Glenna Wiseman (00:00.246)

Not only are we in this incredibly volatile environment right now and we're racing to make sure that we can electrify our society fast enough. Now we have all of this going on and our jobs are under stress. And am I gonna, like you said, train something that's gonna take my job of the future? It's a lot.

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Nico Johnson (00:17.954)

What happens when you put some of the energy industry's most senior leaders in a room and you ask, what's actually working with AI? AI is rapidly changing how we all make decisions, manage risk, run operations, and even deploy capital. But are we actually creating enterprise value? And are our organizations prepared for the changes that AI is bringing along? A recent Chief and Harris poll study found that 84% of senior women leaders credited

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Peer community insights with smarter AI decisions. Well, 83% said they actually learn more from peer conversations than traditional AI training. That research inspired today's guests, Abigail Ross Hopper and Glenna Wiseman, to dig deeper into what it means for the rest of us. And they brought together senior leaders at the RISE Leadership Forum to uncover the challenges and practical solutions to implementing AI.

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Glenna Wiseman (01:15.534)

There's a huge disconnect between what companies are saying they're doing with AI and the value that they're deriving from AI. That disconnect is played out in the research that you see in all the business realm, but it's also really poignant in the clean energy space. And so we wanted to see if we could really prove that what you lit what you learn in live time, because AI is moving so quickly, what you learn in AI

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lifetime about what your peers are experiencing in terms of challenges and the solutions they're deploying right now. Could it help them? And that's what we did in Chicago.

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Nico Johnson (01:54.51)

For those are unfamiliar, RISE, which stands for the Women in Renewable Industries and Sustainable Energy, I think, is the by by many, I think would say it is the gold standard for as an association of nonprofit for supporting women in leadership across the sustainability industry. Many, many folks in the solar industry are members in RISE and

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The event that we're referring to is the annual Rise Forum or Rise Summit, where you all were able to gather nearly a hundred senior women leaders across two separate workshops. One was the C suite executives, another were senior strategic leaders. I'm curious what you set out to discover and and how did the structure of the conversations get beyond just surface level questions to get the deeper answers?

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Glenna Wiseman (02:49.814)

I want to acknowledge the RISE organization for allowing us to play in both rooms because this was a really important thing and something that they hadn't done before. And that was based on the consensus that we really needed to hear from all of these leaders related to something as consequential as AI. I'm so grateful for Abby's willingness to do this with me and because we both set out to do it with the intention that the wisdom was in the room.

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The wisdom is in the room. The challenges are in the room. The solutions are in the room. And we need them live. And so that is what we set out to do and surface surface the challenges that these leaders are experiencing right now. See if they if they mirror the what we're seeing in industry overall. And then what solutions can leaders walk away with and really move the needle on their capacity to address this fast moving change and

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the value that they're creating in their own organizations.

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Nico Johnson (03:51.63)

I was really impressed in the documentation that you shared of how you structured the workshop. Frankly, it comes across as no surprise, super professional, thought out. Even the the gauge, and I will talk about sort of how you did a litmus test of the sort of temperature in the room and and the level of learning engaged there. Could you help me understand how the two of you thought ahead of the workshop on specifically structuring the dialogue so that

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You were able to harvest meaningful results.

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Glenna Wiseman (04:25.238)

really important question, Nico, because companies have these kinds of workshops all the time. It's really important the container that you create. And this comes out of a lot of work that I've been doing in the industry over the last year, since I left my Marcom role and the training that I've gotten in systemic team coaching as well. So you've got to create a safe space.

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You've got to let leaders know that they are safe in that environment, that that their whatever they're speaking is anonymous. And also that they create those guidelines, right? And I also think it has to do with the intention of what you're trying to create. But I would love to hear Abby's point of view on this. So Abby.

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Abby Hopper (05:08.034)

Nico, again, thanks for having us. And it is such an honor to be here with you again. And I I want to add my appreciation to Rise for putting on this leadership forum and putting on the executive the executive summit as well. So I would say the thing that really set it apart is twofold. One is that, I mean, Glenna and I started both of the conversations with just a little bit of

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reveal about our own selves, right? Like I shared that I was a little bit nervous in this new role as a facilitator. and that it felt a little, I felt a little uncomfortable. You know, Glenna shared a little bit about her journey. And so sort of as leaders and facilitators sharing some of that vulnerability starts to set the frame, set the container, as Glenna said, we gave people data. You talked about the Chief Harris poll. There's other research around how our

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companies, how are leaders feeling and experiencing and understanding AI to really validate some of their experiences, like let them know right from the start they're not alone. Right. If they're they're feeling like this thing is going wildly out of control, they're not alone. And then broke them into small groups. And so we've all been in workshops where there's small groups. Like there's nothing groundbreaking about that. But I think because some of that work had happened in advance, those small groups, I mean, Glenn and I sat back and thought said, ooh, listen to the hum.

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Of all the people talking and sharing. It was pretty magical.

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Nico Johnson (06:37.39)

Abby, you all created an environment where folks are open and willing to start sharing deeper view inside of what's happening inside their organizations. Has that unfolded? I'm curious what surprised or maybe even concerned you most as you're listening to the hum of the room and starting to pull threads of what these executives are sharing with you.

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Abby Hopper (07:05.676)

I think one of the things that surprised me the most was the commonality of the responses. There were so many folks who I heard them say when someone was sharing, like, my gosh, that's happening in my company too. Or, wow, I had that same kind of experience. There was both in the small groups, and then we obviously did readouts. So every group sort of said, Here's the one big challenge that we've identified.

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And by the time we got to some of the the groups near the end, they were like, well, you know, ours has already been said. And so I think that for me was was both surprising, but also affirming, both affirming to us as facilitators and affirming to the people in the room that the this thing we were talking about was not some sort of one-off problem that that one company was having, but was sort of a universal challenge with how the rollout of AI is impacting teams and companies.

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Nico Johnson (08:05.868)

wonder if there's anything that either of you heard repeatedly you feel companies were willing to say in that container, but unwilling to really acknowledge publicly?

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Abby Hopper (08:14.4)

One of the things that we heard pretty, pretty consistently was, you know, we don't really have a strategy. I don't think anyone's gonna go out on their earnings call or on their, you know, investor call and be like, just kidding, we didn't actually have an AI strategy. but we heard that over and over and over again. and it wasn't it it was more kind of of a like, hey, there's this tool.

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It is a tool that both has sort of personal impact, right? How can I use this tool to help myself be more efficient? How can I use it to help my team, whatever its function, be more efficient? And how do I help the overall enterprise be more productive and and hopefully profitable, right? And there didn't seem to be, with very few exceptions, which we can talk about, much kind of overall strategy around how to use these different tools.

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To achieve those outcomes.

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Glenna Wiseman (09:15.456)

Want to jump in here too because consistently I have heard not only in Chicago where we were with with the RISE organization, but also through the year when I've been doing these kind of things, the term is patchwork. We got this patchwork thing happening. We've got individuals who are AI champions, we've got teams that are moving it, but it's patchwork, it's not strategized, it's not it's not deeply embedded in.

