Name: The AI-Enabled HR Leader: Driving Workforce Transformation in an Era of Disruption
Uploaded: 2025-06-11T18:16:05.178Z
Duration: 1 h 2 min 36 s
Description: The AI-Enabled HR Leader: Driving Workforce Transformation in an Era of Disruption

Transcript for "The AI-Enabled HR Leader: Driving Workforce Transformation in an Era of Disruption": Hi, everyone. Thank you so much for joining us today for the event, the AI enabled HR leader, driving workforce transformation in an era of disruption. I'm Kate Harner, and I'm on the marketing team here at Betterworks. We're so excited for you to join us today, and we'd love to hear where you're joining us from. So over on the right hand side, a lot of you have already found the chat, which is awesome. You can put in where you're calling us from. We'd love to hear. I'm personally calling from Charleston, South Carolina. I'm very grateful now that we're heading into the summertime on staff and conditioning. Before we dive into today's webinar, just a few housekeeping items. This webinar is being recorded, so we will send you the on demand link in tomorrow's email so you'll get that shortly. And if you have any questions for our speaker today, please use that q and a tab over next to the chat. We would love to hear from you. Charlene will be taking questions throughout the presentation, and we'll have time for q and a at the end. So definitely take advantage of that q and a tab. And lastly, we have a documents tab right there in between chat and q and a where we've got some great AI resources for you. This webinar is part of our people fundamental series, which is all about HR leaders and building community with your peers and fellow thought leaders. We, we provide an HRCI credit for each webinar, and, again, that will, be in your inbox tomorrow with the company in place. And we feature, speakers from all over, lots of, diverse voices from analysts to authors to practitioners. So we're really excited for you to join us for this next week of eight hours. Now it is my honor to introduce you to our speaker for today. Charlene Li is the author of six best selling books, which is as someone who would love to, be an author herself one day is just so so upsetting. She also has, consulted for giant corporations and has been instrumental in leading, in times of disruption and showing us, especially as HR leaders, what we can do during eras of disruption to make sure that we shape the change that she wants. So I'll let her take it away so you can start enjoying her knowledge. Please welcome Charlene Li. Thanks so much, Kate, and hello, everyone. And thank you for coming from all over the country, all over the world. So excited to be here with you today. Alright. I'm gonna be sharing some slides and going through them today. And one thing in particular I wanna talk about is especially, you may have heard this quote before. There's a lot of fear and concern, a lot of uncertainty and doubt out there. And what I wanna talk about today and my theme for today is that AI is not here to replace you. It's here to elevate you. And we're gonna go through and talk about how that works just for you as an HR leader and also for your team members, for your colleagues, for your organization. And the way I would characterize our approach to AI these days and I am here in San Francisco in the middle of this huge bubble of AI. And right now, I would say the sentiment is lots of FOMO, fear of missing out. And the reality is when I leave this bubble, there's also another predominant concern and and feeling, and that is what I call FOGUE, fear of getting in. There's there's there's we're being pulled in two different directions. We you're excited about the possibilities, but we're very concerned about also what the implications are, what the the barriers are, and also the potential harmful aspects of this. And this is particularly strong in The United States and especially, I I appreciate that we have such an international audience here today. This is some statistics put up by the Stanford AI index, and it's a percentage of people in each country who see AI products and services as more beneficial than harmful. In China, it's 83%, and in United States, it's less than half than that. Only 39% of people believe AI will be more beneficial than harmful. So we're fighting some headwinds in The United States and and and and several of the other, countries in the Western Hemisphere. And what we're finding is that it's really this concern, this history, and and also lots of cultural issues, governmental policy issues that is driving this concern. So what I wanna talk today is about how AI is gonna be used, how it can empower and enable you as a leader to be able to bring the goodness of AI, downplay, and and also mitigate the risk and the downsides of AI while we do this too as well. So the three things I'll be talking about today is the future work. What does that look like? And then, also, what is HR's role? And and I believe it should be a substantial role in developing AI strategy, and then just some tips on how to get ready, get set, and just go. If you're going already, these these are ways to go even faster. So let's get into the future of work. So you may have heard this quote before that AI won't replace you, someone using AI will. And I like to say that it's it's I would like to modify that a bit because the the reality is is that AI will take on so many of the tasks that we do today. And I I believe this is gonna happen in a few stages. So, again, I wanna talk about how it goes from augmentation to restructuring the way the work is done. So in the stage, we're right here right now. AI is enhancing us. It's augmenting us. It's removing a lot of the drudgery. I do a lot of writing and, research and AI has been a game changer for me. If you're doing, work in in HR around creating, job descriptions or reviewing resumes or looking at job performance and doing analytics around the workforce. Again, AI is changing the way we do the work. And so the tasks are being automated, and it's starting to change our jobs. And this goes into stage two. When our jobs start to change, then we're going to see some of these jobs going away, some of the jobs being restructured and and and moving around. So we're going to have to reskill. We may have to redeploy. And in stage three, this is when agents come into play. And that is a game changer because these AI agents and I'll explain what they do in just a The AI agents are going to transform the way we work completely, the way that work is done. Because now instead of having people be able to oversee the AI at work, we're just going to have the agents do the work itself. Now it's it's not gonna happen for a while. These agents, people talk a lot about them. Some of them are incredibly interesting and promising. But the idea that you could wholesale replace people with agents is still in the works, but I do believe it's going to come at some point. So we we anticipate that this is going to be a