Andreas Welsch: 0:30

Today we'll talk about how to lead when AI creates uncertainty in the workplace, and who better to talk about it than someone who's helping companies develop digital strategies and lead innovation around AI, Alison McCauley. Hey Alison. Thank you so much for joining.

Alison McCauley: 0:44

I've been looking forward to this conversation.

Andreas Welsch: 0:47

Awesome. That makes two of us. And I hope for those of you in the audience, you're just as excited as we are, but Alison, maybe not everybody in the audience knows you, yet. Why don't you tell us a little bit about yourself, who you are and what you do?

Alison McCauley: 0:59

Sure. I have spent my entire career at this really exciting intersection of emerging technology and human behavior. So how it affects emerging technology affects us as people, as individuals, and as organizations, as teams, as culture and society. And so I have to say it's never been more interesting than it is right now. I begin my career at the when the field of change management was just forming. And it's been fascinating to see how some things have stayed the same since those early days when we were really literally writing the playbook for change management. And some things are brand new and it, I started working in AI in 2010. Very different times, very different kind of space. And so it's been really fascinating how things have changed over these last couple years. And it is truly a whole new area that needs to be navigated. And so that's why this topic that we're talking about today is the topic of, the era.

Andreas Welsch: 2:08

Wonderful. I couldn't agree more. There's so much talk about tech in bringing it to the business, but at the end of the day, hey, there, there's still people there that need to adopt it, that need to get comfortable with it, that also need to help other people manage the change and lead through it when you know. Probably very few of us have the answer of what does it mean, where are we going? So I'm looking forward to digging a little deeper there and learning from you and from your insights.

Alison McCauley: 2:34

Wonderful. Yeah.

Andreas Welsch: 2:35

Why don't we play a little game to kick things off. What do you say?

Alison McCauley: 2:38

A little improv maybe.

Andreas Welsch: 2:40

A little improv. Exactly. When I hit the buzzer, the wheels will start spinning and you'll see a sentence I'd like for you to answer with the first thing that comes to mind and why, in your own words, to make it a little more interesting. You only have 60 seconds for your answer. For those of you watching us live, please drop your answer and why in the chat as well. Alison, are you ready for, What's the BUZZ?

Alison McCauley: 3:01

Let's do it.

Andreas Welsch: 3:02

Okay. Let's see. Here we go. If AI were a color, what would it be and why?

Alison McCauley: 3:11

Wow. Okay there's some colors that are that are yet to be discovered. And we hear about these occasionally and I have a feeling that AI is a color that we haven't quite seen yet. It's forming.

Andreas Welsch: 3:33

Oh, love it.

Alison McCauley: 3:34

So I think, we'll, we can't turn, I think, to what we already know. I think it's gonna be something that is new that we all discover.

Andreas Welsch: 3:44

Wonderful. I like that. You know what, when I ask my children, what's your favorite color? The answer I've recently been getting is: rainbow. All the colors of the rainbow. I love rainbow color. So definitely, there's a lot to be discovered. And I was lucky Il and I feel like the colors can change very quickly as well as things evolve and adapt.

Alison McCauley: 4:05

Yeah. And these analogies actually are really apt, because AI is adapting and changing so quickly and there's so much to be discovered that we're all discovering together because this new acceleration is so new. Yeah.

Andreas Welsch: 4:20

This newness and this newness factor also creates a lot of uncertainty and a lot of changes. We, we've seen in the last couple weeks a lot of coverage about how recruiting for entry level jobs is slowing down because of AI driven automation. Companies are looking to do more with AI, more entry level tasks, things that are a little more complex than if this happens, then do that. Great. Yes, AI can do that. AI can also help professionals and senior experts on more complex tasks. So we'll likely see this trend going up the hierarchy, if you will, or seniority levels of what AI can do. And that also creates a good amount of uncertainty and fear about jobs, not just AI. I just graduated where I find a job. Those are some of the conversations that I'm having with students where I teach as an adjunct, but also more senior professionals. What are you seeing when you talk to leaders in organizations about these topics? What AI means for jobs for organizations? What are people seeing?