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in what the problems are that the company is having or the innovations they want to drive through all the teams.

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Nico Johnson (09:52.758)

Another word that I've heard is siloed, that there are team level quasi-strategic initiatives, even strategic projects. But it sounds like you know what I'm seeing anecdotally seems to resonate that everyone is so busy and we're all resource constrained. Everyone recognizes, it seems, that AI is a lever and and and the leverage.

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It's a force multiplier from an HR perspective. And yet nobody has the time to slow it's like cleaning up your inbox. Time to slow down and say, like, is there a strategy here that would work across the whole organization rather than the engineering team does it their way, the HR team does it their way? Is that what I'm hearing you say?

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Glenna Wiseman (10:40.974)

Yeah. And it's part of the problem is that it starts with the shiny thing. It starts with the tool instead of the problem or the or or the the result that we want to drive. Yeah. Right. And and we heard this through both the challenge section and the solution section. Right. If you start with the friction that you're trying to smooth out and how can AI serve that? Yeah. And you then you get a cross functional or de siloed sort of team embracing that.

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then your chances of testing and piloting and moving it forward are gonna be much more successful.

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Nico Johnson (11:14.094)

I wonder if there were any significant differences you noted between the C suite concerns and the experiences of the leaders who were actually on the front lines implementing?

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Abby Hopper (11:22.392)

Think that was one of the most interesting conversations that we had the ability to see, right? The folks in the room didn't, but it will certainly show up in our playbook. And that was that the the senior strategic leaders who are the ones kind of on the front lines, leading teams and and responsible for delivering specific functions, to my mind seemed way more stressed, way more stressed by this lack of.

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strategy because a couple things were happening, right? They were being tasked with use AI to be more efficient without really understanding how that how that mold like fit into the overall organizational strategy. Some of them were being told, okay, now we have AI, so it's time to start cutting headcount. And you know, they don't they don't have they

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processes in place to cut the head count. And so that created a lot of tension. And then there was also this really interesting dynamic where sometimes it was people on their own teams who were really, you know, AI native or or adventurous with AI. And there was like a disconnect between what they felt was their ability to supervise them because they didn't have the same kind of technical skills or understanding about what was happening.

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And you know, that created a lot of anxiety. So it that was, I think, one of the more surprising things to me was really seeing the difference. I would say on the strategic, on the enterprise level, the the C-suite folks, it was more kind of addressing the the silos, the patchwork, and and also thinking about how the outputs of AI were impacting their reputation.

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their customers, their products, their services, right? Like, really, you know, we we learned a lot about trust in this exercise, but that was a real focus of the Suisse the C suite was their external facing impact of AI adoption.

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Nico Johnson (13:35.596)

want to pull on a thread here because the premise, the promise is operationalizing AI to increase enterprise value, something that at the C suite level is the one of the core drivers of the economic pursuit of building a company. The definition of enterprise value is a measure of a company's total economic value represents the theoretical price that someone would buy that entire business for. So

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question in the in my mind as an entrepreneur as we implement AI and and most of the founders that I interact with is how does this tool give us the ability to build repeatable processes that can increase or create enterprise value in the term in the form of economic value that we deliver to customers or to the marketplace. One of the things that surprised me is

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is when we were discussing privately sort of getting ready for this call, Abby, you disclosed that you very few participants could give a concrete example of actually delivering enterprise value using AI. What do you think that reveals about how companies are measuring success? And in particular, are companies creating value that are isn't able to be measured yet, or maybe confusing activity with results?

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I'd like to I'd like to have a general discussion around that, because that's something that I think is at the core of what your report purports to address. I think it does a great job of of giving good outline and boundaries there, but I'm curious your thoughts on what it reveals about how we measure success of AI at the moment and this not this notion of confusing activity and results.

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Abby Hopper (15:18.862)

I'm happy to answer and then I'd love to hear what Glenna has to say. I think you nailed it with this sort of confusion between activity and results. And I don't think most companies have a clear metric of how do we measure the impact of the utilization of AI on our productivity, on our profitability, and on this more amorphous piece, which is the trust our customers have in us. And so we heard a couple of examples, both of

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sort of AI gone wrong, right? Where where there was someone in a silo creating a product that shipped to a customer that was not good. That kind of problem we've heard from some law firm kind of people who, you know, their their clients are now saying, do not use AI in any of my legal work, which is the whole different kind of challenge. so I think that conflation of activity and progress is a really important one.

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Glenna Wiseman (16:14.702)

I think one of the disconnects here is it's that AI in most scenarios is one to screen. And that equates to me as an individual is are measured my by what OKRs or what goals I reach as an individual. Team structures and team measurements are where a lot of the work gets done that adds to overall profitability, right? And so traditionally companies and ooh, I could be way out of my limb here.

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don't necessarily measure team effectiveness. And this is a place where there's a lot of friction around how AI is being deployed in companies. And I've been hearing this a lot. It's like, how does it affect teams? As a matter of fact, Harvard Business Review Harvard Business Review was just out this recently with a a f one of the first reviews of how team is out of Stanford, how to how teams are being affected.

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Yeah. By AI. Okay. So now we're into the crux of the the core nucleus of a company, the core working structure of the company, a team, and how is AI being used within the team dynamic in a trustworthy fashion so that we don't have to let somebody go, like A Abby was just talking about. And we can really move the needle on, you know, what is really

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going to drive value here. And value is also about re reducing friction. So in the C-suite, we heard a very senior executive talk about removing contract friction and doing this in a way that broke down the silos and continued and served customers better by surfacing s surfacing issues within a contract structure and then and then harvesting the input from all of the team leaders.

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in order to understand how to drive how to create better contract structures. I mean, that was oof in live time. That was so exciting that one. Because it was in live time. It was helping a manufacturer in our beloved clean energy transition industry. Yeah. And she was willing to share it, which was awesome.

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Nico Johnson (18:23.352)

I want to pull on the the two threads because one of the things that is coming up is how is AI being used to effectively catch what may have been either slowed down or missed in cross-functional teams. I think folks are trying to figure out where is AI giving us leverage and where can we trust that an AI agent or process is doing the work in a way that

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n doesn't require human observation. In our business, you know, ten years ago and I started the podcast, transcripts done by machine learning were not trustworthy. You had to go through them with a human. This company, Rev.com, actually had two different service levels. One was like, if you're okay with like what comes out of the AI machine as like maybe 70% good transcript, here's that service. And this is the service where

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It's done and then a hundred percent corrected by humans. I feel like we're at that place right now with AI implementation at a corporate level. And as you described, Glenna, the HBR review, I started kind of poking around and it is pulling this thread on AI enhancing teamwork. And there's an article I'll link to some of these that I've found, that there are conditions within which it does enhance, but

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They had a general term that I'd never heard before called relations slipping that showed up in this HBR report that suggests that what's happening to the contrary of team dynamics strengthening is that employees are turning to AI instead of colleagues when they have issues, when they need help, when they can't find something. Whereas, you know, 10, 15, 20 years ago, you relied on your team. You relied on the institutional knowledge, and we're

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Outsourcing that institutional knowledge to AI at this point. It's one of the things that we talked about, Abby, you'll recall at Power Circle, that AI, and I'm curious if this came up in the leadership discussions because it was so close after Power Circle for you, Abby, that AI is usurping the, the, the journey that we all took in our 20s of finding things and figuring out the apprenticeship process for someone who doesn't turn wrenches.

