AI Agent & Copilot Podcast: AI Success in Leadership

Well, for about eight episodes now, we've talked about why AI success starts with leadership, not with licenses, not with tools, not with the number of people using coalpile, and most certainly, not by trying to figure out the answer to, which is better, chat GPT, or Claude. It starts with leadership. So as we close out this series, I want to leave you with one question. And it may be the question that tells you more about your AI progress than anything you can measure or show on your dashboards. Is your organization being led differently because AI is now available? Because although the technology may have changed, if your leadership hasn't, then we probably haven't transformed near as much as we think we have. Let's talk about it. Well, hello there, and welcome back to another episode of AI Agent and Co-Pilot podcast, brought to you by the fine folks at Dynamic Communities, for community by community. And I am your host of this episode, Sean Dorward, Chief Operating Officer at Adobe Consulting, 10-time Microsoft MVP, just been renewed and contributor and writer at lifehacks365.com. And this is episode nine, the final episode in the AI success starts with leadership series. And this episode, I'm calling the reset. You could call whatever you like. Stop asking if AI is working though, ask if leadership changed. I think that's a critical reset that needs to happen. Now, I'm going to spend some time this episode walking back through the first eight as a little bit of a recap bringing these points home for us, but you already know how to scroll backward in your podcast app. So I'm not going to do too much of that. What I want to do is bring the series down to one idea. And I think if you spend any bit of time trying to make your organization any better with AI, we keep asking whether employees are changing because of AI. So what are we doing with it? Are they using it? Are they experimenting? Are they saving time? Are they creating value? Those are all really fair questions. But maybe it's time to ask whether leadership has changed too. Because if we're just looking out to our front line to find if this has been a change, we're really missing the key mark here because leadership starts the AI success journey. And the leadership reality is that most organizations measure AI progress through activity. You know that. I know that many licenses were activated. How many? That's a win. How many people attended training? Okay. How often are employees using coal pilot? What are credits are we consuming for co-work? How many pilots are underway? How many agents have we built? How many hours have we saved? And those measures are useful. Absolutely. You should know whether people are engaging with the technology. Your IT team should be able to see that and measure that, but they can also create false sense of progress because they tell you that people are using AI, but they're not necessarily telling you that the organization is operating differently because of it. Key phrase is the operations of the organization any different because of AI. You can have employees using AI every day and still have the same meetings, the same reports, the same approval chains. Sound familiar? The same decisions getting pushed up three levels. The same spending hours, assembling information for leaders who will ask another version next week. Maybe AI helped summarize the meeting. Great. But you should, but should the meeting still happen? Maybe AI creates the report faster, useful, but does anybody act on the report? Maybe an agent routes in approval more efficiently, fantastic. But why are six people approving it? There's the uncomfortable part in this discussion is really breaking down the business process as a result of us incorporating AI. Sometimes we aren't transforming work. We're making old work faster and faster does not automatically mean better. Let's reset that. Sometimes we're not transforming. We think we are. We're making old work faster. Maybe a little easier and faster doesn't necessarily need mean better. A bad meeting with great AI summary is still a bad meeting. It just has better notes. We have to change the way that we lead in this era. Continuing on that thread of the shift in leadership, you go from asking the question, how much AI are we using and all the kind of ways that you can measure that to asking, what are we now able to do differently? That sounds like a small change, but it isn't. It's an operational operational differentiator because one question focuses on the activity and other focuses on how the business works. Take time savings, for example. We love to say as an outcome of AI adoption that we've saved, let's just say four hours. There's something used to take four hours and now it takes one. That's great. It's fantastic. That's the outcome of AI, sort of. But what happened with the other three hours? And I mean, seriously, what happened to them? Where did they go? Did the employees spend more time helping a customer? Is Sean just out taking a longer lunch? Did somebody analyze an issue more deeply and make a process improvement? Did we learn anything? Or did leadership just give them three more hours of work? Because that's likely what's happening. And employees will notice that. And if the reward for becoming more efficient is simply receiving more work, they may become very quiet about how much time AI is saving them. I mean, wouldn't you? Wouldn't you? So leadership has to decide what recovered capacity is even for. Maybe it supports growth. Maybe it improves quality. Quality. Maybe it's to reduce burnout. Remember a very important factor here is that a lot of times people are already overworked and saving time is really just giving them the time that they deserve back. And maybe it gives people time to address problems that never made it to the top of the list. And continuing on the thread of a leadership shift, we have to change from asking the questions like how much AI we're using. And we're going to switch over to how are we now able to do things differently? That sounds like a small change. It isn't. It's an operational differentiator because one question focuses on the activity and the other focuses on how the business works. Take time savings for example. We love to say that a task is save time. Let's say it used to take four hours and now it takes one. Perfect. Outcome of AI and action. But what happened to the other three hours? That's where your value really is driving. Seriously, like where did it go? Did the employees spend more time helping your customer? Did John take a longer lunch? Did they analyze the issue that was in front of them more deeply or improve a process or learn something or did it just give them three more hours of work from leadership? Because if we're just giving them more work, employees will notice that. If the reward for becoming more efficient is simply receiving more work, what would you do? They may become very quiet about how much time AI is saving for them or less creative in how that we handle it. So if we don't lead from the top in this way to help people see the value and how to apply it and create that clarity for what to do with the newly found time, it's going to fall backwards on you. And maybe that time is supporting growth or improving quality or maybe it's just reducing burnout because maybe a lot of your team is already overextended and AI is just getting them back to a manageable work life. Don't overlook that. Leadership, success is important here. So we've got the shift. Now here's the move. At your next leadership meeting, don't start with