Welcome to Courage to Advance, hosted by Kim Bohr and brought to you by SparkEffect, in partnership with The Empathy Edge.
Tune in to our subseries every 3rd Thursday, right here on The Empathy Edge! Or check us out at CourageToAdvancePodcast.com.
The AI skills gap is widening between high-performing organizations and those falling behind. With only 27% of HR leaders feeling ready to advance their AI strategy, what separates the leaders from the laggards? Join Kim Bohr and i4cp CEO Kevin Oakes as they dive into groundbreaking research on workforce readiness in the era of AI, revealing shocking statistics about executive training and organizational success.
Drawing from extensive research comparing high and low-performing organizations, Kevin shares how leading companies are leveraging AI to achieve up to 30% higher productivity through comprehensive training programs. Discover why companies like Moderna and Mastercard are succeeding with AI adoption rates of 80%, while others struggle to start.
Learn why waiting to embrace AI might be the biggest risk of all, and how to position your organization for success in this rapidly evolving landscape.
Tune in every 3rd Thursday, right here on The Empathy Edge!
To access the episode transcript, please scroll down below.
Key Takeaways:
- High-performing organizations are 17 times more likely to train their executive leaders on Gen AI, creating a significant competitive advantage
- Only 11% of organizations are fully embracing AI across their enterprise, with top performers focusing on both efficiency and effectiveness
- Organizations successfully scaling AI achieve up to 30% higher productivity through comprehensive training programs
- The role of HR in AI strategy has dramatically improved, with non-involvement dropping from 41% to 22% in recent years
- Creating a “change-ready” culture is crucial for successful AI implementation, emphasizing learning over knowing
“You want to create a workforce and a leadership team that are agile and that not only can roll with the punches but can embrace them and figure out how to use this change to our advantage.” – Kevin Oakes
About Kevin Oakes, CEO at i4cp
Kevin is CEO and co-founder of the Institute for Corporate Productivity (i4cp), the world’s leading human capital research firm focusing on people practices that drive high performance. He is the author of Culture Renovation®, an Amazon bestseller which details how high-performance organizations successfully change organizational culture. Kevin has an extensive background in HR technology and corporate development, previously founding SumTotal Systems and serving as Chairman & CEO of Click2learn. He currently serves on several boards and is dedicated to advancing human capital practices that create lasting organizational success.
About SparkEffect
SparkEffect partners with organizations to unlock the full potential of their greatest asset: their people. Through their tailored assessments and expert coaching at every level, SparkEffect helps organizations manage change, sustain growth, and chart a path to a brighter future.
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FULL TRANSCRIPT:
Kim Bohr 01:30
Welcome to courage to advance. I’m Kim borer, and I’ve got a startling reality to share. Only 27% of HR leaders believe their organizations are truly ready to advance their AI strategy in the next few years. Yet, companies that are scaling AI are seeing their employees become 30% more productive. So what do they know that others don’t? Today, I’m joined by Kevin Oakes, CEO and co founder of i Four CP, whose firm conducts more research in the field of HR than any other organization. We’re diving into their groundbreaking new study on workforce readiness in the era of AI, exploring why some companies are 17 times more likely to succeed with AI adoption, and what’s really holding organizations back. Let’s get started just a little bit about Kevin before we jump right in. If you are an HR leader in a strategic role and you are not familiar with ifrcp, you definitely need to check them out. We’ll put links in the show notes. Their firm conducts more research in the field of HR and than any other organization, highlighting next practices that organizations and HR leaders really should consider adopting. And Kevin is also the author of a really, really fabulous book that’s also a best seller on Amazon called culture renovation, 18 leadership actions to build an unshakable company. So Kevin, welcome to courage to advance podcast. Thanks, Kim, glad to be here and thrilled to have you with the time we have the partnership we have outside of this podcast, and just excited to have all of our listeners get to share in so this is a really important and timely research that your firm is doing. And so what inspired Ifor CP to you know, to really conduct this research on AI workforce readiness at this time? Yeah,
Kevin Oakes 03:20
