Now in order to do that effectively, it also requires having an underlying system and structure so that you're able to see that data, you're able to understand those implications when you make a decision. You have a mental model for how that's gonna affect different parts of the company. And I think it's really operating with a CEO mindset to say, as a leadership team.
When we make a decision about where AI is going to have an impact, we also have to be able to understand what that's going to do to other parts of the company. But we also have to figure out what are we gonna take off of people's plate in order to create capacity for them to do that work? Because I think one challenge that's going to start to surface for.
Leaders and organizations is this abundance of ideas that's going to be generated from ai because the barrier to creating a new idea now is a prompt away. And so if [00:27:00] I have a hundred people on my team and they're all generating multiple ideas on a regular basis. What is that filter or decision criteria that we're gonna use to prioritize?
Because we could very quickly find ourselves overwhelmed by new ideas and new opportunities. And so I actually think one of the superpowers that's gonna be required in this new age of leadership is going to be. Disciplined approach around prioritization. Um, and again, that's always been a, a very core competency of leadership.
But I think when you have more options on the table, seemingly infinite options on the table, those who are gonna be able to stay disciplined and focused and prioritized and make sure the organization understands and aligns to a clear common direction, they will have a competitive advantage in the market.
Jerry: Um, I love this conversation and, uh, you know, as a, as a fellow former consultant, I, uh. I'm excited to see, let's, let's call it how even the consulting firms adapt, right? Because they have the tough task of advising companies and all the things that we [00:28:00] talked about while trying to, uh, adapt and, and morph themselves, right?
And, and to, um, be the experts in, in fields that are, are ever, ever changing. Um, we're out of time today, but the exciting thing is, uh, we'll, we'll see you in San Diego. We'll see, uh, tens of thousands of our best friends in San Diego as we continue these conversations and. Um, as we talked about, the topics may change, but the underlying, uh, priorities to make this about the culture and about the mindset center, about the people will always be.
Uh, and Andy, as we close out this episode of Tomorrowist, uh, what is the one thing that leaders can do to tomorrow, uh, to better position their organizations, their teams and themselves, uh, to make them ready for the future of digital transformation?
Andy: I think it's. Being a little bit vulnerable, right? E expressing to your teams that you don't have all the answers, you are not necessarily sure where this is all headed. There is no blueprint, right to our conversation about, um, no longer is this a point A to point B transformation. [00:29:00] Uh, and so I think that's step one.
And then step two, I think it's being really clear about how you are making decisions. I think that employees appreciate that if they understand how you are prioritizing and the way that you are thinking about approaching and tackling these challenges. They give you a lot of grace in terms of. Look, there's a lot of unknowns right now, but if I have confidence and assurance and trust that I know how you're making the decisions, there's a rational explanation for the choices and choices out that you make.
And so I think step one, vulnerability. I think step two is just being very transparent about how you're making decisions, what you're factoring in, and what you're prioritizing.
Jerry: Awesome. Andy Bedo, chiefs transformation. Officer at SHRM, thank you so much for your thoughts. Um, we are excited, anxious, and excited for what's to come in our world as we, uh, continue to learn as our, ourselves, and, and lead organizations, uh, in the world of digital transformation. Thanks for your time today, and we'll see you tomorrow.
Andy: Appreciate it, Jerry. Thanks for having me.
[00:30:00]