The Inner Game of Change
Welcome to The Inner Game of Change podcast, where we dive deep into the complexities of managing organisational change. Tailored for leaders, change practitioners, and anyone driving transformation, our episodes explore key topics like leadership, communication, change capability, and process design. Expert guests share practical strategies and insights to help you navigate and lead successful change initiatives. Listen in to learn fresh ideas and perspectives from a variety of industries, and gain the tools and knowledge you need to lead transformation with confidence. Explore our episodes at www.theinnergameofchange.com.au, Spotify, Apple Podcasts, Youtube or anywhere you listen to your podcasts.
The Inner Game of Change
E95 - The Promise of Change vs the Realisation Gap - Podcast with Lindsay Phillips
Welcome to The Inner Game of Change, where we explore the invisible forces that shape the way we lead, live, and learn, because real change, as you and I know, always starts on the inside.
Today, I am joined by Lindsay Phillips. Lindsay is the founder of SkyPhi Studios, a Forbes contributor, and a seasoned change leader who has helped organisations realise the true value of their digital investments. Her work spans leadership coaching, culture change, and program management—always with a focus on people and collaboration, not just the technology itself.
In this conversation, we dive into the gap between the promises leaders make and the value organisations actually see. We explore why adoption is not the same as optimisation, how fatigue often cuts short measurement, and what leaders can do to create sustained engagement. And we also explore generative AI—why it feels like learning a musical instrument, starting with noise and, with practice, becoming music.
If you care about making change stick, about the human side of value realisation, and about how AI is reshaping the adoption landscape, this is an episode for you.
I am grateful to have Lindsay chatting with me today.
Note: Stay tuned after the conversation for a special ChatGPT reflection and review of this episode
About
Lindsay is an organizational change expert that helps organizations realize the full value of their digital investments. She specializes in guiding organizations through change, fostering collaboration, and enhancing engagement. Her expertise in leadership coaching, program management, and culture change initiatives helps organizations not just adopt new tools, but embrace a holistic approach to transformation. She has founded two consulting firms, SkyPhiStudios and Studio Change.
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We even like to talk about the difference between adoption and then true like optimization because you can adopt something by kind of doing the bare minimum and meeting all the metrics and the goals. But if you aren't really like totally embracing it, then the the company and the team won't actually get as much value out of it. So I think there's even a step beyond, which is three to six months after Go Live. How much has your teams committed to it and continue to grow and deepen their usage of whatever it is that you're putting in place?
SPEAKER_02:Welcome to the Inner Game of Change, where we explore the invisible forces that shape the way we lead, live, and learn. Because real change, as you and I know, always starts on the inside. I am Ali Jamar. Today I'm joined by Lindsay Phillips. Lindsay is the founder of SkyFi Studios, a Forbes contributor and a seasoned change leader who has helped organizations realize the true value of their digital investments. Her work spans leadership coaching, culture change, and program management, always with a focus on people and collaboration, not just the technology itself. In this conversation, we tackle the gap between the promises leaders make and the value organizations actually see. We explore why adoption is not the same as optimization, how fatigue often cuts short measurement, and what leaders can do to create sustained engagement. And we also explore generative AI, why it feels like learning a musical instrument, starting with noise and with practice becoming music. If you care about making change stick, about the human side of value realization, and about how AI is reshaping the adoption landscape, this episode is for you. I am grateful to have Lindsay chatting with me today. Well, Lindsay, thank you so much for joining me in the Inner Game of Change podcast. I am eternally grateful for your time today.
SPEAKER_01:Thank you for having me. I'm really glad to be here.
SPEAKER_02:Thank you so much. Lindsay, today we're going to talk about a different angle of looking at uh value realization of any transformation, any change. And I think that will be a wonderful conversation. But before we start, it would be fantastic to just give my audience a bit of an overview about who you are and what you do.
SPEAKER_01:My name is Lindsay Phillips. I work in the organizational change space and help companies realize the value of the digital investments they've made. And so that really means helping them understand what it's going to take to implement it, both from a people perspective and a technology perspective, and then putting plans in place so that their organizations are ready to really step into this sort of new future that they're investing in. My background is really kind of in the IT space, but I was never really an IT person. I was always more the people person on the team.
