In this episode of Game Changers, host and Principal Consultant Sophie Brazell-Ng is joined by Clarasys change expert Scott Docherty to delve into the impact of Generative AI on people.
Together, they unpack how Generative AI is reshaping work and creativity, exploring its practical applications, challenges, and the importance of prioritising people in the adoption journey. From fostering innovation and efficiency to overcoming fears around AI, this conversation offers valuable insights for organisations looking to harness Generative AI effectively.
Drawing from their experience at Clarasys and their hands-on work with AI solutions, the duo share actionable tips on experimenting with Generative AI, supporting teams, and navigating this rapidly evolving technology.
Listen here or read on for an edited transcript.
Sophie Brazell-Ng: Welcome back to another episode of Game Changers. Today we're going to be talking about the hot topic that is AI, but we're going to do it a little bit differently. A lot of the conversation around AI is about what it means for the future and heavily focused on the technology. But we're forgetting it's here and now and people are really trying to understand what it means for themselves as people and as an organisation.
There's a lot of fears and hopes and excitement wrapped up into the topic and as change managers a lot of what we do, particularly in the technology space, is helping people with adoption of that. But we're seeing that people are really forgetting that we have that capability as a change manager and we're focusing on this from a very technology focused lens.
Today we want to have a discussion about the impact of Generative AI on people and what we can do as change managers to support them. We'll be talking about strategies and challenges of change management in AI projects and how we can manage the fear and excitement and the resistance that comes with that.
Really, really excited for today's episode. I am joined by Scott today. Scott, would you like to introduce yourself?
Scott Docherty: Hi everyone. I am Scott Docherty. I'm a managing consultant here at Clarasys. Unsurprisingly, my background is in change management. And that's been across public and private sector and also across a range of different topics, be it digital transformation or process, some op model type stuff as well. And yeah, very excited to be talking about Generative AI today.
We ran an event a couple of weeks back where we focused on this topic and had some very interesting and thought provoking topics that came out of that. So happy to delve into some of those in a bit more detail and share some of the learnings.
Sophie Brazell-Ng: Awesome. Thanks, Scott. And thanks for joining us. I'm Sophie Brazell-Ng. As always, I'm hosting the Game Changers podcast. I am also a consultant at Clarasys. Scott and I have actually worked on a couple of projects together as well, which have been really great in the change space. So first things, I'm going to start off with a definition, and I think quite a lot of people may know what Generative AI is, but a lot of people don't.
And I know that if my mum was listening to this, which I know she will be, she'll be saying, Sophie, could you have please started off explaining what Generative AI is? So, Scott, what is Generative AI and what is AGI?
Scott Docherty: So Generative AI is slightly distinct from AGI in a couple of ways, but Generative AI creates specific content based on learned patterns, while something like AGI, which is artificial general intelligence, aims to replicate human like cognitive abilities across a wider range of tasks.
Sophie Brazell-Ng: Awesome. So, Generative AI, think of things like ChatGPT, which everybody is talking about. You've got Claude, you've got Microsoft Copilot, there are so many Generative AI tools coming out at the moment. As far as I know, we are not at the point of AGI just yet, so we're not looking at replicating human like cognitive abilities, but Generative AI as a co intelligence, a co author with us at this moment in time.
Sophie Brazell-Ng: As another definition, Scott, what do we mean when we're talking about impact on people from a change perspective?
Scott Docherty: Yeah, and this is where I guess people's definitions fluctuate from those that have been involved in different transformation projects. To me, it is really about what people are doing on a day to day basis.
How does Generative AI impact their jobs and the actual processes, the actual activities that they're practically doing in their jobs?
Sophie Brazell-Ng: So to help keep us on the straight and narrow, we are going to navigate this podcast through three sections.
The three sections that we are going to cover, and we also covered at our Generative AI event is: number one, putting people and what they do first, number two, keeping up with the speed of change, and number three, overcoming fear and resistance.
So first things first, putting people and what they do first.
Sophie Brazell-Ng: Generative AI, as I mentioned, is currently, I'm viewing it as something that's about co-intelligence. We're still at a point where somebody needs to use it and it needs to serve us and we need to input into it. For those reasons, we believe that putting people and what they do first is extremely important when thinking about how you can use Generative AI tools and what that means for your strategy, whether that's as a business, an organisation, or as an individual.