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Nico Johnson (20:50.136)

For someone who turns reports internally or or turns data into something useful is all but gone because we're trying to automate the easiest, earliest stages of work. Even in the report, the Millikan report, like something like forty-three percent, if I remember Sissy correctly, of employees are actually actively concerned that they're they're creating their own job replacement using AI. So I think w one of the things that I learned reading the

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the studies that you sent over ahead of time and and the report that you delivered is that there is this overarching sort of trust layer that is getting in the way of AI implementation. I think that your playbook identifies trust as a central issue connecting these challenges. How did you arrive at that conclusion based on what was shared from the leaders in the room? And what does it say about where we want to go from here?

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Abby Hopper (21:48.856)

You know, it's funny c we we did not start this this inquiry with the presumption that trust was really the challenge. and we did not actually use that word specifically in the conversations we had with with these executives. But as Glenna and I reflected at all of the data, all the conversations and sort of the thematically what was happening.

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We both had this aha moment that was like, you know what? What we are talking about is trust, right? We are talking about sort of an erosion of trust among teams, an erosion of trust among belief in the work product, right? An erosion of trust that customers may be having. and so once we kind of had that aha moment, it it framed everything, right? It was the thematically, that's what we're really talking about, is

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How are some of the ways in which we used to create trust and build trust have been undermined by this? And to your specific question around sort of younger folks earlier in their careers, that was definitely a thing we heard throughout the conversation was that people younger in their careers have gotten many of them, some of them have gotten into the habit of looking to AI without a lot of critical thinking.

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about the responses they're getting and not a lot of experience sort of sifting through what actually makes sense and what doesn't. And that that as a sort of a a challenge that both managers are having, like how do we teach people how to have critical thinking or how to question the results was a important part of the conversation. Glenna, what do you think?

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Glenna Wiseman (23:35.96)

I think all that and I think that the the Stanford a Harvard Business Review really hot recent study around teams and the relation slipping points to teams are built on trust. Teams are built on trust. Who do I need to go to for this? Who can I depend on for that? Is the output that we're that we're putting out to the broader company trustworthy?

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You know, so this is that showed up in all of the in in these conversations. And the good news is people are working on this. I mean, we did not go into this conversation with, this is the shiniest, best tool that you need to be using now. This was not a tool discussion. This was a discussion about how to re-reinforce what I like to call the human infrastructure of the company in order to take on this quantum change that we're going through. Not just a change in the

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grid optimization and the products and the battery analytics and everything that we can deliver to the market. This is about how our companies are shaped and how we solve problems and create innovation. And I I I really remember as Abby and I were getting ready for this, she had just been at a chief conversation around or CEO conversation around AI. And

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And all the so a lot of these themes had come up and and Abby, I remember you saying that but we didn't talk about teamwork, how it affects teamwork.

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Abby Hopper (25:00.994)

Right. Right. It's wild. Right. One of the pieces of data that we framed the conversation with, I'm looking at it now because I think it's so important, is that we, you know, we really we're all, you know, ideally using AI to drive enterprise value, to make our companies more profitable and more more successful. And forty-four percent of CEOs who capture significant value from AI invest in people and change management.

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And sort of there's this idea, another study that was from BCG, this one's from Deloitte. 65% of organizations say their culture must change significantly because of AI. You know, that kind of research sort of reinforces this finding that people are at the center of this transformation. And, you know, people are gonna people. People are gonna people all over the place. And so you gotta like center people in this transition.

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And make sure that they, you know, not only have the tools they need, but have the like human infrastructure and the relationships and the learnings so that they can really flourish and bloom.

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Nico Johnson (26:10.102)

One of the things that caught my attention in the the data and the statistics that were shared, there's the research from the Milliken Institute and Harris Polls report 81% of leaders believe peers could get caught awa AI washing. I'll put it in air quotes for those that are watching if they were in if their work was investigated. And I'm curious how how do you define AI washing? I think a lot of folks are familiar with greenwashing. what does it look like inside of an organization?

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And perhaps more importantly, what should an organization measure to know whether AI is actually improving work products?

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Glenna Wiseman (26:46.636)

Well, I'll start off and then popcorn over to Abby. one of the examples that people shared from the room in Chicago was that their teams had made a decision not to use any AI generating brand related images. Okay. So that is a a line in the sand saying, you know, no, we're not going to do AI imaging, right? We're not gonna do we're not gonna generate what associates with our brand using AI.

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Nico Johnson (27:00.406)

Mm.

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Glenna Wiseman (27:15.724)

Which as a brand person for many years made my heart sing, of course. Sure. But you know, there's a place for all of this. And that's one of the key things here is to understand the place for all this. I think there's also the layer that we heard that executives need to demonstrate their own use of AI, how they're using it, and not just mandate.

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Abby Hopper (27:35.862)

Yeah, the other place where we heard a lot about AI watching was in writing, right? Was in everything from, you know, writing posts on LinkedIn where there was wild consensus that we can all tell when something's been written with AI. As someone who writes my own posts, I would would agree. but a lot of a lot around the writing process, a lot around the synthesis process, right? That you know, taking a lot of data and putting it together.

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I think there was in also in terms of AI washing, kind of this. So if you think about sort of writing, synthesizing, and then analyzing, real distrust that AI can do like the the insightful analysis. It can sort of do some of the here's some of the themes, here's what the numbers say. But that next step of what does it all mean and how does it relate to our company, folks in the room were not persuaded that it could do that. But you know, sometimes you get a product where

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It it appears to have done that.

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Nico Johnson (28:35.896)

feel like it's maybe this concept of like purporting to be more AI savvy and AI forward than you really are. if I if I think about the corollary of greenwashing, it is companies like Exxon touting their climate initiatives when 85 it's like you see the tip of the iceberg that's climate initiatives and not the bottom of the iceberg that's like all the ways they're eroding trust in society. It it seems like perhaps it is companies

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touting the AI benefits and the marketing and like being AI forward when I think the statistic that if I think maybe it was Harvard I read a study that said something like almost 70% of workers feel like they're navigating the transition in the AI era entirely alone on their own. And almost half of employees feel like they are receiving no meaningful AI support or training from their employer in the last year.

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That feels like AI washing too. I'm trying to think of a good analogy. It's like saying we're the most advanced and lean operating machine and and internally it's like mice or hamsters on a wheel. Right. Like actually moving the thing instead of some like fancy new electric engine. Yeah. Right. Yeah. that that cat I feel like that also maybe is a version of AI washing where the the exterior view of this like

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a s sort of forward leaning company doesn't match the employee experience internally.