SPEAKER_02:I think we all have touched somewhere somehow in our career with IT. It's unavoidable anyway. When we talk about investment, digital investment, can you clarify what that term means?
SPEAKER_01:Yeah, like very often companies will decide that they need to upgrade a system, whether that's HR or accounting or some business system. And they generally will maybe hire a partner to help with the technology implementation and the integrations, but helping them actually figure out how do your processes need to change and what are the upstream and downstream impacts of that? How do those folks need to maybe even redefine the work that they're doing or the value that they're bringing to their job in order for this new solution to be successful? Because without those conversations, very often people will just take the old process and dump it into the new system. And it's the same, it's the same world. The system hasn't actually changed because you're following the same processes.
SPEAKER_02:Yes. Is value here the same as return on investment?
SPEAKER_01:I think it's yes, because of course ROI is like a hard number, right? Like where you can tie to, hey, this is how many people, like these how many hours we've saved, or how many an increase in sales that we've gotten as a result of this tool. I think business value is a little less hard numbers and more just the general almost sense that the organization has that the system was valuable.
SPEAKER_02:Yes. So value goes beyond the numbers into perhaps employee experience, uh, customer experience, uh, engagement, all of these things. Is that what we're talking about?
SPEAKER_01:Yeah, and and making sure that everyone understands why you're using the system, when they should use it, and that they have a sense that working together in this tool is for the best for the whole company. And so, yeah, that that especially in the IT space, there are many things where it can streamline the employee experience and and it can shorten duration of delivery of service. But it's not necessarily saving time and money, but it is getting folks what they need faster so that then they can go on and do their jobs more quickly. So ROI can be hard because generally all people want to look at is well, how many jobs did we cut as a result of this tool? And sometimes it's not about that. It's about leveling up, it's about growing and maturity, it's about improving just like quieting the chaos and making sure everyone's on the same page about what's going on. And that's valuable, but it's not there's no dollars necessarily that you can easily map back to that.
SPEAKER_02:In my experience, Lindsay, the the organizations always start with their promise or value promise, that by implementing this, we will get this. How linear is that usually? Um they start with a promise. Do they really end up with a promise?
SPEAKER_01:Well, I think it's often a mystery because a lot of times they do set some goals and they never bother to go back and measure them to actually reach them. I think the other thing is a lot of times companies will set goals that they literally can't measure. And so it's a number that they've kind of made up and the the work that you would have to do to try to like make sure that that actually happens, like no one's actually going to do that. So that's one thing I really focus on at the companies I work with is we need we need to understand our success criteria. Like, how will we know that we have landed this? And if the dollar amount that you're reaching for, there's no way to measure that, then that's not a success criteria. That's something that we can aim for and kind of discuss. But we still should have concrete goals for the organization.
SPEAKER_02:Why is it difficult to actually measure that after a change is implemented? What what are some of the variables in there that play a role in sort of derailing that promise later?
SPEAKER_01:That's such a good question. I think, I mean, the main thing that gets in the way is everyone's just tired of it, right? Like by the time you slog through the project and get it in, and then they get through hypercare, like people are just ready to move on. And and often they're working on day two enhancements. And so there's often very little appetite to go back and prove what you did. And that's why I say like a lot of times the value is just a gut feel. And if you if everyone thinks it went well, a lot of times companies are happy to just move forward with that. And so they never do go back and actually ascertain that they reach the goals they set.
SPEAKER_02:Yeah, sometimes I uh I have actually uh been curious about this. I I followed quite a few business cases, uh, and I've actually seen how people put a business case, and some people are not even experts in that. And uh and so they plug a number in there, and then it gets a business case gets signed off for implementation, and then you arrive at some stage fatigue will settle in in there, and because a time a project has got a constraint of time, budget, and scope, so at some stage when they want to hand it over, the real value should start being realized after the handover, not during the project. But then you're asking the receiving managers to do something way beyond their daily jobs. And that's I think one of the barriers of actually looking at realizing the benefits. I've also seen a different way of doing it, that some organizations realize the benefit first, then they implement the change.
SPEAKER_01:Meaning they they map out, they actually have a clear understanding of what's going to happen and then they put it in place?
SPEAKER_02:Or they think that this is going to save them five FT headcounts, so they take that FTE headcount out and then they implement the change.