Scott, I just want to dive into this a little bit more. Why do we think that putting people and what they do first is important when thinking about your Generative AI strategy?
Scott Docherty: To me, this comes back to the core purpose of what Generative AI is. So the goal with Generative AI is to enhance human capabilities, not to replace them. So in that manner, we need to put people at the forefront of the decisions that we're making around Generative AI, be that from a design point of view, from a vendor selection point of view, or actually, when it comes to some of the stuff that we might be doing in terms of rolling out Generative AI, but in terms of our change management approach as well.
I think there's a really interesting quote, actually, that Tim Creasy, who's the ProSci Chief Innovation Officer, noted. And he said that Generative AI, in the way we view Generative AI, we could think of it as an extremely skilled intern rather than an oracle. So it is there to provide you with support in terms of task and iteration and collaboration, but actually in and of itself isn't going to provide the answers.
So we still need to provide that strategic overlay on the top of anything we're doing and we need to put people at the heart of that.
Sophie Brazell-Ng: I really like what you said there. It's a skilled intern, not an Oracle, and it goes to the point that it's co-intelligence. You have to input into the tool at this point in time when this episode goes out, it might have suddenly released a completely new generative AI tool that you don't need to do that. I dunno if we're kind of really there at the moment, but we do need to work with the tools that we have.
I'm finding it really interesting because our clients are coming to us at the moment and saying what Generative AI tool do I use or what does it mean for my strategy? And I'm going back to them with a question, not an answer. And it's what are your people doing? Do you know what your people are doing? Because they will be best placed to help you understand what you need a Generative AI tool to do.
And we're really commonly seeing at the moment in time that decision-making is made very centrally. So A CTO or a CIO will be given a budget and it will be very much centered around saying, this is your budget. We need you to go and invest in generative ai. What an enormous question to go and be asked. And it's often also very limited as well. So it's, you've got a choice between X or Y. You've got a choice between chat GPT or copilot or whatever it is. That doesn't seem to be the right question that boards or CTOs or CIOs should be solving. I think that the first question that they should be solving to truly understand what Generative AI can mean for them is, what are our people doing or what are they trying to do? And then how can they use Generative AI to best solve those problems?
Scott Docherty: Agreed. Completely. And there's a point there that in understanding what people are doing on a day-to-day basis, we can actually better understand where the game changing differences that Generative AI can make actually are.
Scott Docherty: So, A CTO or a CIO or whoever said decision maker is, making a call on what technology they want to introduce across the organisation that will be based on assumptions. That will be based on a far distanced understanding of what people on the ground are actually doing. So they may make decisions that can improve efficiency. Great. And you might make a 15 percent improvement in efficiency. But actually, where you might get that game-changing efficiency improvement is by understanding on a more practical level what that individual is doing on the ground. So, for instance, the introduction of chatGPT to speed up comms writing. Great. That might save someone 10% of their time and resource in a week. But actually there could be another area where the introduction of an AI tool could save them 50 to 60 percent because they're having to do a far more arduous task. But we can't understand that unless we've truly engaged with the people and understand what they are doing and what their needs are on a more granular level.
Sophie Brazell-Ng: Yeah. And there's a bit that you mentioned about productivity and I'm also going to branch that into efficiency as well. A lot of the digital age and the recent modus and thinking around how do we progress organisations as being around, how do we be more productive? How do we be more efficient? And also putting percentages next to things like productivity efficiencies really gives me the ick right now. How do you label those things? But I think when it comes to Generative AI, knowing that it is actually quite a creative force, is that really the right KPI or thing that we should be tracking? Yeah, it can make us more productive and it can make us more efficient, but as a person that's putting more pressure on me to then be more productive and efficient. And I might not be as good at using a Generative AI tool as somebody else might be. So that's already putting me on the back foot.
When we're actually thinking about productivity and efficiency, it is just focusing on the tasks that I do now. So, as you said, it's going to make me 15 percent quicker at writing a communication. But is that actually the best way to use the tool? If we allow people to experiment and actually understand what your colleagues, your employees, what users are actually using the Generative AI tool for, then it allows us to think more innovatively, more creatively. As somebody who might be somebody's direct report, I would say, oh, I actually want this communication out really, really quick. Yeah, they can go and have a use of Generative AI to get that. But that's me being very directive. Actually by putting the people at the center and understanding how they're using it and allow them to explore it. In a way that I'm not kind of going top down, this is the KPI or this is the task that I want done from it and this is why I'm expecting from it. They can go and find new innovative ways to use the tool that actually might help us explore into new areas in a business or think about things in a really different way that we hadn't done before. There's something about being able to unlock a different kind of potential beyond productivity and efficiency.