Alison McCauley: 5:16

Yeah. There's a big disconnect between what is possible and, what has been newly unlocked with AI and where organizations are right now? So when I talk to different organizations, I travel around the world giving talks and workshops. There's a range of where people are. If I may on Andreas, be very direct through your, viewers are, okay with that. I just wanna be really direct at every. Job is going to change every job. So CEO jobs are gonna change. Middle management jobs are gonna change. Entry-level jobs are gonna change, and we haven't quite ingested that and we haven't quite. We haven't quite taken that in and we certainly don't know yet exactly how they will change. Some are gonna adjust, some will adjust to this. Some people will adjust to this. Some organizations will adjust to this. Some teams will, adjust to this and some just won't. And some jobs. Will disappear and new jobs will be created, and we just don't know exactly how. And we've seen shifts like this before. So the industrial revolution before, before the Industrial Revolution, we were a largely agrarian economy. And that shifted and every single role, every single job, every single industry changed. And now we're at the beginning of this cognitive revolution. But we don't know where it's headed. And when you look back at the industrial Revolution, it's almost like it unfolded with this like choreography that was so well orchestrated, but it happened over 80 years. And now what we're seeing is in the matter of just a few years, or even in some cases a few quarters, it's it's changing fast. And so that, that throws people for a loop. And what I see when I, when I. Talk to organizations is that no one's figured this out yet. We're all, figuring this out together. Those that are better equipped to see what's happening at that front edge of change are those that have their hands in it and are leaping into the unknown. So I really advocate for that because you need to see change as it happens. The best way is to get your hands in it and really work to understand it.

Andreas Welsch: 7:43

I love that call to action, right? A lot of times it's really about seeing and feeling so that on one hand you can either believe or you can also understand. What does it actually mean? What does it do? What are the opportunities? What are maybe some of the challenges where this sounds more like a big promise, but I know that here could be some some holes that we might run into. It's also been a couple decades since we've changed how switchboards work and switchboard operators, right, that were superseded by technology or people pressing the button for you in the elevator. And must say it was in New York City the other day for a tech event and there was actually a person pressing the right button on the elevator. So we got off on the right floor. But we know that these are more exceptions these days than, the norm. But I also feel that from the industrial revolution some of the robotics in the seventies in many other evolutions it feels like it's never been that fast or also it's been so far and so long ago that very few of us actually relate to this. So for our generation now in the workforce in those going into the workforce, this is really new. It's the first time that there is such a big monumental change that's happening with us and to us.

Alison McCauley: 8:57

It's fascinating. We forget every single time there's a transformative technology. We forget how how much it changes us and also how every single change of that magnitude comes with a combination of fear and excitement. So you mentioned elevator buttons. You know when, things were first electrified, when electricity first. Came to us. It was met with fear and excitement. The president of the United States, when electricity was first installed in the White House, would not switch the lights on. He had his staff do it'cause he was scared of it. It's just, it's that combination. It's just that it's hurtling towards us so fast. And that's also because it's changing so quickly. That's why it's important to be in it because things change. Sometimes week to week, but definitely quarter to quarter. And if you're not in it, you don't see it. Someone else, your competitor might, that's very true.

Andreas Welsch: 9:57

We're seeing that a lot and even competitors that are not even born yet are jumping on this. And, will at some point we'll go into spaces that are underserved. But I'm curious what do you recommend in addition to getting hands-on how can leaders support the teams and organizations on this journey? And, maybe right from a team to org unit, company level. There many different layers of of, that complexity if you will, how can leaders under support their organizations?