it’s really part of an ongoing series of research we’ve been doing on AI for, really the last four to five years, even before chatgpt got us all so familiar with AI, and specifically Gen AI can do for organizations. What we’ve been trying to track Kim is just, how are companies preparing their workforce. How are they trying to leverage AI in the future? And how is HR involved in that? And so this latest study called workforce readiness in the area of AI is just really looking at companies progress boards making sure that they are ready to take advantage of AI. I think one important aspect of our research is that we’re always delineating between high performing organizations and low performing organizations. We define high performing organizations as those that have better revenue growth, profitability, market share, than their competition, and we look specifically at the people practices in both of those either ends of the spectrum there, and we often find big differences in how high performing organizations are implementing their people practices or their people strategies versus those low performers. But what we really hone in on the concept of next practices. And while we come up with a lot of best practices, we find that there are certain practices that are highly correlated to bottom line, business impact or market performance, but not a lot of companies have yet put the practice into place, and so that’s a cue for us that it might be a next practice. And so this particular study, we found a lot of those. We found that this is so new that not a lot of companies are, you know, yet really grasping. How to Get the workforce ready for AI. But there’s a lot of things that other companies can take away from those leaders in the marketplace. What was
Kim Bohr 05:07
some of the parameters that you looked at in this study just to kind of set the stage? Well, we
Kevin Oakes 05:13
looked at a number of different things around how those high performers are treating AI. So for example, we looked at, are you already operationalizing or scaling AI in your organization, or are you just researching and experimenting with AI, or maybe you’re ignoring it or actively opposing AI. And it was really fascinating to us that those who were already operationalizing it, they were high performing organizations. So some of the best organizations that are out there are some of the quickest to adopt AI, and the companies that are ignoring it, they were by far the low performing organizations. And I think you’re going to see even a bigger separation going forward, unless you know companies do start to adopt AI. So that was sort of an overall premise, and then we honed in on those companies that are operationalizing it, and what are they doing? How are they getting their workforce ready for AI, a lot of it revolves around training, but they’re also just thinking about workforce planning and their future skills, and what do we need, and what are the skills gap? So all of that went into this particular study, which is highlighted by a lot of case studies from different member organizations that we work with.
Kim Bohr 06:24
So one of the things that you you know just going on to what you were talking about from high performing organizations, your study found that two and a half times or they’re more likely to operationalize it compared to the low so what do you feel like the sense is that those organizations are doing differently that are so much for further ahead?
Kevin Oakes 06:42
Yeah, I kind of separated into two camps. I think the initial way people usually look at AI is from an efficiency standpoint, how do we take some rogue tasks, things that just take up a lot of time and are very repetitive? How can we automate that and have Gen AI handle some of that. So from an efficiency standpoint, we still got a long way to go. We’re only in, you know, inning one of a nine inning game here, you know, I think that’s where a lot of companies are experimenting right now and trying to, you know, create more efficiencies across the organization. But the other side of it is effectiveness. How are we using Gen AI to make our services better, to create product features that people will want, and improve our products externally. It’s more of a customer facing or market facing attitude towards Gen AI, we still get a long ways to go there, but you see it in most software products today, particularly in HR I was, I was at HR tech this year. And you know, most of the vendors are going to tell you they have some kind of AI component to what they’re doing that will help improve, you know, aspects of what their software does. So it’s sort of two sides of the coin there. Kim and, you know, I think, again, I think companies just need to have a fresh look at what they’re doing. One of the things that we’ve discovered is there are a lot of very clever ways companies are using AI, particularly in HR today, that other companies could implement, but they just haven’t thought of it, right? They just don’t know about it. And so we’re trying to showcase all these really clever uses to our other members, because once they see it, it inspires them to say, hey, you know we could do that too. It just never occurred to us that’s how we could be using AI. And that kind of discovery process, I think, is going to happen over the next few years, as we see more and more really cool applications of Gen AI.