Scott Docherty: Completely. And, on that point, this is where I think there is a slight dynamic shift where currently technology, or should I say, prior to Generative AI, technology was very much used and considered to be an enabler of specific tasks, processes, and business activities. And it was quite easy to pigeonhole what a technology was enabling or supporting.
So take a CRM system, it helps you run a customer account through the lead to cash process. Great. It's clear what it does. And it does that one thing, and it does it fairly well. What we have now is a situation where there are tools that we are going to be introducing into an organisation that actually we don't really know the full scale of how they're going to be used. So there are use cases that might emerge that we actually don't know. Don't have line of sight to or that we hadn't foreseen in our business case that we'd put together when we looked for the investment for this. I think the creativity bit and the innovation bit is a massive part of that.
Scott Docherty: There's going to be a whole bunch of stuff that some of the colleagues and some of your employees are going to go away and do with the Generative AI tool that you hadn't anticipated them doing. And that actually might have some really great results out the back of. But, you know, how do you know that that's going to happen? Well, to be honest, you might not. I guess the question is, how do you track creativity? How do you track innovation? And how do you keep a line of sight to that as you go through the process of implementing this new technology? And that I'd love to hear your thoughts on Sophie.
Sophie Brazell-Ng: It's an interesting question. How do you track creativity? Do we track creativity? Is it something that we actually really want to do, because it makes me worry that we might think, okay, instead of tracking productivity and efficiency, we're going to track your creativity. Ugh, that feels really stifling. That feels like the real opposite of what we're actually wanting it to achieve. But there's something about allowing people to explore and listening to the use cases and novel and innovative ways of doing things that you might not have thought of centrally, where that budget is coming from, if we think about traditional investment and business hierarchies.
Another interesting conversation I had with a client recently was they were telling me that they put forward a business case, they invested a lot of money in Generative AI and it wasn't returning on the investment they thought.
Sophie Brazell-Ng: My question back to them was, well, what KPIs were you tracking? And they were like, Oh, we were tracking X, Y, and Z. It was a really tangible to some particular cost savings, particular kind of line items, P&L type stuff. And I was like, well, why are we doing that? Isn't the whole point of that investment to figure out things you didn't know? And they were like, well, we had to put that in for a business case to get the funding for it. Okay. Yeah, that makes sense, but we've really pigeonholed ourselves. We've determined success in a really different way. And actually if you go and open the cupboard somewhere else, so I had a chat with a couple of people that were using the tool that they invested in and they were like, yeah, it's great. It's allowed me to do this, this and this. And actually we've like spun up this whole new space in this area and we've thought about something in a different way. Well, that was never going to be reflected in the KPIs that were chosen in a business case. So I actually went back to them and said, look at some of the stories and the evidence that we've got here that actually shows you that your return on investment is actually really big, but maybe it's not return on investment, maybe it's return on creativity or return on innovation.
Scott Docherty: Or return on people. As change managers, I'm sure most of us have been privy to or being part of processes where we've been asked to report on the success of a change. And sometimes that can be really hard to put a finger on. How can you track sentiment? How can you track how someone feels towards a thing rather than the harder efficiency data or productivity data that we've referenced earlier? Actually, there's impacts on wider job satisfaction, almost you could say, that again, is maybe a spillover effect and not necessarily the reason why you've introduced the thing in the first place, but it's still definitely a positive benefit from what you've done.
It's part of a wider thing about this isn't necessarily related to efficiency when it comes to process or being able to complete a task X number of times quicker or faster. There are a wider set of considerations that we need to think about when we're talking about introducing Generative AI because of the wider impact that it has on jobs, on activities and what people are doing in their day to day work. It's not just. related to a specific process or a specific task.
Sophie Brazell-Ng: Yeah, I love it.
Before I move us on to the next section, I think there's just something that's really stark and important that's coming out here for those that are listening to this podcast. This question does go a little bit beyond Generative AI in itself because we're talking about understanding what your employees do in this instance to then actually help with your investment. I don't think that just actually is something that you should do to understand what you're doing investment for Generative AI.