Alison McCauley: 10:27

So that's such a huge question. I have several different methodologies to get at different angles of that. And so I'll give some hints on some of those or over summer of some of those. But then I also wanna talk bigger picture about it as well.'cause there's, a lot of opportunity to step back and think about it. As I mentioned earlier, I have been, working in change management and digital change since the very beginning of that profession when it was first codified into a formal profession. And a lot of the lessons that we developed in some of our first playbooks are still valid. And so what's really critical? Is to meet people where they are. So people all across your organization are all different levels of understanding of what's happening in this organization. We need to meet people where they are. So you need to understand where they are, and you've got people in your organization who are. Maybe even using this in their personal lives to do all kinds of exciting things. That's incredible expertise that you can tap into. These are passionista that could be nurtured into change agents. And so mapping in your organization, who's using what? Where's the passion, where's the understanding is one way to start to. Bring your organization to build the AI muscle of your organization. Another piece that we could talk, about a lot more is how you connect to value. So we tend to talk about AI as technology. Of course it's a technology, but the real opportunity and where the unlocks really happen in an organization are when we start talking about. What is the real business need that you have in your organization and focus there. So put aside the technology. Focus on where the business need are. What could we do without constraints? What what would we do if we could remove blocks and barriers that we have today? What would we be able to achieve? And then start the AI conversation from that focal point. So that's about really showing people how to get to value in it. That changes everything. And the other piece is about really patiently showing people the way this always takes longer than people think. Once you understand AI, you think, oh, everybody gets this. It's so obvious'cause you get bombarded in your echo chamber around AI. But. Truly people need a long time to be able to understand how to move in that direction. And so I emphasize a, whole arsenal of change, manage techniques around being able to create learning circles. And sharing networks, storytelling, feedback loops. So there's a whole bunch of organizational mechanisms that we can put in place that have a huge impact. So anyway, those are some of the little summary of some tips and tricks. But just to bump it up a level, I'd say that, so when I give talks, one of the big. Surprises that a lot of leaders tell, a lot of leaders tell me they were surprised by afterwards in, the q and a and the discussions are how important expertise is in this moment. We're in a world where AI can generates a lot of it mixed things up. It can, it still hallucinates, right? And only your experts in the organization can really identify. AI garbage for what it is.'cause it presents it in a way that feels really great. You were talking earlier about entry level and some of the challenges for entry level. People without the experience can't identify AI slop and AI junk for what it is. It's your experts that can, so your experts are the one who can understand how do we leverage this technology? And you have experts all over your organization at every single level, every single functional area, every single department. And being able to equip your experts with the knowledge to use AI is what unlocks the opportunity. They're able to navigate the systems and no matter what organization at this point in time, you probably could use more expertise. And so if you experts understand how to use AI to amplify the knowledge they have, if they're able to really, truly. Orchestrate these systems to make it work In that way, you un you amplify your expertise. And so that's so much of the opportunity around here. And then the other thing that I would really encourage leaders to do, and this takes some time, is that we have there's an opportunity in this moment, not just to automate. Today's AI is not just about automation and we have 30 years of experience. With automation more than 30 years, but like a real focus around 30 years of, expertise around automation that works in a certain way. This new AI allows us to do things in a completely different way, so we need to, dig into our imagination around reimagine what we can accomplish and what we can achieve as humans in an organization because we now have these capabilities, and right now there's a real. Deficit of imagination. We're not tapping into that. We're in reactive mode. We're not in, in in, this space where we're really understanding how could we go next level? What new products and services can we introduce? What new industries can we create? Because we now have these tools. And so that's the other piece is. To really tap into what's this? What can we make out of this? What can we do when we no longer have the cognitive limitations that organizations have been governed by forever?

Andreas Welsch: 17:02

That's such a great overview. I've brought generative AI in into the classroom where I teach undergrads in business, how do we actually use these tools? In last fall, we talked about prompting techniques, and we talked about ChatGPT and Anthropic, and probably half of the class, maybe a little less than half, said yes I've used these tools before, but I would love to learn more how I use them properly. This spring, 95% of students in the class raised their hand when I asked who's used it before, and they said can we move on and not talk so much about prompting techniques and, what else can I do with it? So on one hand right there, there's this incredible trajectory that even students and, younger people are on to incorporate that into their daily work. And we need to talk a lot about responsible use. And there's some good studies about your brain on ChatGPT, what do you actually retain and learn? But the interesting part there for me was when I said can you create, for example a, sample questions that a recruiter might ask you about a certain job that you might apply for as an intern? And, then I asked them, what do you think about the response? How was chat, GT's response or cloud's response? And my students said it was good. And I said what do you mean? It was good? Oh, yeah. It, gave me what I asked. I got a list of questions. Okay. Are the questions specific? Are they helpful? Do you think they will ask you and they said I don't know. Yeah, I think they're good. So what I realized is similar to what you shared, that depending on your expertise and, I'm seeing this in corporate trainings a lot where professionals are able to discern, is this good quality? Is this okay? Or is it really bad? Unless you have a rule rubric or some kind of a reference frame of what does good actually look like? It's really, hard to discern. Is this actually valuable, useful, good, or is it just finer total garbage? So that value of expertise and experience, what you mentioned, I think is incredibly important. And to me that's a stark contrast with this push that we're seeing from some companies and some leaders as well, we want to be AI first. We want to lead with AI. We will do everything with AI. And if AI cannot do it, only then we hire people or we hire people back. And you already have people in your company and they're very knowledgeable. They know a lot about your business. They have a lot of tacit knowledge. So to your point, how can you augment them with the right tools and leverage their expertise? I think that's critically important. And I also feel a lot of times we talk so much about leadership, but sometimes it, on one hand loses the meaning. Or sometimes we also know that they're great leaders and they're leaders, they're not as good as they could be. So specifically looking for team members that might need a little more help or that are on the leading edge of things, how do you bring them in? I feel from a leadership point of view, that changes the game for you of how you need to assess and, decide again, who. Should I nurture a little more and give a little more guidance. How can team members collaborate with each other? Again, who's more leading, who can bring some information back to the team? So a lot of the soft skills and soft factors I feel, and interpersonal factors play a lot bigger role when you grow.