SPEAKER_01:Really? Oh my goodness, I've never seen that.
SPEAKER_02:Well they're both the idea why they do it this way is that it will force the receiving groups to focus on the value of the change. And therefore, if you're a manager going down with the number of uh headcount, then it is in your best interest to actually pay attention to what that change looks like.
SPEAKER_01:Yeah. Well, and if you're on the team implementing the solution and you know that you will have fewer headcount in the future, you're probably gonna do a very good job during design to make sure it works.
SPEAKER_02:Absolutely. So just another way to engage the leaders through it. Um and yes, it it may require a level of courage. I've also seen it in retail. I've worked with a number of big retailers in here. Um they call it bank the benefit first and then roll out then, and obviously, as a as a person myself interested in observing change adoption, I have seen the shift. And then later it became, it was kind of funny in many situations, it becomes a negotiation strategy. So if I come to Lindsay and say, we need to let go of three headcounts before I implement the change, we know the change is gonna deliver you that value and perhaps better customer experience. And so then Lindsay will be saying, that's actually not three, can I just give you two? Even the two, that's realization up front. And uh and then you go through it that way. Just another philosophy, another way around, value realization, because we usually wait till the end and somehow, somehow some of them realize the benefits, some of them don't. Uh, and it all sort of dies off.
SPEAKER_01:Can I ask, how does that impact the teams that are doing the work on the project?
SPEAKER_02:Tremendously, tremendously.
SPEAKER_01:Yeah, it impacts also the very demoralizing.
SPEAKER_02:Well, it it also impacts the teams who are going to lose a couple of headcounts. Some of them didn't do it really upfront very quickly. They let the natural attrition happen, uh, especially in a retail environment where you people come and go very quickly. So it just there are different ways. But that's what I thought I said uh earlier. It usually, you know, uh a type of negotiation starts happening around what that looks like, the time frame, and it's actually good. You know, uh it impacts their project managers and the project team because they realize that they're gonna have to do a stellar of a job to enable that team. So, and then it pay it helps the receiving team pays attention to actually I really want to learn this because I don't want to do more work uh because my teammate is already left. Uh so that it's in my best interest to be curious about it. Again, you know, philosophically, some people may not agree with it, but uh I I've seen it and it was fine. I mean, there's always gonna be a level of resistance regardless. But I have seen the shift from the receiving managers that they pay attention to how the change, as you mentioned, has been designed and they question the numbers. Whereas if you actually don't just come and implement it, you say, Yeah, that's fine. Come and do what you need to do and go w without a lot of uh you know of of engagement uh in the in the project. So that's what I've seen in those.
SPEAKER_01:Yeah, that's fascinating. Because you might not get their buy-in, but you'll get their engagement, that's for sure.
SPEAKER_02:You will get the engagement. Yeah, and uh many in many occasions they actually, when those conversations happen with the bosses, they will come to me and say, Ali, can you sit me down and actually walk me through this? So they start paying attention and we'll be saying, Yep, that's fine. We will enable you. You just need to be there, show up, and be interested in this. And then they pay attention to also the return on investment. And also they will ask their teams to be engaged in the learning and the adoption, and uh so it's just another way of of managing value realization. When we talk about a change happening to a team, in my eyes, there are different ways of how a team looks at a change. Some teams uh what I call tolerate it and some teams accept it, and some teams adopt it. Have you noticed that?
SPEAKER_01:Yeah, absolutely. And I we even like to talk about the difference between adoption and then true like optimization, because you can adopt something by kind of doing the bare minimum and meeting all the metrics and the goals. But if you aren't really like totally embracing it, then the company and the team won't actually get as much value out of it. So I think there's even a step beyond, which is three to six months after go live. How much has your teams committed to it and continued to grow and deepen their usage of whatever it is that you're putting in place?
SPEAKER_02:Well, that's an interesting thing, um, because I always see those post-implementation or post-go live. Most people will give it what is it, uh few weeks. And then they hand over and then they pray that adoption will happen. And you were right, these these are there's a usage of the system, there's the adoption of it, there's embracing it, and there are people that will take it even further. Uh, and there depends on how you want to manage it. But there's always the complexities like how long posts they go alive would need would you need to camp with the team to enable them. Because it's a reasonable question from leadership to actually start talking about cost. A project team is not cheap.