I really, really encourage those who are listening that maybe don't have regular engagement with employees and on the ground to make sure they do those day-in-the-life activities and actually genuinely do them and do them regularly. Not just that, Oh, I've done a day in the life of tick box. It's getting on that shop floor. It's getting in that volunteer space. It's really, truly experiencing what your employees are doing to be able to help you make great decisions at the top, or even as a leader, as a manager, as soon as you are even once removed from your employees, then you're not really going to understand how they're feeling and being impacted by something. So even if it's not just Generative AI and you're not being asked to invest in that, I encourage you to have a think about how you understand what your employees are doing and therefore the things that are important to them, the decisions that they're having to make.
Scott Docherty: And can I emphasise that point about the decisions? Because as you say, Sophie, it's all well and good us doing the work and going and looking at what people do, doing employee experience journeys, even doing customer journeys as well. I guess it relates to customer as well. It's how are you then feeding that into a decision and incorporating it as a consideration and decision? Because if we aren't doing that part, then that work is pointless and it's wasted effort. So it's as much doing the work to understand, but also actually incorporating that into what you're then going to do about it.
Sophie Brazell-Ng: Nice. Onto the next topic. Keeping up with the speed of change.
So, I had a really interesting quote the other day that made me chuckle a little bit. In prepping for this podcast, listening to a lot of other podcasts, watching some YouTube, reading different articles, and somebody said in one of those that learning about AI is like listening to a history lesson or learning like a history lesson because what we have right now will be the worst and the oldest version of any form of Generative AI. It's only getting better and the pace of change that's getting better is quickest that it's ever been.
If we are looking back the amount of progress that we've made in such a short space of time, even if you start to have a look at some of the way that Generative AI is regenerating images, for example, and a new meta AI have released a lot of things for WhatsApp and image regeneration, etc. It really is an interesting thing when you actually stop and take a moment and think, okay, it took us this far to get to a point where we feel like we've got a really good use of the internet. And that took years. Decades. Now we've moved on to the next bit and it seems like we've made huge leaps in like two days.
Keeping up with the speed of change is going to be so much harder and not just harder for those that are experts in the field because they're having to keep up with that pace of change, but from an organisation. We're actually unless you're really small and really nimble and quite frankly at the forefront of the topics and conversation about Generative AI it's not easy to move.
Changing an organisation is like trying to change the direction of a big moving barge. It actually takes a lot of effort. And coupled with that, people are going to be at different points in their Generative AI journey. It's likely that Generative AI is going to be ready quicker than you are. And it's likely that some of the people on the ground, your employees, will be a lot further ahead than you are.
It throws up a really interesting point about what does the speed of change mean when we are thinking about Generative AI. I'm just wondering, Scott, this is something that you've spoken about quite a bit our events. What are your thoughts on the pace of change with GenAI tools and what that means for people?
Scott Docherty: Yeah, well, first of all, I absolutely love the history reference as an ex-history graduate. That was spot on, but I think you're absolutely right in terms of the speed of change of Generative AI and the tools and the developments that are happening in that space. They're going to be far, far quicker than almost any organisation is going to be able to move. And also any organisation is actually going to be able to practically rule anything out at. So I think first of all, there's accepting that.
Scott Docherty: We need to appreciate that you're not necessarily going to be at the cutting edge of absolutely every element of Generative AI. What you can be is be at the more forefront of the bits that matter to you.
So to that conversation, we've just had prioritizing needs, prioritizing pain points of the individuals and relating that to actual job roles. We've talked about that a bit already, but having that as a key prioritisation element of your decision-making, I think is absolutely essential.
And then beyond that, I think that we need to start considering that people are going to be using Generative AI. So you either need to get on board or, you know, the ship is going to sail without you.
There was an interesting study that actually the CMI put out. It surveyed a thousand different managers and it said that 58 percent had used Chat GPT for work, but 86 percent had never received any formal training from their employers. So the first thing for me is Do something, do something about it. Do anything because at this point people are using it, right? So if you're worried about the speed of it, if you're worried about how do I keep up with it, the first step is do the easiest thing. Give your employees some basic principles, guidelines, policies around usage of it because it is happening and it's happening in your workplace and you need to accept that. And if you aren't, then frankly you may or may not be in a state of denial. But beyond that, I think the other bit to consider is that from a technology implementation standpoint, this is not the same as our usual technology implementations, where you can put things onto a nice project plan, put some resources towards it, and in three months time, you'll have a new system that's been rolled out to all your employees.