significant change. And for HR leaders to be involved and to move into the space with eyes wide open, instead of saying, oh, AI won't replace you, we're just gonna augment people. Well, the reality is jobs are going to change because tasks are being automated. And as jobs change, careers will change, our workforce will change, and we need to be proactive in anticipating where those changes are going to come from. Let me give you a quick primer on AI agents. So agentic AI, we have lots of these already in our lives. I define it as a goal oriented system that can plan, it can take action, it could learn, and it can adapt to its environment and to the situations, without any instructions from a human. Right now, a lot of AI that's out there requires that you be at the keyboard to give it prompts, to ask it questions, to give it commands, and then they'll will produce it. But with agents, they're very specific to a particular task. So we have them in our homes. We have these AI driven robotic vacuums. I have a nest sitting on my wall that keeps it just perfectly at 68 degrees. And now we're beginning I have this little a bit of a a a screenshot here. This happens to be in particular a a Salesforce demo of an agent that can go through and just do some routine tasks. But you can imagine that when a resume comes in, it looks at it and processes and moves it through your workflow, an agent could potentially do that with judgment that has been trained into it to define what quality and accuracy looks like. So today, what we have happening is we have AI agents doing some very simple things with AI. So we can have AI, for example, analyze resumes for us. We can do meeting scheduling. It can answer some questions that people may have, around HR functions. But with the Genentech AI, lot more of that work, the workflow itself starts getting automated. So you think about the whole entire process of talent acquisition, the whole process of onboarding somebody that you can take that whole entire process of having agent do that. When somebody's signing up for benefits, which can be very complicated, you can have an agent walk somebody through all of these places. And the key thing that has to happen in order for this to happen is that we have to have trust. We must be able to trust that these agents will do the right job in order for us to remove our fingers away from that process to get out of the loop. And so I wanna give you just a quick schematic that that talks about how these work. And so, again, the whole thing about agents is that they take the human out of the loop. There is an orchestrator, which is the actual agent, and it interfaces with you and it understands there's a knowledge base. It has some skills and capabilities to be able to act. It has some autonomy to be able to, do these things, and it talks to an AI. So, again, these are ways that we can structure these agents so that we can see into the agent and understand how it's doing its work. Very importantly, because if it's not doing the work correctly, we can go in and understand why it isn't. In the same way, you may have a new employee. You're coming in, you're training them, and they will may do things perfectly well, but they may be a little bit rough in the edges over here, so you're gonna polish it and shine it and tell it's just right. And what we're seeing is that we believe that 30% of human work could potentially be handled by agents within the next five years. So what the impact on jobs are significant, where the estimates are that between 5360% of entry level tasks are automatable. It doesn't mean that they will be, but they could potentially be automated. And that also that quite a few new jobs would be created. Everything from monitoring these agents to looking at the quality control, to training them, to again, there are so many new jobs that are created every year. Just think about social media, analyst, you think about the ways that we're using AI today, that didn't exist before, even just five years ago. So we do think that things are gonna be changing constantly, but that also about 60% of jobs are gonna be transformed by 2040. So what does this mean? In the near term, we do see that in particular about 14,000,000 jobs will be lost because automation will be coming in. There was tremendous pressure on companies to free up capacity, and we're seeing it already impacted in the entry level jobs in particular. And by 2030, though, we'll see a a change in this because we do believe that 72 78,000,000 new jobs will be created because of AI. Many will be lost, many will be created. Alright. So one thing I wanna point out is that women in particular are very vulnerable to the impact of AI. And this is because, especially in high income countries, 41% of women's jobs are at risk compared to 28% of men's because women are overrepresented in these jobs that tend to be much more, automatable, clerical jobs, administrative jobs, support roles, jobs that are again, this very again, people are looking at and saying, how do we take and use AI to augment these jobs and potentially automate them? And then we also know that when these entry level jobs go away, that the opportunities for job progression, career progression, and wage growth go away too. And then also, the other aspect is that women are underrepresented, continue to be under underrepresented in the tech jobs and AI jobs, both in the technical roles and especially in leadership roles. So, again, I I I just point out that these are things we need to be very aware of, as AI is coming into workforce. So what are the implications for HR leadership? Again, we find that from the research that many of us are using a AI, 72% are using AI work, and that's up significantly from last year, 58%. Again, ethics and responsible use of AI is highly important, but only 37% of HR leaders report that they're actively involved in discussions at the highest levels of the organization about the use of AI, especially from a responsible and ethical AI use. And then 95% of HR leaders are not in, in any way or just moderately involved in implementing AI in the in the organization. And I wanna stress how important it is, and this is why I'm so excited that so many of you are here today because we need to close the gap. We need to close the gap of knowing, doing, and leading AI. So we know that AI is gonna be transformational. Many of you are actually using it and doing it, and it's starting to transform the way you work. But what we need now are leaders to step in and to lead the way that AI is transforming your organization. So I'll give you two examples of how HR is actively participating, and this is, again, not the norm. But if you wanna take just how far this can go. At Moderna, they recently announced that last fall, they announced that they were merging HR and IT into one single function. Because the intersections between the two were just so many, it didn't make any sense for them to continue as silo department. So they took the IT department and