SPEAKER_01:Yeah, well, and I think it does make sense for a lot of the technical resources at some point to kind of roll off because the team should be self-sufficient and should be able to handle defects and enhancements. In terms of having someone on the team who can just almost be the emotional barometer for the organization and hear what people are saying and know how to respond to that to get them to really buy in and engage. I do think that lasts a while. And if you do it the right way, it should take several months. But it does not have to be, and in fact, it is not a full-time role. Um, and so that's one thing you know, I've kind of been working with for the last several years is how do we make experts available without requiring this 40 hour a week commitment from the clients? Because that's where they get, you know, very concerned about cost versus like, no, I can get you, you know, top talent, but then that person's working on multiple engagements so that they don't have to be like on site all day, every day.
SPEAKER_02:Yeah, go deeper into that. I like that idea. Can you go deeper into it?
SPEAKER_01:Yeah. I mean, one thing, you know, my my sort of last um company, we were working on recruiting former big four talent who were burnt out and people who want to be home with their kids or they wanted to do work that was really fulfilling to them. And so we were working to find contracts for them that were part-time. Like it's like there's some change. If you're really not SAP, yeah, that's a 30-person team. A lot of changes don't need a lot of people, it just needs someone with expertise who can be tuned in and can do the work. And so um, we were finding a lot of um, you know, it's very cost effective for clients to say, yeah, you can get a big four talent, you're not paying big four rates, and that person is not full-time. And so clients are much more able to find that in the budget, uh, if that's the proposal.
SPEAKER_02:Yeah, so that person is uh sometimes I call them learning facilitators or adoption facilitators. Uh, they don't need to be attached to a particular, they become coaches almost. But they require a special talent. These people would need to have a high level of change IQ. They need to look for, they need to understand the business case, they need to be heavily engaged with the team, meaning their uh emotional intelligence will be really so they would need to be in a position also to talk to leadership and all and also the ability to communicate and connect with the users. And in my head, this is not an easy job. You need to be very qualified to be able, you need to be a trusted advisor for the leadership. You need to be building a stronger relationship with the lead with the management and the users as well. Is that your experience?
SPEAKER_01:Yeah, I would also add that you want that person to have a certain amount of functional like business acumen.
SPEAKER_02:Yes.
SPEAKER_01:So that when issues do come up, they a lot of times with clients, if if it's the first time they've ever done a change, any issue is really destabilizing and they get very sort of flustered. And it helps having someone say, This is expected. I know what this person is kind of reporting as an issue. It's not a huge issue. So having someone in the room who's seen it and also can kind of help gauge how big of a crisis this is can help just the whole team move through more smoothly.
SPEAKER_02:I love it. Let's shift gear and we'll talk about the uh exciting world of AI where you and I live. And I'm so glad that I'm actually living in this age where I've seen this technology. What's your experience so far with especially generative AI?
SPEAKER_01:You know, I was originally very resistant. Like I'm a change manager, so I don't like change. Like we all get into it. And then about, you know, nine or 12 months ago, I said, look, this is not going away. This is going to revolutionize the world, and I can be a resistor if I want, or I can have a seat at the table about how this is going to be used and I can embrace it. And so I really dove in, I've made it sort of one of my goals to be, I don't know that I'm an expert, but it's I want co-pilot, I want copilot or chat GPT or whatever tool it is to be very intuitive. I want to just know how to use it and how it can boost my own effectiveness and also how to help other people use it and adopt it. So that's kind of how I started. And now, yeah, in helping companies figure out it's not just about rolling out a tool and making it available to people. They will not know what to do with it. They won't know how to change their day-to-day life. And so, what's that sort of learning journey and experience journey we need to make for people to totally change how they approach work?
SPEAKER_02:What is the sentiment currently in your in America or American workplace around generative AI?