Scott Docherty: I think we need to start viewing this period as a longer, more dynamic, long-term transition. So setting up support and setting up mechanisms around the introduction of AI into your business, do not timebox that. Let that be a more of like a longterm, long running process or governance that you're putting in place. Don't put a governance and structure around that that's, that's too timebox and tightly knit around a particular outcome. Because I think we're not going to be able to predict what's going to come. And we need to accept that the change is happening so fast and, you know, most of us aren't actually the ones driving that change. We're the recipients of it. So we are going to be responding to those changes and those developments in the tool. And actually by putting a structure that is more of a long term and something that is there for a period of time and not just a time box, then that will help support that a little bit better.
Sophie Brazell-Ng: So many really great things to unpack in this. I think there was something you shared about guidelines and principles and I think for me is a really important thing about keeping up with the speed of change here is that actually we need to be inquisitive.
Sophie Brazell-Ng: People are using it and we don't need to know the answer and we don't need to tell people how to use it, but we do need to put some guidelines and principles in to help people use it in the right way. So it's not a complete cowboy of environment. You do need to think about your data. That's going to be something that's really, really important that you want to have a strategy around.
The other thing is that we want to make sure that we're not creating this tech monolith, as you say, because actually when we link it back to the point that we made around history and anything that you're using is going to be the oldest version of a Generative AI, we don't know what's coming down the line. So actually, if you put a plan in place and six months down the line, you're like, brilliant, we've delivered it. We've rolled it out. You are going to be six months too old and it doesn't allow you to pivot and move really quickly. So from a tech stack point of view, something that can be agile, nimble, something that you can change.
I like to think about it as, if you're wondering where we can make investments or how do we keep up with that speed of change, it's understand the use cases. So back to the point we were talking about before, putting people first and what they do, understand the use cases you want to invest in. So, make sure you have spoken to your employees, you understand what's important to them, and they're like, yeah, we invest in those use cases, we don't know how we're going to do that in terms of this specific technology that we're going to go for, but we understand these are some broad outcomes that we want out of it.
And again, when we're talking about the business case or reporting KPIs, you need something that's dynamic. You need to report on items that do not stifle that creativity, do not stifle that innovation, but answer the question or actually ask the question, to be honest, of what have we learned? What have we learned now? What have we learned that we can make a quick change to? You're going to have to be involved in conversations with this really, really regularly. You cannot sit there and go, yep, we've made that investment. We're going to sit back. We're going to wait for six months to see what the return is. You should be constantly checking in. And also if you're doing that, essentially educating yourself on it at the same time.
Scott Docherty: Yeah, absolutely. And I think that's where delivery models also come in and are important here in terms of where are you focusing your time and effort, that's where you can start thinking about. We start small and we scale up. You don't need to
Sophie Brazell-Ng: startup mentality.
Scott Docherty: Exactly that. I mean, look at all the most agile businesses that you have. They tend to be startups or those that have maintained the startup mentality. So, it's about focusing your time and effort and it's going to be hard to know where to focus your time and effort because of the speed of change that might change within a month as you mentioned. So it's almost, you know, not worth over investing in one particular element of Generative AI until you're absolutely confident that you're going down the right path. And the way to understand that and the way to focus that is by starting small. And using your end users as absolutely central individuals in that process. So iteration, getting feedback, understanding how it's impacting them, learning about those use cases that you didn't know about that might provide more value that wasn't seen when you started the project. But understanding that and then scaling that up as you go, that's a simpler way forward. And it's going to prevent that disappointment six months down the line when, Microsoft roll out the next version of AI and you're suddenly six months behind and you haven't caught up with the curve. So, you know, start small, scale up. It's the stuff that everyone's been saying for, you know, the last number of years. I think it is absolutely is absolutely as prevalent here and absolutely as important to do here.
From our perspective as people that care about the people and the change side is involve people in that process, you know, and sometimes there is an element here where there's a bit of a cultural shift as well. People, because of our experience with technology today, expect to be the recipients of technology and to be told how to use the technology and then we run away and use it as we've been told. There's a shift in mindset that's needed here where we need to interact and engage with Generative AI in a different way that is more creative, that requires a slightly different skill set and that requires a different way of thinking.