Kim Bohr 08:31
Are you just out of curiosity, perhaps not related directly to this research, but you mentioned seeing, you know, the AI application inside organizations from a customer service standpoint and product standpoint, but then also internally to their own efficiencies. Do you find there’s an interesting, you know, favoring one or the other, or if they’ve done it well, they’re doing it well on both ends, kind of both spectrums
Kevin Oakes 08:53
at all. Just efficiency is certainly, you know, where most people are spending their time these days. It’s trying to speed up processes. How can we free up people’s time to be more strategic if they’re spending a lot of time on very rote tasks? So certainly, the efficiency side is where you know most of the effort has been focused. That makes
Kim Bohr 09:13
sense. So another aspect of your survey saw that 55% of those at organizations that were scaling AI are actually the ones that are more fearful of their job being replaced by AI, compared to only 25% of organizations which are ignoring it. And so is, do you feel like that’s driven by maybe scarcity or fear in some aspects of those that are motivated or are there? Is there some other factors that you found in relevant to size of organization or industry or anything like that. Yeah, let’s
Kevin Oakes 09:44
back up a little bit. The concept of, is AI going to replace my job? You know, has been a fear for a while now, right? And we’ve been fearing that for years and years, just with automation and robots, etc. And the reality is that AI is replacing very few jobs. These days, over time, there’s no question that the workforce will shift, and there will be roles and responsibilities that AI is doing more of than what we’re doing today. I think the smart companies are recognizing that we can redeploy talent in more strategic and effective ways if we can use AI to free up things that don’t use a whole lot of brain power of that very valuable talent, we have a case study of IKEA. Is good example of that, and I think just a very simple example where they applied AI to their customer service department. And a lot of companies have done this to help speed up finding answers to very common problems when customers call in. And so they were able to take a number of their customer service agents that would have normally done that job and reapply them to a new burgeoning industry or or offering that IKEA had, which is helping their customers with interior designs. It’s a virtual interior design and, you know, it’s a paid for service that IKEA offers. And what better way, you know, to spark that business by taking people who already know our products, and, you know, are very knowledgeable about what we do, and have them help others with that interior design. So that’s a case study that’s out on our site. And there’s a very simple one, but it’s a good example. Of where you can redeploy talent. But I said, let’s back up, because I think first we have to think about training the employees on AI. And a lot of companies today still haven’t done that. If training has happened on AI, it’s happened to a very small segment inside the organization. The majority of organizations haven’t trained all of their employees, for example, on AI. Well, we find that when employees do get trained on AI, they recognize they could be doing so much more with it. In fact, we found in our study that in those high performing organizations, the employees that were trained on AI felt like if they received more training, they could be 30% more productive than they were today, even more than 30% productive. So that was an interesting finding, but what the one you referenced was even more interesting. The more they got into AI, the more trained they got on AI, the more they recognize that, hey, there are big aspects of our jobs or other people’s jobs, that can be done by AI. And so that’s where that fear factor comes in. And I don’t know if it’s fear is the right word. It’s maybe just recognition that, you know, things can be done much more efficiently by using AI than what we’re doing today. If you look over time, that’s happened throughout history, right? So Henry Ford had a great quote a long time ago. He said, If I asked my customers what they want, they would have said faster horses, right? As opposed, you know, automobiles, yeah, you look back to the, you know, invention of the railroad, etc. And, you know, over time, we’ve always had this happen, right? We’ve had automation make things better, and there’s a lot of fear that is going to dramatically change, you know, the people’s jobs. It eventually changes jobs, but they morph. They don’t go away. They just simply morph into doing other work around automation. And that’s obviously what’s going to happen with AI as well. Yeah,
Kim Bohr 13:21
you know, I was at a event a couple of months ago talking with HR leaders as well around AI. And one of the things that was really fascinating in this topic of, you know, job evolution, was that by sitting on the sidelines, that’s where there’s a lot more risk than getting involved. And it’s interesting to find the varying degree of which people are experimenting or avoiding or full on committing. And I think your research really just continues to reinforce that very large spread. And, you know, one of the things you were talking about from the training perspective, I think is very interesting, is, what is there a generational gap around adoption? You know, it’s something when you think about people thinking about where the who’s diving in, and you think about the statistics around, like, where’s the strategy landing, and what’s not being conveyed around strategy and use of AI, do you feel that your I don’t think your research explored this, but do you just have a sense that there’s anything generational there, or is that an area that we maybe need to be looking at To help get everybody more on the same page?
Kevin Oakes 14:22
Yeah, there might be. We’re not, as an organization, real big on trying to just label people based on, you know, their age, yeah, generational divides, yeah. Sort of another, you know, form of, I don’t know, just discrimination sometimes, but, you know, just looking at people, you know, by generations, and labeling a generation is one thing. I think there’s a lot of individuals in each generation that are quite capable of leveraging AI. And frankly, I’m seeing it all over the place with boomers. You know, you would normally think, okay, older, you know, folks aren’t going to rush to, you know, really understand AI and leverage AI, but I’m seeing lots of them do that. I suppose. If you. Look at it by generation, you’re probably going to see some differences in generations, but we didn’t tackle that. We didn’t think that was part of what we wanted to do here.