SPEAKER_01:Leadership's always very excited about it, obviously, because we're kind of riding that hype curve. I think people on the ground, um, we, you know, I call it like AI FOMO. There is a certain amount of FOMO of I want to be involved, I want training because I know it's gonna be really important to my career. What's interesting is consistently, and I'm doing a bunch of data gathering and research with the current client I'm working with. Folks are saying, I don't know how to do that because I haven't been given training. And that I think is gonna be the biggest thing that holds people back, where it's like, there is training you could go out and get, but really the best way to learn it is to use it. Like you just have to use it. And so helping people get out of that reception, like I'm just waiting to receive training. It's like, no, no, no, no, no. You are your you're your own teacher, co-pilot or ChatGPT is your teacher. Like get in there and use it.
SPEAKER_02:And that's gonna be a paradigm shift in the mindset that I am waiting for my employer to do something around it. Right. Whereas these tools, you and I know, they are built for self-directed learning. But I still believe that the organization would need to do its due diligence around enabling people, helping them understand how that's going to impact their workflows, uh their roles. And we just talked about the value realization. In fact, with generative AI is actually f you can you can look at the value realization way faster because, for example, in Copilot, in Microsoft 365's Copilot, if you use the feature to just use the existing feature of recapping a meeting, we know you know through million of users that's gonna save you about 20 minutes each time you just do this exercise. So if you multiply that by number of meetings and and especially if your job is an admin that's been just taking notes in meetings, so we know the value realization would need to be uh good. And therefore it's imperative on the organization to show me how using the technology is going to help me. But I always think, Lindsay, the leadership will have another problem. So they're looking now at the usage, but I'm saying to them, your problem is not now. Your problem is in 12 months' time when all of this technology is embedded, and then your problem is that the promise of the technology is that this is going to take away all the repetitive work and all of that, and therefore it leaves you with time to do some meaningful work. Now, when you ask a leader what is a meaningful work, they go quiet. That is hard to actually come up with.
SPEAKER_01:Yeah. Yeah, it's you know, the way I've been talking about it recently is okay, using the tool is gonna boost your individual productivity if you can figure out how to be self, if you're self-sufficient and can figure out how to learn it. In order for companies to move on to organizational productivity where you're actually interacting with other people, yeah, you're gonna have to tell people how are we using it? What's our philosophy? How are we rolling this out and what are our expectations? And then once it's self-sufficient and self-learning, that's when it's sort of like that ecosystem uh productivity. Um but yeah, there's I think it'll be really interesting to see what happens because there was just that MIT research that 95% of AI pilots in the last year have failed. They did not realize their sort of goals. And I think it's because companies plugged and played and just bought it, turned it on, thought it would work. And it just doesn't work that way. It never it they're sell, they're selling you a product, and the product needs some additional effort.
SPEAKER_02:Yeah, unfortunately, uh I um we had an example here in Australia where they designed a change, AI-driven change, uh, to replace some call centre stuff, and it went really bad. Um they wanted to do the upfront realization. They want to get rid of about 40 stuff in here. And I've written an article about it. I was brave enough to write an article about a change that I haven't been part of, but I can see all the symptoms. And so within a couple of days, not only the volume of calls dec increased, the you know, people start complaining, so they reversed everything, which is even worse. They they took away the AI-driven solution, they give people back their jobs, and it was a major story in the media here. And then immediately what those guys have done now, they created a bad precedent about AI. And in my eyes, that's an isolated story that is got all the landmarks of we haven't thought through the impacts properly, we haven't looked at the design, we haven't allowed for some time for this to embed and really understand it. I don't know what sort of pilot they have run. And and I'm not talking from theory. Uh currently I'm leading personally, I'm leading an AI learning experience. And I'm each staff member that I'm dealing with now, they go through three 90-minute session series and where we introduce slowly into the foundational, into the deep use cases, into what an agent will do and how you create an agent. But even with that, that just touching the surface, you actually still, even with my uh extended experience, I still believe that it's gonna have to be ongoing, as you mentioned, you know, the person we talked about is gonna have to be a coach on the side to continue embedding it. And it's not because it's not a feature. This is a whole capability that is actually coming through. Uh so when I read about the MIT and other uh departments, and especially especially if it's a government department, I always question show me where you've done the change management properly. Show me where you've showed the best change empathy with your people, show me your training program, and show me how long you've given your people and the support. Then I'll be convinced. Apart from that, I'm not going to be convinced if you just going to be is what I call a stopwatch event. I've given you this and therefore I expect something in return.