had a report into the head of HR. Now the head of HR is not a technology leader. They are a people leader. And what one of the things that she understood though was that they needed a people view at the transformation that AI was creating. Yes. There's technology, but it needed to have that perspective of how is it going to impact people. Because when you're going through a transformation, there's a digital part, but it's the humans who are transforming the way work actually happens. And this is also happening in smaller companies. Workly, recently merged in a much smaller company. They took the seven IT people, put it under the chief people officer, and and then also shifted to remote work. And there's a lot of changes. And so the whole idea here is, again, to merge IT and HR so it's smoother, it's easier to bring on technologies to make sure they're adopted correctly. And, again, always taking that perks that people view of adopting this new technology that can be so transformative. So, again, that's a a quick view of how future of work is going to change. I wanna see if there are any questions here. And and, yes, Landon, you're right. I I switched it. It's it's actually the other way around on that last slide. It's actually 72,000,000 jobs lost, a 170,000,000 created for net 78. So thank you so much for catching that. I was reading that going, that's not correct. Okay. So resources were upskilling from Corel. I I'll I'll talk a little bit more about skilling and and training a little bit later in the implementation stage. Was AI you know, this is the question. Catherine asked, you know, was AI used at all the development or delivery of this presentation? This is something that I get in almost every single presentation. And, Catherine, I would love to hear a little bit more of what's behind that question because I suspect it's, that what's real, what isn't? How can we trust it? What is the use of AI now? When is it being used? Are we being transparent about this? And I think I should disclose at the beginning of my presentations from now on that I created every single one of these slides. I don't even have an outside production person. I do use AI to, to create some of the graphics, and I'll show them to you. I don't think I've used any of them yet. No. I haven't. But I'll show you when I say this a this graphic was created by AI. But that's about it. I may use AI for some of the background research to get into the nuances of how HR works. I use AI to do some of the background research to dig deeper into the case studies, Moderna and WorkLeap. But that's about it. But I'll I'll point out again where AI I use that. But here's the thing is we begin to understand why does it matter when AI is being used or not, and when do we need to disclose that? And I'll I'll talk a bit more about how important transparency is. There's a couple other cramps questions. When how will AI evolve to make different choices than the human user? Aaron, I I think that's a great question because I I I think, again, making decisions is what we think we do really well. And AI, I I'll I'll I don't talk into too much in detail here, but this interface between AI and human. As leaders, we need to understand when a job and a task is best done by human, best done by an AI, and best done by a collaboration of the two together. I imagine that at some point in the future when we interview people, we will be interviewing people alongside the agents that they use. It'll become an interesting question because if somebody develops an agent at work, are they able to take that agent with them? Or what happens if you leave and you leave your agent behind? You're leaving a part of you behind and those tremendous value being created by that agent. And how much of it is that person entitled to benefit from the value that they had, they created in making that agent possible? So lots of questions around this. Let's see. I will be sharing the the slides. Also, I have a link at the end. Let's see. Oh, there's a question here from Carol about how if people are willing to adapt to AI in different age brackets. I don't have the data in front of me. One of the things that I find consistently, again, there is a, IT and tech optimism and pessimism, but we find tech pessimists and optimists across every single age group. So you will find more of them in the younger groups because they just more adapted adapting to new technologies, and they they're using it more in their in their lives. But you also see tech optimists and AI optimists in in the older groups too as well. Alright. I'm gonna continue back into presenting here, and we'll have more time for slides for questions later on too as well. So let me go into HR's role in AI strategy. I do wanna say this. You probably have a lot of use cases. Many, many use cases. Lots of ways you could use AI. But I'll say it till I'm blue in the face, use cases are not a strategy. A strategy is an integrated set of choices that you make that decide where you're gonna play and how you're going to win. So it's about how do you get from where you are today to where you want to be in the future. So use cases are great. Make a long list of them, but do not mistake that for a strategy. So a strategy that I believe around AI is a focus on how AI supports your strategic goals. As an organization, what are your top three strategic goals? How can AI support them? So instead of thinking and asking, what does AI do? Ask instead, how can AI help us? How can that help us achieve our goals, overcome obstacles and barriers? And do that at the highest strategic level you can do in your organization. Do that for your department in HR. Do that for your particular function and team inside of HR. Constantly be looking at your top three goals and saying, how can AI support me meeting my goals? So let me give you three ways that I see AI transforming HR. And these are consistently three categories of efficiency, engagement, and reinvention. So, for example, we can see improving efficiency around using chatbots tied to acknowledge base that employees can go and ask about everything from how many vacation days do I have left to what's our PTO policies to how am I how do I use these benefits? What are my benefits? You can use it for some automating to screening of your resumes, again, with care and caution, like, with bias in mind. And then also taking those wonderful engagement surveys that you do and summarizing them or doing some analysis on them without having to tap into some data analysts that you have. You can just ask questions of that that database. We can increase engagement. I learning and development is such a crucial part of an employee's, engagement. We can now personalize them. I I didn't share it today because of time, but I have an avatar that I created that I can give a script to, and it can deliver audio and video, against that script and perform almost like me. And I can personalize that training for every single person in my course depending on their role, their