Kim Bohr 15:06
Yeah, that makes sense. I know. I think in our conversations too, from what the work we’re doing at Spark effect and working with leaders, I don’t know that we’re seeing a generational component either, but I do think we’re seeing just different across the board, regardless of what kind of role people are holding, but I do feel that we are starting to also see some separation of getting everybody in the leadership team, on the same page. I think that’s kind of a big and I kind of got that sense from the work you were, you all did, was that there’s a big opportunity there to get everybody online, because that’s probably where it needs to start. One of the things that that was really interesting also in your research, you talked about it, identified the top five barriers to AI readiness, lack of organizational knowledge about Gen i ai led at night, 39% lack of AI specific training at 27% and then I thought was really interesting is this lack of strategy articulated by senior leaders comes in at 24% I’m just curious what jumped out to you and your team when You saw those top three indicators, and if there was anything that has prompted you maybe to want to explore anything further from that lens?
Kevin Oakes 16:08
Well, yeah, like I said, we’re continuing to research this, so this is a very longitudinal topic area for us, and we’ll continue to look at how companies are improving. And frankly, we have seen some big improvements. We came out with a study a year ago called is HR already behind in the AI revolution? And so I’ll cut to the chase. The answer was yes, HR was already behind. And what we were finding is that in many organizations, HR was being left out of the strategic conversations and the governance conversations around AI, which is kind of silly, because AI affects the workforce. You know, first and foremost, HR, if you’re going to say who’s in charge of the workforce, you know, most people would say HR, you know, is most knowledgeable about the workforce. That has changed dramatically. We found in this particular study that was cut in half. I think we had 41% of organizations where HR wasn’t involved. Now it’s only like 22% something like that, and HR has gotten much more involved in identifying what the strategy should be, what the governance should be for the workforce going forward. But you started out that question just talking about leadership, and I want to just touch on that, because we found leadership is super important to adoption of AI. No shocker, I suppose, but the stats that we found are kind of shocking. We found that in those organizations that are already scaling and operationalizing AI, they are providing targeted training for their senior executives, and so those companies are 17 times more likely to have trained their executive leaders on Gen AI. They’re also 15 times more likely to indicate that their executive leaders are using Gen AI at least to a moderate or high extent inside the company, and then 10 times more likely to say those executive leaders are encouraging others to use Gen AI to a moderate or high extent. And I think it just goes to show that if leaders are involved and they understand Gen AI, then as a workforce, as an organization, you’re going to be more likely to, you know, be ready for the future and be already using Gen AI inside the company. I think a lot of those companies that are ignoring or opposing Gen AI or, frankly, even just in sort of the research mode, you’ll find that the senior executives probably aren’t that familiar. They don’t have that hands on experience. They haven’t been trained. So I think that that was a very interesting finding, just seeing how big the difference was there.
Kim Bohr 18:37
Those are astonishing statistics. So if you think about from the HR leaders lens, you know, how can they have a more prominent voice in this policy discussion, right? And getting everybody aligned, yeah,
Kevin Oakes 18:51
what we encouraged in that initial study that we did HR to do is, first of all, get you start using it right? So get familiar with HR with AI and begin using it also what I said earlier, look around at what other organizations are doing, because that’ll give you inspiration of how to leverage AI within your HR function. There are certain areas of HR that have adopted AI more quickly than others. Probably, talent acquisition has adopted it the fastest and is really seeing good results from Ai. They’re using it to find passive candidates, you know, much more efficiently than sort of the manual way we were doing it a few years ago. We have one case study where a company is using Gen AI to send emails out to passive candidates on an automated basis, seeing if they can get them interested in different positions in their company, and they were finding dramatic improvement in the response rate from the Gen AI emails versus the human written email, which we thought was really fascinating. And there’s a whole bunch of other ways TA is using it just to help the candidate experience. Experience, etc, but TA has been a big user of it. I would say L D is the other 1l. D is right up there with TA and all the research we’ve done, and they’re using AI to provide personalized development paths for individuals. They’re from an instructional design perspective. They’re using AI to much more quickly, create courseware and design, you know, design those courses. So L and D is one that also really embraced, AI, for sure.