SPEAKER_01:Yeah, well, especially because companies are incentivized by their boards to always do the razzle dazzle and say everything's fine. So I was at an event last year and I was up on stage with a with, you know, a CIO, and on stage they were saying everything's great, we're having great success. And then behind the scenes, he's like, I could, I could never say this, but like not like the only people using it are execs. And I was like, typical, like typical. So it's to me, the the analogy I've been using, I'm I'm curious if this resonates with you, is learning AI is more like learning a musical instrument than anything. Like you need to learn music theory first. Like you have to understand how prompt engineering works, you have to understand how MLMs work and and uh and then you have to start to learn the tools, but you have to practice. Like you can go to training, but that's just like a music lesson, and then you still have to go home and do your scales and do your chords and like practice this brand new skill that no, it's not intuitive. Like you have to just go learn it.
SPEAKER_02:I love this, uh Lindsay. We need to go from noise to music.
SPEAKER_01:Oh are we gonna are we about to write an article together?
SPEAKER_02:It's because when you start learning a new musical instrument, all you're doing at the start is noise. And over time it starts to talk to you and you start to make a tune and uh and uh a sound. So noise sound and then usually later becomes the music. And you you touched on a very important point. There's a difference, and I've been an advocate of this currently. There's a difference between a prompt engineering and context engineering. And context engineering is where you build and you feed and you uh uh educate your uh AI capability with who you are, what you work on, your history. So for example, I've been working with co-pilot for uh since it was started, December 2023. So it's got it's got a over a year and a half worth of context about me. And therefore, when I collaborate with it now, it knows me inside out. In fact, it reminds me, remember three months ago you worked on that? This one is actually similar to that. Once you this is the music. But if you touch it every day with one prompt here and there, and then you give up, that's called noise. So to use your analogy.
SPEAKER_01:Yeah. Yeah, and it is watching people learn how to use the tool. It really is like watching somebody learn how to use a musical instrument. Because I I was in a training session this week, and somebody was really proud of himself because he had figured out how to get a summary of his emails from the day before in co in Microsoft Copilot. And I was like, Well, but do you want that? I was like, Don't you already know what email? Like, what are you gonna do with that?
SPEAKER_02:Yes.
SPEAKER_01:He's like, Well, now I can look at it and I can see what emails I got. I'm like, you can. Look at your inbox and see what anything else you've got. Like, what's the next step? And so he hadn't yet gotten to the point of, well, let's say this did just save you time. What next? What so what? Yeah. Um, so I think the so what is what's the biggest sort of learning people need to make is it's not just a UI you click around. It's like, what are you actually doing with it?
SPEAKER_02:Go go deeper into the so what, because that's really an important point.
SPEAKER_01:Yeah. So you can automate any, there's all kinds of automation or tasks or research you could be doing, but if there's no reason or it doesn't progress your sort of journey or make your job easier in some way, it's it might be fun and it might be interesting, but there's not really that like grounded reason and value that it's bringing. And so the example I like to use is now I built this because I was learning how to use ChatGPT, but I have a ChatGPT in my own personal project. I really wanted like something that would help me plan my meals and cook. And so I have a little project and I said, talk to me like Julia Child. And so I just have this project that talks to me in Julia Child's written, you know, not out loud, but like written voice. It's so fun and I love it. There's no value, like it makes my life easier, but it's not like it's like making me money. And so we can get a lot of dopamine from this stuff without actually like progressing our professional like careers and lives.
SPEAKER_02:Yes. And that that is when it goes from play to capability building. And uh you remind me of a framework in communication where it says what so what now what. And you you're absolutely right. You when a user just summarizes an email and so what, like, what are you going to do with this information? If you're gonna summarize a file, what are you gonna do with this information? It's almost like state your objective first. What are you trying to achieve, then utilize the technology to actually help you with that. That's probably a better way than saying, give me all of my schedule for today. You can already look at that. The fact that it summarizes that is just cute, but that's not really the point, is it?
SPEAKER_01:Yeah. The other thing we're seeing with this particular client, um, it's actually wasting time in some in some cases because now business users can go generate a project description of something they want and submit it to IT, and it's using references to databases and things they have no idea about, but it sounded legit to them. And now someone in IT needs to, you know, a leader needs to go sit down with that person for an hour, hour and a half, and talk them down and say, that doesn't mean anything. Like those words don't mean anything. And so we're really trying to figure out like how do we stop people from using this to go beyond their own expertise? Like you cannot, it cannot, it can extend your capabilities, but it can't extend your knowledge and you cannot trust everything it says. And so you really have to be kind of securing your space to lean on it safely.