industry, and and potentially their optimism and pessimism around AI, for example. It can out also function as mentors and coaching. I I have a little coach that I developed that I give transcripts to of my talks. I give it videos. I can analyze and give me coaching on ways I could hold conversation and and and do better. And then it all also can be adaptive to the way that we work. Each person works differently. We need to take breaks. When do we when does the AI sense that we're getting tired? We're not being productive and say, look, we're gonna I I suggest that you take some time here and and and take a break. Go walk around. Go get some water. So, again, different ways to engage. And then also driving reinvention. How do we we think the entire way that we do talent acquisition? The way I like to think about it, it's one thing to automate your process. But if your process isn't that good, if it's just okay, if it's mediocre, then we design that process in a way that you could never have imagined possible because it's possible now with AI. Reimagine the way you do performance management. We do it so solidly, sometimes yearly, sometimes semi annually, maybe if you're lucky quarterly. What if you could make a continuous performance management? How would you reimagine what that could look like because of AI? And how do you think about organizational design as something you do very rarely because it's difficult? But what if you could be completely agile around this? So you take these three buckets of ways that AI can transform HR, ways that these areas could support your top strategic goals, and you create a a portfolio of value of impact. So in q one, you may be more focused on efficiency areas because these are just low hanging fruit. Let's go get after them. But in q four, you may have shifted things. And so as you're pulling together this map of how you're going to map out the value you create, I think of it as putting together this walk of value. And each quarter, you're mapping out in q one, we're gonna deliver this value and impact, q two all the way up eighteen months. And the reason I say eighteen months is that you need a longer time frame to understand how transformation is going to unfold. And to have this plan, and this is your strategy that you can communicate to everybody in the organization, so everyone knows what is happening. And it's so important because if you are not active in in in promoting and understanding how that is going to change, then people are going to be uncertain. They're going to have doubt. What about this consideration? Have you taken that into account? Are we going to do this initiative? When is this going to happen? When is it going to impact my job? And you could start seeing that mapped out. Now the concern the question I get is, well, everything changes all the time with AI. How do you know what's gonna happen eighteen months from now? You don't. And so I like to say that this strategy is written down in pencil. Because at the end of every single quarter, you'll sit down and go, where are we now? We just sprinted to the end of this quarter. Where are we? Or how far are we along our plan? What new opportunities? What new barriers have come up? And then adjust the plan for the next five quarters and add another quarter. This is a rolling eighteen month plan over the next six quarters to lay out what you're going to do. And you can use AI to help you build this, but I think it's so important to be able to communicate this. And then, very importantly, you wanna communicate this well, and I'll talk a little bit more later on too as well. And I think one of the examples of this is the former CEO and chairman of LinkedIn, Jeff Weiner. And at the beginning of every single meeting, he would say, hi. I'm Jeff Weiner, CEO of LinkedIn, and our purpose and he would state the purpose here at Connect with World's Professionals at LinkedIn. And then he would go into a strategic point or a value, like members that was relevant to the meeting. And we begin every single meeting like this. And the, the the the somebody went up to him one day and said, you know, Jeff, this is getting kind of old. When are you gonna stop doing this? And he said, I'll stop doing it when people stop looking surprised. So this is the key thing about strategy and especially with AI strategy. We need to remind people this is the path that we are on, the journey we are on. This is where we want to be. This is how we're going to get there. These are the ways we're going to get there. These are the things we're going to do. And very importantly, these are the things we're not going to do. So make sure and especially because you are in this role of of HR to to make sure that everyone is able to answer these three questions on your team. Again, your immediate team in your department and ideally throughout the entire organization. Who is our future customer? Who is our future employee? Who do we want to serve? What are their needs? What is the future we want to create? What is that strategic goal that we want to have? What is our strategy to meet their needs? How are we going to get from here to there? And then very importantly, the question people should be able to answer is how am I personally contributing to that strategy success? If everyone can understand this, and this again comes to the role I think of HR to be a part of the discussion because AI is very much driven by people as well as technology, but also to be able to lead the conversations that can answer all of these three questions. And that, I believe, is a foundation for a great strategy. Alright. I'm gonna before I go on to the next phase, I'll see if there are any additional questions at this time. Alright. The systems so Haley has a question. Will you be sharing the system you use for virtual coaching feedback? I I use something very simple. I I get I I use something, within chat g p t called a my g p t. It's basically a custom g p t. So I I I give it instructions. I have and I'll show you in a little bit how to set up the prompt instructions. And then I give it some of my background. I give it my various, psychological profiles, my Enneagram, my MBTI, Myers Briggs. I give it my DISC profile. I I give it my objectives and and all the other things, and and I also ask it to follow various coaching protocols that I know about. And so and then it's I can ask good questions. It loads my objectives. I go in there and just talk to it every once in a while. I I, again, occasionally, will use coaches too as well, but I can talk to this coach anytime. So that's that's how I do it. If you want to be, what's the best learning we can okay. So Heather asked, if you wanna be extremely proactive in getting prepared to be at the forefront of leading, what are some of the best learning we can do now? I think to use AI, and I'll talk about it in the next phase. But use AI. Use it to do as many of the tasks you can do. You may end up not doing it for a lot of things, but I I guarantee you'll