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Abby Hopper (30:09.506)

I think that's a really interesting way, Nico, to think about it because I would agree with you. That's a that's a good frame. And it speaks to the experience that individuals are having. And back to that trust question, right? If you if you can't trust your employer to train you and sort of help you understand how this disruptive tool, which may be taking your job, is is part of your workflow, that can be incredibly unsettling, right?

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I was joking with someone yesterday, right? I assume most of us are gonna be at RE Plus in Las Vegas soon. I was saying, you know, I bet you if you had to take a shot, like you walking around the show floor and you played AI bingo and you were gonna take a shot for every time you saw a company with like we are an AI enhanced and AI led and AI whatever. First of all, you'd be drunk before you got like halfway down the lane. I imagine, yeah, you won't get out of North Hall. But

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I would imagine that most companies are going to be touting their AI prowess in their booths at RE Plus. And I also would speculate that most of the people who work with those companies would be having some of the similar experiences that we're talking about, right? Where they're not quite sure what the plan is, how it how it impacts them. The other piece we talked about a lot was how much more work is creating.

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Right. Like it's not most a lot of people felt like it wasn't actually making things more efficient. It was creating more work. More work to b either check what's happening, more work because they don't know who's doing what. More work because like now, you know, they've it's done all this and now they have to do this other thing they didn't have to do before.

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Nico Johnson (31:56.63)

Yeah, and it's also encouraging companies to slow headcount, additional headcount, until they can figure out what can AI do that we that we could avoid adding humans on. Yeah. So it's just piling up more work on every team, mine included, right? Like everyone is in this hire versus build AI for conundrum.

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Glenna Wiseman (32:20.684)

There is a validation phase here. One of the ideas came forward in the solution to have a sort of a the equivalent of a PE stamp where you know, that there was a human that was responsible for validating that this information was what it needed to be and that that was a trained person instead of AI, you know, human in the loop. It was AI in the loop and was the human validating.

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Nico Johnson (32:41.762)

Right. Yeah. This issue of governance, yeah.

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Glenna Wiseman (32:43.924)

Right. So governance here is a really critical part of the of the equation and very transparent. And there are some companies, I you know, shout out to Pattern Energy. They've done a great job in terms of communicating their governance structures, omnidian the same. So there's some companies that are doing a really good job with doing this and keeping them up to date so that everybody understands what tools they can use, how they can use them, what are the guardrails. I think, Miko, you use that. but I think we

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We could also spend a minute on data because one of the things that came up as a challenge was data hoarding. I love that term. Data hoarding. Because people are in their silos. You also brought that up earlier. People are in their silos and they own their little their silos and that's their data. Well, in order for enterprise wide, and I am not a technologist, so no throwing of arrows, you've you've got to have d clean data. That's a a huge lift right now. Yeah.

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Right. That's a huge lift right there. And how do you connect all of that data? I mean, even, you know, on a a large utility scale project, think about the amount of data that is involved in that build and the financial reporting that needs to be there to fund those projects. I mean, it's it's a huge lift. Right. And that's an additional stress on the people who are trying to learn all these tools, implement these tools, check the tools and make sure that they're

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that they're valid and then check the results. That's a lot.

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Nico Johnson (34:16.514)

You know, you bring up this issue of governance and this and the notion that Abby pointed out that it creates sometimes more work. One of the things that I wonder is who's ultimately accountable when AI, not if, when it produces something that's wrong, misleading, potentially harmful to the company image, to the marketplace, as pedestrian as someone on the team.

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creates an agent that reads their emails, reads the news on a daily basis, and says, I'm gonna think like this person and I'm gonna post on their behalf on LinkedIn. And they let it go. And we see people I see people posting on LinkedIn using agents where it seems to me they didn't even review it. They just let it roll. If you multiply that at scale on a company of 10,000, 20,000 people, governance, it now becomes as sort of s serious and hard to manage as cybersecurity.

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Glenna Wiseman (35:16.236)

Well, and I think it invites just like we invited live real time because this is moving so quickly and and boards are putting pressure on C suite, which then puts pressure on functional leads to make to to roll these things out, these programs out. I think we should invite, you know, comment and c you know, what's happening, you know, in your organization and in a way that you can share, that the AI agent isn't doing it for you. that

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helps everyone understand because one of the things here that I was that I am so proud of this work and the continuing alliance of doing more of this work with Abby and I is to surface what is working, surface what the challenges are, surface what is working, make sure that the entry level person who may be more savvy than the CEO, really, when it comes to AI implementation and what AI can really do.

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Make sure that everybody is at the table.

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Nico Johnson (36:15.854)

Well, I know par one of the things that participants raised as concern was this idea of losing their professional voice or feeling isolated, even losing the joy that they get from their work because it feels like they're now an automaton in this machine that feels less human. What were you hearing underneath those concerns?

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Glenna Wiseman (36:34.044)

there was the joy job robbing. Wasn't it? Wasn't that the way they said it, Abby? Joy job robbing.

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Nico Johnson (36:40.632)

Wow.

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Glenna Wiseman (36:42.456)

I mean, that really taps into the sentiment that not only are we in this incredibly volatile environment right now, politically, in policy, and we're racing to make sure that we can electrify our our society fast enough. now we have all of this going on and our jobs are under stress. And am I gonna, like you said, train something that's gonna take my job in the future? It's a lot.

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Nico Johnson (37:08.632)

Abby, you ran for a decade a large organization that grew a lot under your leadership with high expectations for results. And yet, as you now said a year outside of having that role and thinking about how to help other leaders, in very material ways, the game has changed for the leaders that you're helping sort of wrap their hands around though the the new rules of engagement. How do executives then balance legitimate

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Expectations for productivity gains with their responsibility to develop the people and protect the trust inside the organization.

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Abby Hopper (37:46.582)

I think Glenna really identified it earlier. It is, you know, back to the basics. What are we what are we trying to solve? Right. Like not what is the coolest new tool, but what what is trying to solve? Right. Where are we starting? What is the unique contribution our company is making and where are we having friction? And then bringing in the tools to help manage that, right? The tools to anticipate.

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volatility in the marketplace and then with a focus on the people. Right. And so I think think there's definitely a path forward. I'm a huge believer that in in disruption is amazing opportunity. And that's partly why I'm excited about where I sit right now because it feels like everything's getting disrupted and like that's the time to move fast and seize some opportunity. But doing it with some of the basics like what

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What is the problem? How can we fix it? What are the best tools? And who are the best people? and that's what we heard from the group, right? When the group really sat down and focused on solutions, it was we need to have a conversation amongst ourselves, right? We need to be talking across silos. We need to stop this patchwork approach and really maybe slow like that old phrase, slow down to hurry up. Yeah. And you, you know, you identified it early on, like what are we measuring?

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Right. How do we know when we've succeeded? Sometimes it's more money, sometimes it's more employee retention, sometimes it's better customer satisfaction. Right. But like we need to be really clear about what the goal is here.