Kim Bohr 20:28
That’s great to hear. And I think it’s so important to for more of that to be coming forward, because we talk about HR, you know, trying to keep that seat at the table and but yet, carrying being expected to solve all of the organization’s problems, it seems like it many times. And so this is a big one of, how do they continue to to coordinate? When you think about all the different, you know, stakeholder interest around the security lens and you know, the IT lens, and the actual, you know, application internally, I think it’s a huge opportunity. Was there, has there any been any interest in the research you all have done of some of the different studies of looking at AI and this skill based world that’s starting to evolve in so many organizations, or is that not something that has kind of crossed paths yet?
Kevin Oakes 21:11
No, it’s crossed paths a little bit. We’ve done a lot of research just on how organizations are leveraging skills, and most organizations have morphed into a skills based approach across, you know, a lot of things, what they’re doing, what hasn’t really worked is creating internal talent marketplaces based on skills databases inside the organization, in many companies, that has stalled out a bit, just because the culture isn’t ready to leverage that. And so that’s a whole nother issue, and we felt that for a lot of things, and Gen AI is included in this, you have to really first focus on the culture of the organization. Are they future ready? Are they agile? Are they ready to accept, you know, some of the things that you want to put in, and particularly with an internal talent marketplace, you know, where we have such a job mentality inside of organizations, versus a project or gig mentality, and even where you know, talent mobility isn’t all that common. You know, in a lot of organizations, that kind of that internal talent marketplace is going to stall out a bit, but you can use Gen AI to help on the skill side. Certainly, Gen AI can help identify the current skills that you have and what’s the gap with the future skills that you need going forward, it can do that a lot more quickly than we can as humans. And so I starting to see some application there on the skill side.
Kim Bohr 22:30
So it sounds like maybe those are some of the things that some of those progressive companies you’ve seen adopting are starting to bring forward as some of these best practices, or future practices as well.
Kevin Oakes 22:39
Yeah. In fact, what we list out in this particular study on the future ready workforce, they’re doing the ones that are really high on future readiness. They’re doing some things that are a little bit over and above what most companies are doing. So for example, they’re cataloging their current skills and capabilities. It’s sort of a difference of 48% to 10% you know that they’re doing, that they’re forecasting their future skills needs. They’re identifying the skills gaps. They’re offering up skilling, or I don’t love the term re skilling, but they’re offering those opportunities and then exploring sources of talent outside of their full time workforce. You know they tend to have a cadre of gig talent that they can tap into when needed. So all of those are components of being a future ready workforce.
Kim Bohr 23:26
I think that’s really important, so important in the work we do at Spark effect, where we’re working with executives around from a very high level executive coaching lens, or leaders trying to create alignment to be able to obviously be ready for what’s coming. And I think we find there’s big gaps in leadership readiness be to not only deal with this, you know, very new work, remote workforce, that people have finally got used to. And now here comes another layer of complexity, and how to lead in. And so we’re finding these topics to be really relevant. You know, just in how leaders are trying to get their arms around it all, and we find that helping them understand where, as you mentioned, some of this just tactically can help them is great. And then where is it that can strategically help them, when we think about the AI and their role and how they can be more informed, when one of the things that your research shows that I want to talk about a little bit more is that high performing organizations are investing heavy. You mentioned that 65% are specific training at the executive level. Yet there’s many organizations that seem to be taking a more reactive approach to that leadership development lens that we’re talking about. What risks do you see that organizations may have that were really more proactively, like getting on board in this more organized way.