find some way of helping it achieve the most important things you want to do. So do it for yourself. What are the most important personal goals that you have? How can AI help you do that? And in particular, start doing this, what I call organic learning with each other. You will you all do functionally functional things. You have common strategic goals. So teach each other with bomb bag lunches, and and I'll go into that for it. But you have the agency to take on that learning yourself. Get curious. Read a lot. And you'll find incrementally, you'll begin to learn, get more confident at using AI and understanding what task it is good at and what things it's not really good at too. Alright. Are there programs that are a Gentic AI that are inexpensive and or free? Yes. I I don't have again, I don't know what they are for HR in particular, but there are many different programs out there right now. I would say, again, the, there are usually a lot of agents that are built into your work tools already. So within, the the systems that you use. So go and explore what already is in your systems that are allowing you to automate some of the things that you are doing. Can AI detect when an exception is needed? This is Carrie Hughes. This is what AI is really good at. And so you can train it what good looks look like, and and we call it the evaluator. It's evaluating the results coming out of the AI. So there's a big model that's doing work, and then you have another little AI that's sitting on the side evaluating it against a standard of quality and accuracy that you want. And so it can, like, identify when there's an exception and kick it over to a human. Like, this doesn't look right. Or the AI will even even itself, the model will say, I'm only 80% confident this is the right answer. I need it to be reviewed. Alright. So those are just, I think, of some of the ways that AI is really good at changing the way we think about work. So if you can rely on AI to do most of the handling and only send you the exceptions, that is a game changer in terms of you having to look at everything and, frankly, get fatigued at looking at everything and not even be able to see what are the exceptions that need to be handled. Alright. This is how you get set get ready to go. of all, make sure there is strong governance and and policy development. If you have an AI policy responsible and ethical use, fantastic. You are in the in the very small minority of companies that have one and are actively using it. I cannot stress how important this is, and working with your legal risk compliance team to get a policy in place is the best thing you could do. I like to say AI is like this Formula one car. It can go super fast, but you won't go fast unless you feel safe, unless you have good brakes. So good brakes allow you to go fast and your policies are your breaks. So one of the ways to be thinking about this oops. And here we go. This is this is my graphic here. So get your AI use policies and training the base of all training in place. The way I think about structuring this, and and I do have resource around resources around how to create a basic policy, is to think about it as an AI trust pyramid. So at the bottom, you have safety, security, and privacy. And especially for your security people around data, the use of data, access to that data, if somebody is is able to access data who can, especially very, very secure customer and employee data. So you wanna make sure those are compliant and in line with your existing data policies and use policies. Next level up is fairness. You want to be sure that the AI is being unbiased and is fair. And so every AI was created by a human. It's using data that was created by humans, so every AI has inherent bias in it. There is no such thing as an unbiased AI. And And so what you wanna do what you wanna do is understand what bias is in there so that you can accommodate for it, mitigate it, understand that these are the things. So the key thing to ensuring fairness is to test and understand what is fair. And here's the thing, there is no universal definition of fairness. Are you aiming to be equitable or you're trying to create equality? So what does fairness mean in the definition of your organization, in the definition of a particular solution or problem set that you're trying to look at? So being clear about what fairness means in the context of this particular task is extremely important. Similarly, quality and accuracy are highly dependent on context. If you're creating, some marketing materials for the organization, and and things, you you can be you may may be, opting on the way of of maximizing for speed. And so you can be the the definitions of quality and accuracy may be very different than if you're looking, for example, in a medical company and looking at a diagnosis for a a a, for a medical condition, you want to be highly accurate. The quality is completely different. So what does quality and accuracy mean for a particular task, for a particular job? Accountability is when you have you when something goes wrong, who's accountable for it? Who's responsible for it? And as AI takes on more and more of the work, when something goes wrong with AI, who do we hold accountable? Somebody needs to be managing that AI to be monitoring it, to be correcting it, giving it additional training, right, making sure that it's corrected and it's not doing the same things again. So who will be accountable for the AI as it is working? And then finally, transparency, I mentioned that before. When is AI being used? And, also, being able to look into it and see how it's making its decisions. When something goes wrong, how do you understand and have transparency into the process it used, the thinking process it used to come up with the answer. I again, I I use AI a lot. There are a lot of times I'm like, what did you do? How did you get that? Did you make that up? And it'll sheepishly admit, yeah, I did. So critical thinking becomes extremely important. I'll talk about that next because I do believe that critical thinking, this ability to, be actively thinking about what AI is doing well and it isn't, is a key part of culture. And culture is a key part of any strategy. Those are quote that's attributed to Peter Drucker, that culture eats strategy for breakfast, and I like to say it every single day because AI is changing constantly. You could have a a mediocre strategy and a great culture. It'll be fantastic. But if a great strategy but your culture isn't there to support it, it won't go anywhere. So there are five traits of AI ready culture. The one that that I think is so important is speed. This is, again, the ability to adopt, try things, look for momentum rather than being perfection, and and to trust the decisions that are being made very, very quickly is a very important trait of AI, cultures. Of the focus, making sure you focus on the most important things so you're not distracted. Experimentation, and this is where that critical thinking