the dashboard. Start with the question, what have you personally changed because AI is now available? Like two-year leaders. Not where your team is changed, not what IT is deployed, not what the innovation group is in the middle of testing or what did you change that affects your customers? What did you change as a leader? Did you redesign a meeting, restructure meetings? Did you stop asking for a port report because you can get it some other way? Have you delegated decisions or increased decision making ability or reduced decision making time or increased decision accuracy? A lot of good metrics there. Have you changed an approval? Do we communicate differently? I think this is going to change the way that we think as leaders because if we can identify the way that we're running the business differently with AI, we're not really fully experiencing the benefit internally. Have you raised the expectations for the quality of analysis? I know I have. Or maybe even ask yourself, what did you change? Directed internally and shared with your team what you've changed. So ask them the question and then pause and let them think. Well because the first answer might be I use co-pilot to write emails. Okay, you're going to hear some things about I use co-pilot to help me on sales deals or something like that or how to respond to this email. But keep going. Don't stall out there. What changed about how you lead? The question will tell you whether the transformation is actually being reached. And if a leader can't identify anything, then that isn't a reason to embarrass them. It's a signal. Remember, we're looking for sentiment here and that's a signal. It may mean AI has reached the employee experience but not the leadership model. Ding, ding, ding. Almost every organization struggles there. Then ask one more question. What part of our business still operates as though AI did not exist? Probably all of them. Maybe it's reporting or forecasting or customer service or project delivery. Maybe it's how knowledge moves through the company. Pick one. Not 27, just one. Find a process that was designed around an old limitation. Maybe information used to be harder to gather. Maybe expertise was difficult to distribute in the organization. Maybe every transaction had to be reviewed because the organization couldn't identify the exceptions. If the limitation changed, the process should at least be reconsidered. Don't automate it first, question it first, because AI can make a bad process move faster. And then everybody celebrates the efficiency while the process is still bad. Here's a real world example. Think about customer service. An employee can now use AI to review the customer's history, summarize prior conversations, let's see, identify open issues and recommend next steps in that journey. That's powerful. But then the employee says, I need to transfer you to someone who is authorized to do that. That person needs a manager. The manager needs a finance. And now we are very well informed employee who still can't help the customer. Did AI fail? No, I don't think so. The technology did its part. The authority didn't change though. The operating model didn't change. Leadership didn't change. And that is the point. AI transformation cannot be something leaders ask employees to do while leadership still remains untouched. You need to reset. So here are some quick things that you can do as leaders. First, identify one leadership behavior AI should change. Not an employee task, a leadership behavior. Second, identify one process that still assumes information is scarce, slow, or difficult to interpret. That's where approvals generally come in. Then ask whether that assumption is still true with the insertion of AI. And third, add one outcome measure besides your adoption measure. Don't stop measuring usage, but say that. But also measure whether a decision happens faster. Whether customer got a better answer or whether report disappeared. Whether an issue was identified earlier, which that's an awesome outcome. Or also whether employees spend more time using judgment and less time assembling information. Remember that in the promise of AI, the mantra was, "We'll just be a better version of ourselves. Let your employees do bigger and more impactful things." That line there, whether employees spend more time using judgment and less time assembling information is an example of just that. Usage tells you somebody touched the tool outcomes, tell you whether the organization became better. So here's my take. I think we spend too much time treating AI as something employees need to prove to the organization. Are they using it enough? Are they finding use cases? Are they saving enough time? Meanwhile, some of the biggest opportunities are sitting inside leadership habits nobody wants to question. The report we still request that's taking resources in time. The approval we refuse to delegate because we're holding on to the authority because we think that team members can't make that decision. The meeting we continue to schedule because we can't do it without it. The decisions that keep getting delayed. And then let's go on and on. The process we defend because it has existed for 10 years. Leaders do that too. I know we chuckle about it, but leaders do it too. Most organizations don't have an AI problem. Even though it's so young, it's not really an AI problem. They have a leadership model that hasn't caught up with how AI now makes things possible. And that doesn't mean that they have bad leaders in their organization or they're not forward-thinking leaders. It means the world changed faster than the operating model did. And that's okay, but it's important we have to acknowledge it, the reset. AI makes that gap easier to see. When information moves faster, slow decisions become obvious. If we can get all this to this point in two hours and then it sits on a decision path for three days, that becomes obvious. When analysis becomes easier or endless requests for more analysis begin to look like avoidance, which is another side effect of AI. When employees have better insight, unnecessary control becomes harder to justify. Think about that. I mean, it's just so obvious to me, but it's hard to see past the habits of the past sometimes. AI doesn't make leadership less important. It makes it more important. It makes passive leadership less sustainable. That's for sure. To close out this AI success starts with leadership series. Here's the question I wanted you to take away. What is different about the way your organization is led because AI is now available? Remember that at the top of the episode. What decision change, what expectation change, what meeting changed, what process changed, etc. etc. The honest answer is most likely not much yet. And that's okay. It doesn't mean the AI initiative has failed. It means you found the next phase of the work. That's why we're having this conversation. Because the most meaningful evidence of AI transformation is not that employees are using the technology, it is that the organization is truly being led differently because of what the technology now makes possible. That's the reset. My name is Sean Dohrward. Thank you for joining me for this episode of AI success starts with leadership and the final episode in the series. You can find more practical ideas and perspectives at Lifehack365. Feel free to reach out to me. And don't forget to subscribe to this channel to catch up on the previous episodes. And look out for future episodes. We're going to dive into co-work in a couple other cool series. Thank you for joining me. And until next time, take care.