Alison McCauley: 20:23

And you know what? The sort of the pro move here that's so easy that anyone can do is and you mentioned it with the students, is. Learning how to use AI as a thought partner. So it's the use case that can help anybody with any challenges that they have. And so even the one that you outlined for leaders, where do I start? How do I understand how to activate different members of my team around it? So if you learn how to use AI as a thought partner, as and you're really interacting with AI as if it is a incredible. Peer or expert in different areas and you're using it to push your thinking and you're continuing to evolve that you can unlock all kinds of new levels of your own brain and expertise. You mentioned the studies that we're seeing where, AI in some studies has shown they can basically dumb you down. But there's a juncture here. AI can make you dumber or it can make you smarter. It's all about how you use it. I, yeah, I had an interesting example with a students. What I tell them to do when they're interviewing for jobs is go out and upload some information, the job description, your resume. Upload to AI, ask it to ask you those hard, develop a bunch of hard questions to ask you. Then record yourself using AI. Record yourself giving the answers, and then have AI evaluate that. Do that three times now, see what happens. So it's that thought partnership and anyone can apply that to anything and you build AI muscle in the process.

Andreas Welsch: 22:01

I see we're thinking a lot alike that there was one of the one of the exercises that I gave to my students as, as well use it as a sparing partner as, a coach, as an interview coach. So you develop confidence and, you see where are some areas that you can improve upon. And by the way what applies to, students. And early in, in career individuals also applies to professionals and leaders alike, looking to stand out in this crowded job market.

Alison McCauley: 22:24

Yeah. And frankly all the way up to the CEO Yeah.

Andreas Welsch: 22:27

To use this as a thought partner.

Alison McCauley: 22:29

So I have clients that use it to pregame their board presentations. Yeah. It's a fantastic use. Yeah. And this one anyone can do today.

Andreas Welsch: 22:38

I think that's one of the beautiful things about it, right? It's right at the editor or fingertips where you don't have to be a trained math mathematician, a statistician. You don't need to have a PhD to use these tools anymore. They're on your phone. Go ahead, use them, obviously, use'em safely, responsibly. Don't put confidential data in there. All the guardrails and boundaries that we need to set, but it's there. You can use it. You can use it at the dinner table if you want.

Alison McCauley: 22:59

Please do you know there's a flip side to this. Yeah. So when we are confronted with too many choices, we tend to freeze. Have you ever had that happen where

Andreas Welsch: 23:08

Oh yeah.

Alison McCauley: 23:09

Yeah. So this is called the paradox of choice. And what happens is we actually have this with AI because we are used to technology. What it does that's dictated by the technologist, right? It's dictated by the app. All of a sudden you sit in front of AI, what happens is people freeze. They have no, no idea what to, where to start. And that's part of the challenge is how do we how do we know what to engage? How do we know where to start? And so that's the one of the first things to do. It's really focus in on where it's gonna make a difference for You

Andreas Welsch: 23:45

I love how practical your suggestions have been so far throughout our conversation. I want to take us in into a negative rabbit hole, but I'm looking for, some additional practical thoughts from you as well, because I know a lot of leaders are, also concerned about. What AI or agent AI means for their jobs, right? Will I eventually have a smaller span of control? Are we not going to backfill roles with humans? Am I having, are going to have a, lower personnel budget, but a larger technology budget in OPEX budget to, to spend on a technology? And, again, what does it mean, right? When a lot of times I feel, especially in large organizations. Influence and status. So much depends on how many people do you manage and do you lead, do you have 5 50, 500, 5,000? How do you feel that the leaders can prepare themselves? Right now, you already gave some good examples, but what would you say to leaders who are concerned about what does all that AI change mean for me and for my role, whether I'm at first level, leadership, mid-level, or even senior leadership.