becomes so important. Asking why. Challenging assumptions, continuously improving. And, again, the critical thinking applied to the AI is also very important. Remaining customer centric, and you can also call think about this as employee centric, making sure that everything you do is in service of the people you are trying to serve and then constantly continuously learning. Again, these are the traits I think you we need to bring in as leaders to develop and foster in our cultures. So just to give you an example, one organization, about a mid size organization said, you know, we're gonna be AI ready. We're gonna be AI We're gonna give everyone training on how to use this. We have a a variety of tools available to you, and you can start using it. And what we're going to do is put up a dashboard and with everyone's name on it. And if you're using and actively using these tools, getting into them, you you get a green light, which is great. If you're figuring out training, you know, mucking around and I'm still not sure, that's also awesome. We'll give you a yellow light, but you're on the road to that discovery. And if you're not using it at all, then you're gonna be a red light. And the reason we want to know this is that if you're a red light, we wanna make sure that you're getting the support because this is so important. You need to get to at least yellow. And in six months' time, our goal is to have no more red lights in the company. You'll either be on your way, you'll be experimenting, or we will have had a conversation with you. It's like, is this the right place for you? And if this is not a place a a direction you wanna move in, completely understand, and we'll work with you to find a place where your talents will be will be able to shine. But this is not that place. But no more red lights. And and, again, this is a a culture shift and a change. And and I think organizations will need to grapple with how fast this change is going to happen, how that culture is going to change, and I don't guarantee you, culture is the way work gets done around here. Then the expression of that is the actual work and the processes and the the rituals and the stories and the symbols that you put into the value of that work, and all of that will change. So HR needs to be at the very middle of this, defining how culture is going to change, especially with the transformation from AI. So the next part is that a key part of that change in transformation is your leadership. And again, I believe leadership needs to be highly prepared for this. So train the top two levels of your executives. Make AI personal and strategic for them. So, again, this could be yourself, for example, starting with yourself. And identify how AI can support your top objectives. Create these custom GPTs. They're free and easy. Again, if I I'm I'm assuming you have access to ChargeGPT. You have some paid or enterprise version of it, but you can create very easily a custom GPT. I did this with some executives. I just took some materials from their companies. I took publicly available materials. I gave the AI the the custom GPT, the URL. I I gave them their LinkedIn profile for that executive, and it and then ask those executives to go do a key task in partnership with the AI. And so they can see how AI can help them get it done, and that little bit of customization made a huge difference. And and and also, I encourage people to write prompts really well. So this is an example. You're a communication specialist. You're drafting a script. So giving you some clear instructions, giving it some context, some additional information that I may be attaching to the request, asking it to make the tone, how the style wants to be, and I'm being very specific about what the output's going to be. So this is how you can create a prompt, and I'm not gonna go into it and say, you know, go and be explicit about how to do prompt engineering, but just a little bit of training and education around how to write a good prompt is super helpful in getting better results. But I'll tell you, the magic really happens when leaders and you start using AI as a thought partner rather than an answer machine. So I encourage you to add this little bit of text at the end of your pops. Before you start, ask me any clarifying questions you may have. And what happens is it 10 and instead of thinking about it's prompt engineering, you're thinking prompt questioning. It's a conversation now between you and the AI. And this conversation eventually evolves into, here is my strategic plan. Give me ideas of how it could be improved, or here is a communication. It's something I wanna create. Look at it from the different perspectives of personas on how they would perceive this. Give me feedback on it. So now you're using AI and the power of AI in ways that you never could have thought of before, and you're doing work in a different way. And that transformation of work is what you want to experience personally and what you want your leadership to go through and experience personally. Because here's the truism, you cannot transform your organization with AI until you have transformed the way you personally work with AI. So that transformation doesn't happen unless you personally experience it because you just can't see and imagine how work could possibly change unless work has changed for you directly. Alright. The the next section I wanna talk about is communicating. Again, this is the last thing you wanna do, is to have your AI strategist sit there on the shelf, unread, unloved by anybody. So, again, one of the things about AI strategy and communicating about it that's different is that there is this tremendous uncertainty and yet you need to be very transparent. So you want to separate what you know from what the forecast is. And so this is what we know today, and this is what we don't know. And we're forecasting. We have an idea where it's going to be, but we are not completely sure. The weather could change. And and especially when things can change, you wanna focus on principles and especially when it comes to the workforce changes. So, for example, a principle could be, we know jobs are going to change. We will tell you how work is going to change. You will be notified. It's not gonna be hitting you in the middle of the night. We're gonna be transparent about when AI is being used. We're going to work along the side by side. We will find opportunities to upskill you and if needed, to reskill you. You are important. It's so important. And and one organization said this, We're committing to not replacing people, to not firing people because of AI, but jobs will probably change. Your job will probably change. So being able to talk about that is very important. And describe what the learning process is gonna look like. One organization separated people and identified people who were were AI optimists and gave them a certain set of training, and then another group they knew were AI pessimists, and they gave them different training