SPEAKER_02:And cannot replace you as well. You are more than a co-pilot, you are a human. And uh you talked about it can delay us in the learning curve. In fact, and I've seen this again and again. I've lived in through this experience. I have personally trained over 200 hours of generative AI. So I've seen it. People sometimes give up and say, I might as well do it myself. It's faster. And we're saying to them, that's not really the point. You may go slower now, but it will think long-term game. And the second thing is that you are the human in the loop, so you are accountable for anything. Uh, that is not a new thing. The the fact that this gives you extra information and puts it in audience it in such a way, that is not an excuse to actually say, well, it's done it for me, you still need to check the words, you still need to check the positioning, you still need to check the context in there. But the beauty of that, Lindsay, is that the more you build context engineering with it and build your capability and your knowledge with it, especially during a daily use, this conversation around relevance will actually become obsolete later because it can it will start making music with you.
SPEAKER_01:Mm-hmm. Yeah. Yeah, but people definitely have to put the time in at the beginning because it's not an immediate thing.
SPEAKER_02:What what is the role of leadership uh in all of this story?
SPEAKER_01:Well, I think it's very much like every change, leadership has to lead it, inform it, um model it. I think that's one thing that often is missing. Um leaders will think, well, if I didn't disagree and I'm not rocking the boat, then that's enough. And especially with AI, it's not enough. Like we really need to start to incorporate it into our daily lives, and you need to expect your people to be using this tool and to become experts. And without that sort of expectation, because no one cares what IT thinks, but they do care what their manager thinks. And so without modeling it and really embedding the technology change, it's not going to be successful.
SPEAKER_02:And when do you think leaders would start mandating using the capability? Is that the right way? I think for AI. Yes. Yes. Um that's probably in America, not in Australia. Not yet in here.
SPEAKER_01:So right, yeah. Y'all are still going rogue. Yes, yes. Um you know, with with other changes, it can be a little easier where it's like we just rolled out this new ticket system, thou shalt use the ticket system. And if I find out you're not using the ticket system, we're gonna have a conversation about it. With AI, it's a little different because someone could think that they're using it effectively. But it's also up for the to leadership to use their judgment of what's the most important, like what's what's the priority here and what are we trying to actually achieve? And I think they also have to like mentor and guide their teams. Now, the challenge can be that leaders have been out of the technical game longer than their team. And so often the leaders are less tech savvy than their individual contributors. And so their expectations can be wildly off base. And so trying to get leaders' expectations to be both realistic, but also like we want to set a challenge. Like, we need to expect people to be able to rise to the moment. Um, and so that is kind of the sweet spot for getting leaders to support this.
SPEAKER_02:Such an important point around that literacy for the leaders currently, and because not many of them get it, and they just think this is another tech uh change in there. I really like that. I want to run uh I'm aware of time, and I want to run one idea by you, and I've just started thinking about it actually just yesterday. This is the conversation. If Lindsay's got uh a business need to recruit extra people, and uh Lindsay's team has already got co-pilot capability and we train them, could we get to the day where Lindsay will come to me as a CFO instead of asking for more resources, Lindsay will ask for more capability uplift and building for the team, meaning she would like to optimize how generative AI is being utilized. So she can ask for Lindsay will ask for 10 hours of upskilling and deep learning with it for her team rather than asking one FTE or a part-time casual that will help her for six months for a particular thing. What do you think about that?
SPEAKER_01:I for sure think that that I don't know about the individual teams asking for it, but I could see companies saying, we have a learning lab and we have a cycle that every team is cycling through once a year or whatever it is, and like investing in that sort of upskilling.
SPEAKER_02:Yes.