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Nico Johnson (39:25.112)

think that there are meaningful strategies that are emerging. and it's like there's technology adoption concerns through the arc of history and time. you know, some someone recently was making it analogous to helping folks transition from typewriters to computers, which was in many ways the last major organizational

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shift of technology where it made a meaningful change in people's jobs. You know, like typists whose job was making sure memos got captured from meetings converted that skill set into the role of executive assistant and and other sort of organizations serving service roles rather than just manual, manual entry, manual operation. I've heard companies talk about how they're sort of gamifying the process of improvement around like

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what actually works with AI and sort of having having d contrary to some of the consternation that came from the workshop, there there does seem to be some like microcosm of companies that are encouraging the teams to share internally and making sort of leaderboards of like who's implementing AI in what specific ways and how's it adding value to companies. Back to the workshop

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The operational playbook that you've developed identifies five readiness lenses. So I want to give listeners an opportunity to now put application and framework around the lessons learned and the takeaways that you have. And those five lenses are culture, process, technology, governance, and learning and story capture. Those are in the same bucket. I'd love it if you could talk a bit about that, Glenna, like how you came to those five lenses and how leadership teams can

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Can you use these to identify what's holding AI back in their organization or holding them back from deploying it well?

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Glenna Wiseman (41:18.506)

It's really a centerpiece for my work right now because it's based on how do we uplift the human infrastructure that's dealing with this technology from a number of different lenses. And so that was just as Abby used a lot of really great content in terms of what are the challenges, the stats that uphold the challenges in business that were t that could are the context for the challenge sourcing. Then we use these lenses around AI readiness.

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and the humans in the in the in the company for framing but not checklisting the solution gathering. So it was an opportunity for leaders in the two rooms to look at, well, how do people relate to AI through culture? How what are the processes that we're using through process? What are the tools that we're using without getting too nitty-gritty in terms of technology? How are the decisions made? What are the risks involved in terms of governance?

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And how is useful experience spread through learning and story capture? Learning and story capture is really one of the, you know, things that companies leave behind a lot. And it's really, you know, if you institutionalize or s systematize learning, we one of the ideas that came forward were centers of excellence, right? Uh-huh. Or cash prizes for really great innovation, right? I mean, I agree with Abby. There is, there's a

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There's so much innovation opportunity here. It's kind it's pretty exciting.

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Nico Johnson (42:50.58)

I am wondering for the CEOs and C suite listening, does your playbook allow for and give sort of a framework for evaluating my own company's readiness across these five areas? You know, are there prompts or questions that it asks or invites that allow me to use these five lenses to see into my company beyond beyond highlighting them for me?

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Glenna Wiseman (43:14.024)

I created a digital tool for AI assessment using these five lenses that a a leader can take. And I just finished my first AI hackathon. Yeah. at my she as she builds, where it's multi-leader. So yes, there we are developing tools. We are developing tools that can help leaders look at this and look at it from different points of view.

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so that they can identify where the friction is because we can't all tackle everything all at one time. You just said that, Nico. You can't just tackle everything all at one time. So you've got to choose what matters most. And so so these are, you know, our industry is creating these tools that we can help leaders understand where the friction is within the team and how to and how to address it.

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Nico Johnson (44:00.302)

I loved several of the ideas that were presented from the findings in the workshop. I think I'm going to implement the AI office hours. As a as a completely remote team, and we were we used to be very good at this, but we occasionally will host office hours, which is simply like we co-work together as though we are all in one office. I like the idea of there being a dedicated time for a team to focus on how is AI being implemented and what are we learning from it.

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across the org. When an org is moving so fast on a single topic like this, it's important to be able to rally the team and sort of sort of circle the campfire as it were and be able to have like even a a show and tell, like your own internal hackathon would incorporate something like a show and tell because people would talk about what it was, what it was that they developed. And I feel that we lack this in organizations right now because people are moving so fast and there is not a regular cadence to say, hey, here's

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how it's worked for me, here's how it failed for me, here's how I've noticed that it seems like we're doing things differently across the organization. I wonder if there are other practical examples that came up that you want to highlight that you'd encourage leaders to try in their organization moving you know, this week that can implement?

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Abby Hopper (45:15.372)

Yeah, one of the ones that we heard from a number of different companies was like a riff off of the off of the office hours. And that was the leadership team talking about specifically how they were using AI, mostly in terms of like their own effectiveness and their own efficiency, but just sort of normalizing the idea, A, that we're using it and B, we're learning, right? Like we have not captured.

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The flag on how to utilize these tools. That was one that was happening across organizations. and is pretty easy to implement. It also shows vulnerability, right, from your leaders. It builds trust in sort of this learning process together. The thing I like about the open office hours too is it does the same thing around trust. Like it it's like, okay, Nico, Nico is also having these questions, right? Like okay, I I I can trust him because he's

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Like just showing me sort of the good and the bad of how he's learning. Those are the ones that come to mind for me, Glenna. How about you?

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Glenna Wiseman (46:17.358)

Where people sit is really important. Organizations understanding where people sit and we did it so that we can so they can plot where you know where progression can happen. And so

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Nico Johnson (46:29.43)

when you say where they sit, you mean like where they are along a learning curve? Not like in Durham or in Washington. Yeah. Well, because also like where they're living like anyway, keep going.

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Glenna Wiseman (46:33.1)

Right. Where their capacity is.

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No yeah.

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Glenna Wiseman (46:43.95)

Yeah. Yeah. So so Abby had this great idea. You know, we should see where people are, you know, in the beginning of the session and where they are at at the end of the sess.

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Nico Johnson (46:53.12)

I swear to God it's like you're reading my mind, Glenna. Like you anticipate my next question before I even get to ask it.

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Glenna Wiseman (46:58.158)

And and and what we wanted to do was make sure that that was analog, which is really kind of humorous because we were having an AI conversation, but we were using an analog tool in the early stages of working with teams. I b and because we're the energy industry, I wanted to develop a tool that would give teams the ability to say, here's where we're at right now. Not related necessarily related to AI, but just in general. Here's the capacity to do the job. I'm completely depleted.

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Or the b energy barometer moves up to completely energized and rocking and rolling, ready to go. This was a really great way to not have group therapy when the team gets together, but to register where you're at. So we use this simple way to register where these leaders at. And think again, these are a hundred of the most senior leaders in the industry.

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Nico Johnson (47:50.638)

Yeah.

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Glenna Wiseman (47:51.65)

You know, where do they sit in their own personal capacity to move the needle literally on value, right? And I I this is in just 80 minutes, because that's about how long we had for each of these sessions. They moved from, first of all, we had 86%. Think about that. 86% of them filled out this cube form. I mean, come on. That's an amazing stat. Right? So they did it.

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Nico Johnson (48:13.377)

Yeah.

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Nico Johnson (48:18.038)

It actually is.

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Glenna Wiseman (48:21.698)

They put the sheet down, they picked it back up again, and they moved the needle from average guarded to steady. They moved the needle up from steady to resourced. Yeah. In eighty minutes.