because just telling them, it's just be optimistic about AI is not going to work. So, again, having some of the people who are optimistic be mentors, to be champions, to hear concerns, but also to say, yeah, we get it. This is hard work. It's changing the way we do things, so we need to think about that. I wanna share two quick examples of of how AI was communicated. And there's a difference between internally and externally, and these came from the Shopify CEO. It was an internal memo that was starting to leak, and the very controversial part was this part. Before asking for my headcount, teams must demonstrate why they cannot get what they're doing done with using AI. So it's not saying we're not gonna have new headcount, but use AI So that was a big concern for people. But when they read about it, okay, that makes sense, but it's still concerning. And, Julien, though, CEO, also did something similar. We'll be rolling a few constraints, and one of them is that headcount will only be given if the team cannot automate more of the work, for example, that we're going to stop gradually using contracts to do work that AI can handle. So again, communicating things. In the case of Duolingo, it backfired on them in some to some degree. Again, they're they're b to b I'm sorry, b to c facing versus Shopify being b to b and some of the pushback came for, like, well, if you're going to fire people, you're gonna let AI take jobs and I don't want anything to do with Duolingo. Again, it goes to that fear and concern about what AI is doing to our our our communities, to our workplaces. And so the key point here I wanna make is that internal storytelling is very different than external storytelling, and you wanna make sure that the two are approached with in with a point in mind of what your audiences are looking for. So, internal storytelling, go beyond slides and the spreadsheets. Define the future with stories. Connect AI to the this the every concrete business problems we're trying to solve. Again, AI strategy should be supporting business goals. So explain, this isn't just gonna save time, but it's gonna save time. So it allows you to do more things with the more important things that you care about, having the conversations, being able to think strategically that allows us to do these things. And so put them into the story. So when you're thinking about communicating, this is bridging that divide from looking at the technology and the jargon to having a shared understanding, using strategy analysis, progressive disclosure, lots of visuals, taking a business approach and then translating these, these benefits, not just talking about AI does. So one of the last things I wanna talk about before we we close-up here is the the rhythm and the consistency of the communications, especially because it creates a sense of stability in a place where everything else seems to be blowing up. So weekly updates about what's happening, monthly reviews of what's happened in the past, quarterly big reviews and setbacks. Again, all of these sort of rhythms, a cadence of communications create some predictability in uncertain times. And this is this is just a framework of ways to talk about when you're communicating. This is what we've learned in the past period. This is the value. Keep talking about the value that we're creating or that we're targeting. What's changing? What hasn't changed? And what's coming up next? So if you can frame the the the the conversations consistently and from a temporal point of view, from a timing point of view, but also structurally, it just helps bring the sense of, the sense of predictability into a highly dynamic space. And speaking about the dynamic spaces, I wanna admit this is really super messy. It is confusing. It feels sometimes we're just spinning around in circles or going backwards and forwards and sideways. And then we're in this liminal space, leadership becomes even more important that we be that beacon of light for people when in the darkest moments of, like, why are we doing this again? And they can look to the leaders to look to people like you and say, oh, and get that reassurance, like, this is why we're doing this. These are our top goals. This is the strategy. This is where we're headed, and this is how we can do this together. And and and I think I I this is a very special time because instead of thinking you have to move through a through this messy period as quickly as possible, that's our instinct as humans, to get out of this messiness. Instead, invite and I invite you to stay in this messy middle because you're no longer anchored in the past. You haven't arrived at the future. In the world of possibility, in the world of imagination of what you could reinvent and and see the possibilities are immense. So take advantage of this time. Take advantage of the messiness because it's gonna take a lot of work to get out of it, but also to stay in it for as long as you can hold that space for yourself and for your people to work through this messiness. In the end, I do believe AI is going to make us better humans. I feel that, by better understanding each other, by understanding ourselves, we can bring out the more human aspects of how we engage with each other. And we're going to need it because as knowledge is commodified by AI, what is left is wisdom and judgment and understanding, collecting, and belonging that is all that is a very, very human thing, and only we as humans can do that. So by removing all that clutter allows us to be better humans too as well. So this is my contact information. I put up my contact information at every single presentation, and I encourage you to stay in touch. I would love to hear from you in whichever channel you feel comfortable. What are your takeaways? How what are you learning? And this is part of a benefit to you if you wanna take advantage of it. Share your takeaways because that actual sharing will help you remember this, cement it, and also integrate it into your work. You can scan this code for the slides too as well. And, again, I encourage you to stay in touch. Alright. Kate, I think we have a few more questions here. If you can help me filter through them, that'd be great. And I'm going through here. Let's see. Thank you so much, Charlene. We definitely have a lot. So thank you all. Please, submit any more that you have in the q and a, and we'll try to get to as many as possible. Charlene, I saw that Shannon had asked how can we be mindful of the environmental impact of using AI while using the tools in HR successfully? Yeah. Again, the the one of the things that I'm most excited about are what we call small learning models versus large learning models, and they can sit inside of our phones, for example, like, the conversation transcriptions. Don't need to actually go out and use a large link. A model can use a small model that's already inside your PCs and computers. So I think it's been using more efficient models for easier questions. So I, for example, will will will