SPEAKER_01:Um and then that would be, I think, a lot more easily, that'd be easier to like manage too. But I think so, because if you can get a team that knows how to knows their business, knows their data, and knows how to leverage AI, then you got to get them a little bit of time and space and maybe bring in some other experts to just like you know, it's a lot of I'm I really am excited to be alive right now because it's like I know we're getting to workshop, like we're getting to be creative. And, you know, as as an English, I was an English major, and so I'm like, my writing skills are suddenly like super important because now I can talk clearly to co-pilot. And so if you can get a room full of people who have good writing skills and they know what they're doing, um, and they know how to write prompts and they have their context engineering done, I really think that's really what you're gonna start investing in.
SPEAKER_02:I love it. Um I'm aware of time, I'm thoroughly enjoying this conversation. What would be an advice for people like me and the rest of the challenge management community when it comes to realizing value uh value in different format uh around the change? How where can we influence?
SPEAKER_01:I think helping organizations understand how far they've come because very often we get blind to the progress we've made. And then also I think starting to really set specific goals of where we're going and then show that we've reached them. I think that's kind of the number one thing that we can all be doing.
SPEAKER_02:Well, I've got uh a challenge for you. At some stage, you'll be uh I'm giving you an article uh idea from noise to music. There you go, uh Lindsay. Uh that's you're welcome, Lindsay. And uh that's my idea for you. And uh, that's the challenge. It will be useful for all of us in the community to see an article coming from you around that. And uh I thoroughly enjoy this conversation. I would like to know how people can connect with you.
SPEAKER_01:Hey, I'm on LinkedIn, so Lindsay Phillips, ATX, and on LinkedIn, and I'm also on Forbes, so I'm a Forbes contributor, so folks can come kind of see what I'm thinking about. But I really would love to just continue to have these conversations.
SPEAKER_02:Fantastic. We're gonna put all your information, Lindsay, in the podcast info. It's been a pleasure having you in my podcast, the inner game of change. I hope I can get you back maybe next year and we have another conversation and see how the world has actually changed in 12 months' time.
SPEAKER_01:That would be great. Yes, we can use AI to analyze this conversation, what we said was gonna happen.
SPEAKER_02:And I I want to drop in there that uh your episode, I will use ChatGPT to listen to our conversation and give its own opinion at the end of the episode. And uh and that will be an interesting sort of mix. Uh I've always wanted to do it. I didn't commit to it, but now I'm in public, I'm committing to it, and I'll make it happen as well. Yes, until next time, Lindsay. Stay well and stay safe. Thank you. Thank you.
SPEAKER_00:Hi there, it is ChatGPT here. I listened to this episode of The Inner Game of Change, and here are my takes. What struck me is how Lindsay and Allie brought focus to a truth we often overlook. The promise of value is easy to make, but far harder to measure and sustain. Too many projects start with bold claims and finish with tired teams who never stop to check if the promise was kept. That gap is where change often falters. History is full of similar patterns. The printing press did not change Europe because the machine existed. It changed Europe because people learned to read, debate, and share ideas. The steam engine did not matter until people redesigned work around it. Technology alone has never been enough. It is people who translate potential into progress. That lens makes the discussion on generative AI especially powerful. Learning to use AI is less like installing a tool and more like learning an instrument. At first, it is clumsy noise. With practice, it becomes sound. With leadership and persistence, it becomes music. The question is whether we are willing to play through the awkward stages. And as always, leadership is the amplifier. Leaders who only sign off budgets rarely see real adoption. Leaders who model the behavior, guide their teams, and ask the hard so what questions turn adoption into mastery. So if this episode gave you something to think about, whether it is how you measure value or how you practice until the tune becomes clear, share it with someone who might benefit from it. Conversations like this are meant to travel. That is my reflection. From promises to practice, from noise to music, what change are you willing to play through? My thanks to Lindsay Phillips for her insights and to Ali Juma for guiding the conversation. And thank you both for allowing me into the conversation. I look forward to the next episode of the Inner Game of Change podcast.
SPEAKER_02:Thank you for listening. If you found this episode valuable, remember to subscribe to stay updated on upcoming episodes. Your support is truly appreciated. And by sharing this podcast with your colleagues, friends, and fellow change practitioners, it can help me reach even more individuals and professionals who can benefit from these discussions. Remember, and in my opinion, change is an enduring force, and you will only have a measure of certainty and control when you embrace it. Until next time, thank you for being part of the Inner Game of Change community. I am Ali Jumma, and this is the Inner Game of Change podcast.
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