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Nico Johnson (48:35.362)

Yeah. And if you're not watching, by the way, on YouTube, then there's this barometer that Glenna and Abby introduced called the Team Energy Barometer that I'm gonna steal. I'm gonna use it. It is fantastic. and it's literally just tick a box, whether you're depleted, strained, guarded, steady, resourced, or energized. What an absolutely fantastic I mean, I've been in marketing my whole career. It's so hard to

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Create a container, Glenn, and I think you'd perfectly captured this. I give you kudos as someone who for 20 years has been not only like watching people do marketing badly, especially around surveys, but have seen you sort of in your element and providing value as a marketing consultant. Like this is the this is the result of years of like human human psychology study.

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Like I think that you should make this a download that just the barometer. I think people should steal it and use it in their meetings. I'm fascinated. What you d what do you believe happened in those eighty minutes that helped those leaders feel better equipped to act? Like you can literally measure that they went from guarded to more steady and resourced in in a in a span of eighty minutes.

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Glenna Wiseman (49:54.528)

Okay. First of all, I'm going to do a shameless plug for you. Can find this on my website, Permission to Bloom. And second of all, it's my next digital because I used AI to develop this. It's very backed up in terms of the formulas to to make this happen. Yeah. So that's an example of a problem that I was trying to solve and that I used AI to solve it. And then I'm going to digitize it as the next thing. Fantastic. So thank you for all of that because very proud of that work. And that it worked in this environment. They got it and they used it. But I'm going to move over to Abby.

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To see why does she think we got movement on capacity?

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Abby Hopper (50:29.592)

is pretty amazing and I'm so glad that we measured it. And I'm so glad we did it in an analog way. I was trying to I was arguing for like, let's let's have it. You know, we can get on this QR. That was what I wanted to use. I got

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Nico Johnson (50:42.872)

No.

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Glenna Wiseman (50:43.244)

Because you and I think alive

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Abby Hopper (50:45.23)

Yes. No, it was the perfect way to do it. And I I like, I just I love the irony of talking about you know, AI and measuring it with a pencil and a piece of paper and talking about this tool and doing it with other humans, right? This machine learning and doing it with other humans. And I think that's why there was movement, is because we were doing it with other humans. There was this trust created because we normalized the challenge, right? We gave data at the beginning that said.

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Sort of quickly took off the table that you were sort of some unique person if you didn't understand or weren't getting the full value out of this thing. Like what was going on? And then, you know, we're like, all right, let's figure it out, right? Like Gunnet said at the very beginning, the solutions are in the room. And, you know, we had incredibly smart people who have built wildly successful businesses. Like, we can figure this out. We can figure this out together. And I think that there was just the reason it shifted is because

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We normalized the challenge and we provided people an opportunity to come up with solutions together. and then to have something tangible. They'd be like, I can, I could do this. I could have office hours, I can have a contest to see what's working, right? There's some real practical application. that's my take on on why the movement happened. And I will say the other reason is we didn't talk in big weird, like complicated technical language, right?

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We talked in we use the like the language of the people. We use the language of sort of how are you feeling? How is this working? What are the challenges? Yeah. What are the solutions?

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Nico Johnson (52:25.218)

Yeah, and I think that if you're a leader, you're listening to this and you're nodding your head and at the same time saying, Well, a lot of this is is so obvious. Okay, then why aren't you doing it? Right? Right. 'cause I guarantee you're not. you're cause 'cause we're not so dissimilar. And what it's what it's highlighting is that companies really are in this like AI era fractured in the way that

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what I think this exposes is just a communication gap in most companies. It's not that people don't have intellectual assent to like the way we've used these tools that you've just explained of like how we can actually create organizational learning. It's it's not that folks are ill-intentioned or lazy. It's that we are so frac we are so fractured in the need to produce more, show productivity, reduce headcount, increase asset value, enterprise value.

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It's hard to hire. And so there is now a default that we didn't have before. Let's it's hard to hire, folks. It's hard to find a new person to take a role that you need a human on. And and so, you know, if you're listening to this and you're feeling like me as I read this report that these ladies put together, like beating yourself up a little bit on how you could be doing this better, take heart. You should read the report. It's got great practical guidance. I want to get into the final stage here of the practical guidance, Abby.

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so let's bring this action into executive meeting. The playbook gives leaders five questions to consider. How would you use them to move from AI experimentation towards a focused strategy?

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Abby Hopper (54:03.224)

So first of all, make time and space for the conversation. Right. Like, I mean, it's just as basic as that is like create the containers so you can have the discussion with your team. Acknowledge that perhaps it's, you know, that we're all at different points in our learning. And let's just set that baseline up front. And then figure out like where are we having friction and what are we trying to achieve?

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I think some like as I I as I think about bringing it into the boardroom, I think about kind of that question that is so critical. What are we trying to measure? Right. Like what are we trying to measure? What are we trying to accomplish? What are we trying to measure? And having a real conversation around that. The other and I actually can't remember if it's in our list, but the other practical suggestion that came out of the conversations was, you know, oftentimes when we have sort of these leadership initiatives, we say like,

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The CEO has to drive it, right? It has to be the CEO's responsibility. And there was a pretty strong sentiment in the room that while the CEO certainly had to be brought in, CEO has neither the capacity nor the experience to drive it, unless it's a particular kind of company. And so like acknowledging that and creating a role for someone to be the holder.

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of this process and these learnings is a really important addition. And that was that's not something we normally hear about kind of initiatives that transform and and create great change.

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Nico Johnson (55:39.264)

Yeah, yeah. I have had two conversations in the last week that blew my mind. One is our friend Daniel, at C at CIR, Ink Tech Industry Resources, create an entire division. Like their business is built on like leveraging AI, but also leveraging human ingenuity and the ability to create processes that people can repeat. Create an entire team and is hiring like five new AI engineers, but like an entire team who their job is to

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a answer this question at the organizational level of how AI helps everyone and like and how and then the other one was I had a conversation with I won't mention his name, but a an IPP CEO who owns I think owns a gigawatt, operates another three, four gigawatts of solar capacity, like massive organization, almost almost seven hundred people. Wow. And hired a new CTO who is

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But came from AI to cr basically create an an AI sort of governance process in the business, recognizing that like everything from like today forward is going to be AI friendly or AI forward without AI washing kind of blew my mind. I was like folks that are actively building, you know, multi-million dollar, multi-billion dollar organizations have

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Started to take a step back and say, what is it for? Yeah. What is it for? Like all my team, everybody's talking about AI. I listen to, I listen around the water cooler speaking to the CEO. Like I listen around the water cooler. I listen in the boardroom. I listen in all these meetings. I think that it's wonderful to see that people are taking these practical steps. Would you be okay if I read out the five questions from your playbook for those of us that are lazy? Like,

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Glenna Wiseman (57:29.528)

F but first I want to say first I want to share one of those questions. One of those questions has to do with not only what is it for, but who is it for? Who is it for? Who are the stakeholders that we that whose trust is really important here? Yeah. You know, and that it that expands the lens out from just the CTO. And, you know, that's a really, really important role. however, all the stakeholders are important.