Kevin Oakes 24:47
Yeah, it’s still a small percentage of companies that are leading from an operationalizing perspective. It’s only about 11% of all organizations are really embracing AI in their work. Flows in their organization, across the enterprise, really. So I think the risk is, the longer you wait, the harder it is to catch up to some of those organizations. For example, the companies that have embraced, AI, they’ve done a lot of training, not only across the workforce, but particularly with their leadership, as we outlined before. And they’re already in, you know, a lot of brainstorming. You know, this brainstorming mode of, you know, enabling the workforce to say, here are areas of my job that I think could be automated. And that’s one of our recommendations, is to enlist the workforce in that task right, to identify parts of their jobs that could potentially be automated. You have to have a psychological safety to do that. You have to have an environment where the employee feels like that’s going to benefit them, not hurt them, to be able to do that. But you move much more quickly if you can evolve the workforce in identifying that. But the ones that are forefront now are starting to look at agentic AI. You know, how can I put in AI agents that are doing complete tasks for us going forward. And you know, how can we create more of these, you know, over time that will even further speed up processes for us, you know, or make us more efficient, whereas those laggards, the ones that are, you know, still sort of researching or even ignoring AI, they probably don’t even know what agentic AI is, right? And so they’re just, you know, they’re falling further behind in this whole space. So, you know, our advice is, don’t, don’t sit on the sidelines. You know, you got to get involved. You got to start creating some sandboxes where people can experiment safely about, you know, using Gen AI, you got to create some governance around it so people know how to use it. But also, more importantly, articulate your strategy. That’s what still a lot of companies haven’t done. They haven’t talked about, you know, how do we think we’re going to use this strategically long term, all those are, you know, aspects of trying to get up that curve, that maturity curve, towards operationalizing. Ai, why do you
Kim Bohr 26:58
think that is that they haven’t been able to articulate that? Is it that alignment piece, getting leaders on the same page? Is it just the complexity of who owns what? Do you have a sense
Kevin Oakes 27:07
all of that? And, you know, look, change is hard, and a lot of lot of organizations are change resistant. They don’t, when they look at change, they think it’s not only a nuisance, but a lot of them fear, you know, change, especially if things are going well within their organization. And history has shown time and time again. Our research shows this over and over again. Companies that not only are used to change, but the ones that embrace change and look at change as an opportunity, right when things are changing in the marketplace. You know, how can we make use that to our advantage, right and benefit from that change? Those are typically the leaders long term and with things constantly changing. Gen AI is a great example of a huge change in our environments, but there’s going to be more. You want to create a workforce and a leadership team that are agile and that not only can roll with the punches, but can embrace it and you know, figure out, how do we use this change to our advantage? So
Kim Bohr 28:04
I think that change is so important. And I think one of the things that I’ve been really fascinated with lately is that there’s this idea of, you know, change is we know it’s happening. We know it’s constant. It’s always there. And yet we still have this almost, you know, parallel thought of, once I get through this thing, it’s kind of that arrival fallacy, and I talk about that in this January podcast of once we get through this, things will be easier. I’ll have more space. And I wonder how you know, at some point I think those have we have to reconcile those two thoughts to be really one, in order to be more, to take advantage of what’s in front of us. So I’m curious if that change exhaustion, or any of that you know, as you talk about from the research, if that’s something that companies really need to be understanding that in order to make that shift to what you’re talking about, of being more leaning in and more, you know, embracing. So I’m just curious if you have some thoughts on that, something I’ve been very fascinated by,
Kevin Oakes 29:00
yeah, you mentioned the book that I wrote, culture renovation, and I talked a lot about this in that book. And there’s a lot of history to this of how organizations have tried to condition a workforce to constant change. You just use the word change exhaustion. I would try to change the attitude towards change excitement, right? You want a workforce that is very comfortable with change, but actually gets energized by change, as opposed to exhausted by change. And so it’s an attitude shift. You can hire for it, for sure, I think more importantly, you want to create a change ready environment. There’s a lot of companies that induce change on a regular basis, just to keep the workforce accustomed to it right? Just so that people don’t get to this point where they don’t want things to change. I think that it’s critical, and Microsoft did a great job in their culture renovation. Satya talked a lot about I want to learn it all attitude inside the organization, versus a know it all attitude. And really, what he was getting at there is I want an organ. Organization that’s agile. I want them to constantly be learning. I want them to embrace new things, share their knowledge internally. And anytime we find a company that says we have a learning culture, they not only are a very change ready culture, but they’re a company that typically is off the charts, high performing, meaning that, you know, they have better market share, profitability, you know, revenue growth, etc. So I think it’s an important concept. I think if you’re trying to be a high performing, high performing organization, you have to get that attitude in the culture of the organization,
Kim Bohr 30:32
yeah, and I think that’s something that’s, like you said, hiring for it being very intentional. I think that’s really the key one as we move into some of our kind of wrapping our conversation up. One of the interesting findings in the research is that organizations successfully scaling aren’t just focusing on technical skills. They’re really investing in more of these leadership capabilities you have mentioned in our conversation prior around, companies like moderna achieving 80% adoption rates. MasterCard success with AI initiatives or significant? What role are you seeing? The executive development playing into this? Anything that you feel like you know, again, we’ve put up so much on HR, what do we do to get everybody you know more to have these kind of results that you all have been able to document through some of your clients? Yeah,
Kevin Oakes 31:18
those are two good examples of dozens and dozens of case studies that we’ve tried to capture, going back to the notion that I said earlier, where people are doing really cool things with AI, but you just have to get other companies to see it, to help them, you know, understand what they can do with AI. And moderna and MasterCard are great examples of where they’ve embraced Gen AI, throughout the organization have trained all employees on Gen aI have very specific training offerings and continuous training offerings. They don’t just stop at the basics, right? They’re helping people really advance their skill set. And the leadership in those organizations has been very clear on the fact that they have an AI strategy and what it is, and the leaders are using AI like I talked about before. In fact, if you go out to modernist site, they have a great video that showcases how they’re using this across the organization and really trying to advance, you know, some of the solutions that they’ve been providing to society, trying to do that in a much more rapid way. So good, you know, just two good examples. But there’s many others out there, depending on what industry you’re in, or, you know, size of company, even you can really learn a lot from some of those companies.