use a cheaper model, simpler model, or or use, again, easier tools with things that I think are really easy so the environmental impact isn't as high. I think we're in this impact right now where we think bigger is better, and that's not not always the case. So I think just being cautious about which models you use can pick and choose if you're in Chatt GPT or in Cloud or even in Gemini, which models you use depending on the task. And as you bring automation into the organization, there are little tools and agents that sit at the very front of the process that can decide, well, this is a pretty simple straightforward question. I'm gonna use a a a less environmentally impactful model to answer this question, the one that requires a lot of reasoning and and problem solving. I love that. Thank you. And that sounds like easy steps we all can take, for better results. I saw Lisa too had a quick question about industries that might not be so tech savvy. Do you have any advice for how to get folks and employees started kind of on an easier path to get into AI? And and I think, again, with with and the drivers, for example, I do believe that role specific training is really important. There's a base level training so that if any again, we're talking about mostly knowledge workers who have access to this, but we also see people in the field who are beginning to use AI to do their jobs. The it's really about being very specific about what that role needs to understand. If you're in a high-tech role, of course, you need more training. But if you're using it lightly and for general administrative things, then this is the level of training you need. It may be much more job specific about how you use AI. So this this, again, much more fine tune. And, again, this is where that centralized learning versus decentralized learning becomes really important. Not everything needs to be centralized. And, frankly, centralized isn't fast enough. So if you're a truck driver, for example, I know that one truck driver said, you know, I I see an automated driving coming. I'm gonna get certified for hazardous materials transportation. And then also taking on and understanding, again, as as AI is coming into to bear into different jobs, how you stay up to date on different regulations and training and and and use that training that's personalized to you and how to tap into that is very important. Great example. I love it. I think we have two more questions. One comes from Landon, who asks, in addition to building policies in place for AI, do you foresee a need for entire teams within HR devoted to AI ethics and outcomes? And if so, how would you recommend getting educated on the work of AI ethics? That's a great question. I think it's actually a function inside of the company at the highest levels of company. We talk about in our upcoming book the role of an ethics AI ethics officer in office. And the reason that's so important is I have never seen a technology that brings up so many ethical issues. And you want an office also that's identifiable that both people externally and internally can go in and say, I'm concerned that we're doing this. Why are we doing this? Just because you can, doesn't mean you should. And so this question of should we and and building ethical use of AI deeply into our processes is not something that you want to just hope happens. So having an AI ethics office that is actively proactively building it into the processes and workflows, but also can be a catch all for concerns that come up and address them at the highest levels reporting to the c suite and also the board. So this is an office that has tremendous power and responsibility, but I don't see it as only living in HR. I do believe seeing it operating at the enterprise at the various highest levels of the organization. Great question, Li. Thank you for asking that. Perfect. And then just, we have time for one more. I see the question, are there any other AI tools for coaching that you're seeing being used with positive reception? For example, BetterUp and LinkedIn Learning have AI role plays and chatbots now that we're looking at. Also, MS Copilot has a coaching bot answering bot. Any others you Again, I I there are lots of coaching apps, so to speak, AI agents that are out there that, can coach you. Again, I know coaches are rapidly developing their own AI bots to support their work. This is a fast changing field, and my recommendation is to start using them. Use the ones that are already in built into the places, like in BetterUp and LinkedIn, you mentioned them. Again, Copilot has these tools built into it too as well. I see it being built into sales, augmentation tools where it can help you with the processes, but also look at your calls and evaluate them and give you suggestions in real time. So the tools are multiplying like crazy. And in the same way that you can find a coach to help you with pretty much everything, you can now find these AI tools with with, that can do a lot of things. I I believe we're still very much in early stages. So if you find something, and this is the caveat, if you find something and you try it and it's not that good, don't give up hope. We are so early in this process. The AI tools, most of them don't have memory. They don't remember you like a good coach would from session to session. They are not necessarily trained on coaching protocols and best practices. They're trained maybe on knowledge, but not the process of how a coach would work with you and requires time as you would with a coach to train the coach how to understand you. So be patient with these tools. Develop them. Spend the time to fine tune them. I mean, I look up my coach and I had to teach it how to coach me. And and it's and it's an okay, adequate tool for now, but I'm looking forward to trying some of these other tools that can do a better job that help me with very specific things that I wanna work on. So, yeah, coaching is fascinating. Training is again, I I think one of the biggest opportunities to take training that you develop and just do a little bit of personalization from somebody just by having them answer three questions at the beginning of the training session. So that's where I think a a lot of the gains and interesting work is gonna happen with coaching and with training. Amazing stuff. Thank you so much, Charlene. I know I learned a lot. And judging by all the questions and comments in the chat and q and a, I know our audience did too. So thank you all for joining us today. Please scan the code on your, on your screen now to stay in touch with Charlene and download resources. Again, we will be sharing the on demand recording tomorrow. And if you have a few minutes, if you can fill out the survey that we just launched a minute ago right in the platform, we'd appreciate your feedback. So thank you again, everybody, for joining us today. Special thanks to our speaker, Charlene. I hope everyone has a run wonderful rest of the day. Take care, everyone. Thank you so much.