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Nico Johnson (57:38.221)

Yeah.

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Glenna Wiseman (57:59.308)

Right. And what and h and what d how do we create trust with them or not hurt the trust that we already have with them? But yes, go ahead and read the five questions, Nika.

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Nico Johnson (58:08.492)

Well, I Glenn, I would love if you would read them. You already have a command of the topic since you created it. I was gonna just read it because I know there are folks that are lazy like me listening who maybe won't download the playbook and I wanna at least give them something to chew on. Would you be willing to read it?

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Glenna Wiseman (58:22.446)

Sure. Questions leadership teams can put to work. What important outcomes should AI help us achieve? And how would we recognize measurable value? Two, whose trust matters for this work? Board, workforce colleagues, partners, customers, or regulators? Three, what evidence of quality, fairness, transparency, and human accountability is currently missing? Four, what one or two changes across the five readiness lenses are

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would make progress more dependable? And five, how will we share results and lessons, including what did not work? There you go.

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Nico Johnson (59:01.41)

Abby, you spend a lot of time advising executive leaders. If you're advising a CEO that wants to make tangible progress over the next 30 days, what decisions are you asking them to make first? Who should own these decisions and how to how do they review those results and start to integrate it?

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Abby Hopper (59:21.038)

If I'm working with a executive and and we have a 30 day clock, right, for the for the first deliverable, my first question would be literally just like, what are you trying to accomplish? Right. What are you trying to accomplish and for whom? And I think getting clear on that answer is the first question the CEO needs to needs to be able to discuss. They're doing it for their board. It's very different than if they're doing it for their staff.

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Right. And in a perfect world, it's not an either or conversation. It is, you know, very few of us have one stakeholder. Most of us have many. And sort of figuring that out. And then sort of figure like does one or two things you can do quickly. Right. Like, okay, here's the challenge. Let's find one or two things you can do really quickly to demonstrate to your team, demonstrate to your board, demonstrate you to your investors that you are thinking about this.

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critically that you are putting some metrics in place to measure progress rather than just activity that you can articulate to your customers why the why the sort of inclusion of AI tools into your product is a competitive differentiator and is something that they can trust, right? those would be the questions and the conversations I'd want to have right away.

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Nico Johnson (01:00:42.37)

And Glenna, you mentioned earlier your AI uplift assessment that leaders can complete takes about I think eight minutes or so. What will they learn about the organization and and how would they use those results within their teams?

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Glenna Wiseman (01:00:56.334)

So it it moves five questions f for each of the lenses, the readiness lenses, and it enables them to first of all really think. It it it it it it just asking questions are really is really good because you're just actually opening up the aperture of what your thought is around this, you know, and it helps you to understand, well, wait a minute, maybe I'm not

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I'm not doing enough over here about capturing what is really working and and propagating and communicating that through the whole organization, right? And putting a showcase on the success stories. That's one of the things I would add to Abby's list there. What's working in the organization right now and how do we how do we communicate that? Right. So you're gonna learn where there is opportunity. Where is there opportunity to to build up your teams?

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So that they can really embrace AI and not just as tools, but as innovation. Really innovation, right?

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Nico Johnson (01:01:53.228)

Okay, ladies, I want to hit quickly our quick charge segment. These are quick answers to potentially consequential questions. And if anything resonates, maybe we'll circle back around and dig a little deeper. Abby, what's one AI use case executives are overrating or that you see as overrated?

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Abby Hopper (01:02:12.724)

One use case that I don't think is valuable at all is using AI to predict the future. We are in a time of rapid innovation, crazy politics, like the government is doing all kinds of wild things. And so, you know, trying to put in all this data and be like, this is what's gonna happen in the future, you gotta have some human intel and insight and differentiation there to make those kind of predictions.

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Nico Johnson (01:02:38.114)

Lena, what's a leadership practice that you feel is underrated for building AI trust?

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Glenna Wiseman (01:02:44.64)

Learning from the people in on your teams and creating an opportun a safe, a psychologically safe place for them to do that, even if you have to test those out in little mini cases first and before you expand it across the whole organization. Like we entered the room in Chicago, like we've entered rooms all year long. The wisdom is in the room and that is the the truth there in in terms of these companies. Yeah.

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Nico Johnson (01:03:10.67)

Daddy and and 'cause then I'll probably ask you the same question. What's one belief that you've changed about AI in the last year?

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Abby Hopper (01:03:17.208)

Say one thing I've changed, thought I've changed about AI in the last year is that I have to figure it all out by myself. Right. Like I I have had this debate with my children. They get really annoyed with me when I tell them I'm interested in AI, using AI, exploring AI. They're of the generation that thinks it's gonna kill us all. And I've said to them again and again, I am not gonna be a middle aged lady that gets left behind by this technology. Like that is not my story. I refuse to be that. and it felt like

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I had to figure it out all by myself. And that is the thing that has really changed for me is that approaching it as sort of this this communal learning opportunity where we can really learn from each other and have no shame about it has been pretty transformational.

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Glenna Wiseman (01:04:04.866)

You know, we had people come up to us after the sessions in Chicago and and un un solicited say this these sessions were the best that they had gotten out of the out of the event. Now, of course, th Stacy Abrams was also there, so it doesn't count them. so, you know, I mean that is a validation of what Abby just said. We're doing this together. The stat that you started us out with, Nico

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was the chief Harris pull around we learn from each other. We're in this together. And I would just say also that the thing that I've learned over the last year, and I've been working with AI for maybe three years or so, but really diving into what I could do is take, don't as Stacey Abrams said, don't be the first one in line to say no to yourself. You know, you can do it. Whatever age you are, you can do it.

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You can explore executives who might be concerned that they're going to look less than to their team, if they talk about their concerns, using it personally and with their own leader with their own C suite, a little bit of vulnerability and tran you know, transparency w could go a long way. You know, and we're all we are all in this together. And I am like if this person

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Over here also in her whatever phase I'm in can can do an AI hackathon heck. Anyone can do it, you know? We're at this together.

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Nico Johnson (01:05:36.686)

Going to tag on here as as you were talking, I was asking myself the question, like, is there something that I've changed in my belief? And I and I I want to add it because I think it should be helpful for other like type A overthinkers like me. not that there would be any of you out there in the audience. I realized that I kept waiting for there to be a moment where I would be able to.

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Abby Hopper (01:05:54.498)

Mm-hmm.

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Nico Johnson (01:06:03.84)

Set time aside, like study it, think about it, figure out like should I be using Claude or GPT? And there's the technology is moving so fast that the belief I've changed in the last year is that I needed to learn in the traditional way how it works. And instead, I said, what if this new technology, unlike any other technology before it, could itself teach me what I need to know about how to use it, which is the

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Glenna Wiseman (01:06:20.853)

AI work.