Kim Bohr 32:31
So as we wrap up the conversation and we think about, you know, what your research has shown, what are maybe the top, you know, three takeaways or so that you feel like listeners should really be hearing and what’s going on and what able to start to think about what actions they should take.
Kevin Oakes 32:49
Yeah, we have some recommendations in the study we’re coming out with, so one of them is what I said earlier, engage your workforce and identifying where parts of their job can be automated and used, you know, leveraged with AI. I think that’s a big one, the agentic AI that I talked about. So if you’re not familiar with that, get familiar with it, because that’s going to be a good big part of, you know, of AI going forward, training everybody, including leaders, is a big one as well. Is sort of a simple one, but just so many organizations haven’t really embraced that and then creating a future ready workforce. It’s not just about AI readiness, it’s about being future ready as a workforce and addressing some of those change issues that I talked about. Those are some of the broad recommendations that we have, and then we have more specific recommendations underneath each one of those. One example, you have a love for leadership, we find that some of those leading companies are having leaders teach, and leaders as teachers, has been a concept that’s been around for quite some time. Jack Welch actually popularized it decades ago. But while most companies don’t do this, they don’t have their leaders teach, the ones that do tend to be those learning cultures that we talked about, and there’s a lot of benefits when you have leaders teaching others. You never learn something as best as possible, unless you’re forced to teach it. But there’s also a lot of, I just think, interaction with the workforce and leadership that happens when leaders are actively teaching. So that’s one small recommendation underneath the hey, you know, let’s train everybody recommendation.
Kim Bohr 34:21
That’s a fantastic recommendation as well that we need more people modeling what we want others to be able to embrace and do. As we wrap up any final thoughts or points you want to make sure the listeners get to particularly like
Kevin Oakes 34:36
you’re behind. Don’t worry, you’re in good company, because most, most are, yeah, so we’re really early in this process, and you can catch up. There’s no question about it, you can catch up very quickly in this AI game. But don’t wait, because the longer you wait, the harder and harder it’s going to be to catch up. And so I would just encourage listeners to do what they can to try to get the workforce up to speed on AI and just. Be ready for this future that, obviously is Gen AI is going to play a big part in
Kim Bohr 35:04
Absolutely. It’s not slowing down, it’s not going away, and so we better just find a peace with it, dive in. So thank you so much, Kevin. I so appreciate your time and this knowledge and information for our listeners. We’ll have free resources at that you can download, take advantage of we’ll have links to what you’ve talked about, Kevin, so people get familiarized with this report and some of the recommendations that you’ve suggested for our resources, they’ll be at courage to advance podcast.com. I want to also thank the empathy edge for hosting our podcast sub series and to our the listeners for tuning into the episode of courage to advance where Transformative Leadership isn’t about having all the answers, but it’s about having the courage to find them. Thanks again, Kevin and we’ll tune in again for another episode of courage to advance next month.
Kevin Oakes 35:51
All right, thanks Kim
Maria Ross 35:54
For more on how to achieve radical success through empathy. Visit the empathy edge.com there. You can listen to past episodes, access show notes and free resources. Book me for a Keynote or workshop and sign up for our email list to get new episodes, insights, news and events. Please follow me on Instagram at Red slice. Maria, never forget, empathy is your superpower. Use it to make your work and the world a better place you.