Alison McCauley: 24:51

I've heard that concern from several different areas about how do we measure leaders when it's no longer about the number of people they manage? That's what our structure Yes. Have long done. So that's, that is a fear that's out there. That is a concern. And so what I have observed is that there's, a, what I've noticed is that people often go into the conversation about AI. They're, like, okay, we know we need to learn about it, but they're coming in it, at, even at an executive level with a lot of fear about true what truly, what does it mean to me that the emphasis on expertise and the importance of expertise is a bit of an unlock because all of a sudden people understand that we can, w we, need our expertise. Yes, the expertise across my teams, we still need. The other piece is when you get hands-on and I have a workshop methodology that I've used that has worked really well, I. To help leaders go from skepticism to actually a path forward, to navigate the use case or a perspective on the use cases that are really gonna make a difference in their business and how to make those first steps in just a few hours when you get to the point where you're thinking about your business problems and how to solve them with AI, and you can collaborate as a thought partner with AI to do that. That's where you see the shift and all of a sudden it's wait a minute. I can solve these perennial problems because of it, and I can help with my team. I can reimagine what a role is about and how I can better serve my customers or. To build better products and services because of this. I'll give an example. I was working with a team where we were actually the, organization wasn't aware of really the kind of change that was happening in the middle level of their organization with AI. And so they decentralized innovation. I recommended a combination of decentralized and centralized innovation around AI. They'd done the decentralization work so people were equipped with tools. So one thing that we were doing is mapping out where are the people who are using it in ways that are effective, because a lot of organizations don't even know how it's being used. And I found a woman who had worked with it was it, they had a service that was a very costly custom quote process. It took weeks of back and forth. So she created a tool using Claude that enabled that work to be done in a matter of hours. So then I dug into her, with her about w. How'd the team feel? Because all of a sudden this this team that had been doing the custom quotes had been spending weeks of time, and now it's just hours. Yeah. Their job could disappear. But of course they were excited about it in this situation because now all of a sudden they could spend all their time on developing more strategic Yes. Relationships. Yeah. So that's where that's where we can start to see these kinds of differences.

Andreas Welsch: 28:12

I love it. I love the positive that is in these transformations as well. And thinking about the client that you mentioned, if you previously spent weeks creating these custom quotes. Now, it's a matter of hours. So how many more quotes can you create in that same amount of time? Meaning how many customers in addition can you serve or can you serve more quickly?

Alison McCauley: 28:34

How deeper can you serve those customers?

Andreas Welsch: 28:36

Yeah. Yes, that too, right? So it's not just about how can we now repurpose or reduce the number of people that we have, because we still plan for that same volume of custom quotes. But what else can we do for businesses and for leaders like to suss out what else can we do and, again, what can we deliver in terms of value in customer satisfaction in that sense. Now, Alison, we're getting close to the end of the show and I was wondering if you could summarize the key three takeaways for our audience today.

Alison McCauley: 29:04

Yeah, so I would say very clearly jump in if you haven't already. So that's that's number one. Get hands on. Really get hands on. The other thing is really lean into the expertise in your organization. Equip your experts with AI, enable them and help them chart a path to how they're going to amplify their value through AI. It's a huge opportunity. And the next thing is, leaders should really lean into imagining and dreaming what is now possible with these tools. It's not just about automating what we're already do doing, it's about rediscovering, reimagining what's possible because of these tools.

Andreas Welsch: 29:53

I love them, right? It's all about dreaming big, getting hands on, experiencing for yourself what it can do, and helping those around you have the same en enlightening experience as well.

Alison McCauley: 30:04

Yeah, there's a lot here. There's a huge opportunity here for those that are ready to jump in.

Andreas Welsch: 30:09

Perfect. Alison, thank you so much for joining us and for sharing your experience with us. I've really enjoyed our conversation.

Alison McCauley: 30:15

I love talking to you. It's so great.