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Nico Johnson (01:06:32.992)

Absolutely mind-blowing thing about AI. Yeah. Yeah. So I started, I started instead of saying, well, when I like when I kind of wrap my hands around this, I'll start trying to figure out how to use it in my email, et cetera. And I started recently going, okay, ChatGPT, Claude, like, how should I be using what you are capable of to improve my like, here's my schedule. You've got access to my calendar, my email. Where should I be focused? And

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Being vulnerable, even to say this on the podcast, right? Like being vulnerable with yourself to say, like, okay, actually I don't have an executive assistant. What if I could turn this AI into my executive assistant? It has transformed the way I use these tools completely in a way that's like it's it's still mind-boggling. But the best part of it is that I thought that I needed to like make them sort of compete against each other. The

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Best use I've found of Claude is double is b is fact checking AI, open AI. And of open AI is fact checking and like telling me where Claude is wrong. They are really good at critiquing each other and it's fascinating. It's like, well here's where Claude got that wrong.

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Glenna Wiseman (01:07:44.43)

A little joy, baby. A little joy.

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Nico Johnson (01:07:47.966)

I love it. what is something that we need to be careful not to automate?

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Glenna Wiseman (01:07:56.078)

Conversations like these Human Connection.

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Nico Johnson (01:08:01.304)

Yeah. Hmm. Yeah.

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Abby Hopper (01:08:04.024)

Something we should be careful not to automate is the entirety of the hiring process. There's just something about meeting people in person, you know, on Zoom where you can see them, hear their voice, yeah, see that like curiosity in their eye that can't be captured. And conversely for applicants, right? To have to feel like they the the company is making time.

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Meet with them. I've had so many young people tell me they've had interviews with with bots. Yes. How do you have an interview with a bot? It's so sad. Every young person I know has had them.

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Nico Johnson (01:08:36.0)

AI bots.

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Nico Johnson (01:08:44.054)

It's so saddening. I was recently posting for two job roles on LinkedIn and it I think rightly gives you the option to like filter by these qualifiers. I decided not to use them even at the even against the advice of a recruiter that was helping us because I thought like, well, well, if i in s inst basically I felt like it was gonna unfairly and potentially like

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unjustly eliminate folks that are good candidates but don't even know how to express what I'm looking for in their LinkedIn resume or didn't take the time to do it but are like I'm looking for someone in BizOps, right? And if they didn't take the time to put like to really thoroughly flesh out their LinkedIn, but they're now becoming sort of less entrenched in their current job and looking for a new job, they're not marketing professionals. They've spent

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The they're they're gonna approach the job search differently. And you're right, Abby, like the AI or like automation focus that we have on the hiring process, just we have to remember, this is something that I I was Scott Galloway mentioned in a recent article. everyone should listen to the interview that Scott Galloway did with Sam Harris. It is absolutely phenomenal. If you don't listen to the Prof G podcast, I'll try to link to it in the notes.

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But you see, you have to remember that AI models revert to the mean. Like they are looking for the the the most logical average option that should follow the next word, right? It is a it is a reversion to the mean, it is seeking average.

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Glenna Wiseman (01:10:30.167)

Pattern recognition.

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Abby Hopper (01:10:31.028)

Pattern recognition.

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Nico Johnson (01:10:32.078)

So yeah, so go ahead. If you are gonna use AI for a hiring process, go ahead and get used to the average process that you are bringing into your in in inviting into your organization. Yeah, I completely agree with you there, Abby.

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Glenna Wiseman (01:10:44.27)

And and I would mention too that what we would be remiss if we did not mention the equity issues, both r racially and gender, because AI is backward looking. It is pulling from the mass of human consciousness and the mass of human information that preceded in the past, right?

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Nico Johnson (01:11:02.99)

And learning from how we've done things, not how we want to do them.

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Glenna Wiseman (01:11:05.814)

Right. And Abby brought it up saying don't use it to predict because we are the imaginators. Right. We are the ones that want to see whatever future we want to see. And we want to see a future where this is equitable, not only in how these data centers are cited and fueled and p and powered. Yeah. But in who has access and how they represent, right?

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Nico Johnson (01:11:28.194)

Yep. Okay, I got two more questions. Abby, finish this sentence. AI creates real enterprise value when

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Abby Hopper (01:11:35.352)

when it's either solving a challenge that a company is having more efficiently than it otherwise would, or creating a new either revenue generating opportunity or sort of, you know, solution for its customers than it otherwise would have.

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Nico Johnson (01:11:52.024)

Lena, what is one question every leader should ask their employee about AI tomorrow?

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Glenna Wiseman (01:11:57.164)

How are they using it and what are they afraid of?

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Nico Johnson (01:11:59.982)

If we have this conversation again in a year, what evidence would convince the two of you that clean energy organizations have become genuinely better at using AI, beyond just having more people and tools using it and implementing it?

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Abby Hopper (01:12:15.022)

you know, people would be talking about uses that I we couldn't even imagine sitting here today. Right. Like that's that is so that bringing that creativity and that innovation to the problem solving would be one way I would know that it's working, that people are using it. And then the second is that when we sit down and have these closed door conversations, perhaps not everyone knows everything, but at least there's more less patchwork, more strategy.

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Glenna Wiseman (01:12:43.374)

The energy barometer reading would be high on the we invested in people and culture. We expanded our use cases, but we really made it human friendly and human forward. So I'd like to be sitting in that room hearing all about that and helping with it too, Abby and I. So there you go.

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Nico Johnson (01:12:50.382)

Yeah.

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Nico Johnson (01:13:06.35)

Yeah, exactly.

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Yeah, and we will we will certainly link to the Rise forum so that those of you who qualify can sign up and attend next year's Rise Summit. Thanks to Doseki and the great team over there for the leadership they provided, for the vision that that organization has given to this to the industry for more than a decade, and for the the safe space that allowed you all to carry out a workshop that

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now resulted in this in this playbook. again, that's operationalizing AI for enterprise value, a playbook for building trust and accountability. It will be on both of your websites. Why don't you go ahead and share your websites with our audience so they can find you and the playbook and the many other resources that you offer. Glenna will go with you first and then Abby, you can announce your new website.

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Glenna Wiseman (01:13:56.43)

Spell it all out permission to bloom dot com. Or find me on LinkedIn.

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Abby Hopper (01:14:01.678)

So I am now at Gem Advisory LLC, and that's G-E-M advisory L L C dot com.

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Nico Johnson (01:14:10.638)

Fantastic. If you are leading an organization that's adopting AI, I'd encourage you to put today's questions to work with your team. Start by asking what business outcome you're trying to improve? Whose trust you need to earn? How will you measure whether these tools are actually helping versus just giving your team something else to do? Glenn and Abby have provided resources to help do just that, including the operational playbook and the

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AI uplift assessment. I hope you'll complete them. Takes just eight minutes. We'll link to everything that we've talked about today, including the workshop resources. I hope that you, if you are so inclined, will attend the Rise Summit next year. Take the assessment, share it with your leadership team, share it with Abby, Kalna, myself. We're all on LinkedIn. We'd love to see how this episode impacted you. Thank you so much for giving of your only non-renewable resource, or rather the most important, and that is your time.

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We all are grateful for remember you are what you listen to. Thanks again for showing up, so little warrior. It's half the battle.

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