We're going to probably come on to some of the different types of skills and capabilities that you might need to build a Generative AI, but there's definitely an element of that which we can't forget as well.
Sophie Brazell-Ng: Yeah. Turn around this section off quite nicely and move us into the next part actually, is it's coming to the forefront that we need to change the way we make decisions. We need to experiment more. But within that experiment, allow a forum for us to discuss and understand what it means for how Generative AI can enhance human capabilities, not replace them, but enhance them. And that's something that none of us know. And we need that space in order to keep up with that speed of change. So it feels like it's not running away from us. We feel like we're part of it.
I guess some of that, and actually what I'm saying there in terms of having a discussion and a forum is a way to address overcoming fear and resistance around Generative AI. And that's actually the next section that I'd really like to dive into here.
Fear and resistance is something that is coming up a lot in the conversation around Generative AI. And just to put it really bluntly, people are saying, well, I still have my job. Is it going to replace me? Robots are taking over.
The funny thing is, is when we're talking about robots, it's, you know, lots of people think about like iRobots taking over. And I know, uh, Elon Musk has recently done the, the event where he showed all of the new, the robots he's got come out. Although I'm actually convinced there was somebody inside there, but nevermind. Building trust in AI is really difficult and encouraging people to use it is really difficult. The conversation around, will Generative AI replace my job, or I don't understand how to use it, or I'm really worried that I can't keep up with it, that's not going to go away. Interestingly though, we seem to have really indexed into it in a way that we haven't really done in previous technologies. You know, the internet really changed the way the world worked and look where we are now. We've all adapted to it. What are your thoughts, Scott, on how we can start to address the question of how do we respond to fear and resistance with Generative AI?
Scott Docherty: There's a whole range of things that we need to consider here, because I think there's a wider cultural context of what is the environment like in your organisation? What is the ability for people to try and fail? And what is the transparency culture? And how does trust play out in your organisation? And actually, you know, the introduction of Generative AI might spark some thoughts amongst people about, you know, how that looks across their organisation more generally. And I think that's one thing which we'll come on to in a minute. One of the more practical things I think to do is look at training and skills and capabilities that are related to these tools.
So the way that we use Generative AI tools, we've kind of mentioned this a little bit already, but it is different to the way that you would use a normal business technology. It isn't a click button exercise where we are asking someone to complete a process with the support of a technology. What we're asking people to do with Generative AI is to engage with it in more of an innovative manner and more of a iterative manner.
There are skills like prompt engineering that people won't have done much of before, I'm sure, but that requires things like more critical thinking, more creativity, some emotional intelligence, and even things like negotiation type skills where you're trying to create an output and actually you're having to try it five, six, seven times to get to the right output with the support of a Generative AI tool, because it's not quite giving you what you want.
So skills of, how do I provide the right prompt so that it gives me the right output. That's a different type of skill. So training based on those kind of things. So as I mentioned, things around critical thinking, innovative thinking, negotiation skills, even almost. Those are topics which I would actually hone in on as, as training topics alongside, okay, here's how to access the tool and here's how to broadly use it for the couple of use cases that we've identified.
Actually, if you give people those types of skills, that will allow them to explore on a more of a practical basis how to actually use it in different ways.
Sophie Brazell-Ng: Yeah, and training now is beyond just click that button and you do X in order to do Y. It's sort of, you can use this tool to help you explore, learn this skill that allows you to do that, that allows you to best make use of the technology that you have at your fingertips.
For me, something that's really resonating is doing things differently. And we're also very much at a point where we're not at AGI right now. It's very much that we need to use Generative AI as a collaborator.
Something that I use it really well is I really struggle when I'm starting off with a blank document. And actually it's really great for me to have my first draft of something and it really helps me to unlock different ways of thinking. I still have to input the information into that. I still have to understand the question that I'm addressing. Those things don't go away. I'm approaching it in a slightly different way. I still need to be involved in it. And it will change our jobs, it would be weird if it didn't. And when we actually look at the broader world, everything changes our jobs. We just need to keep up with it.
And there's a sense of fear that we don't understand it and it's actually moving really fast, which I completely understand and get.
For me, a really great way to overcome that fear and resistance is talking about it like we are, but talking about it within the context of people's jobs, allowing them to experiment, to keep up with that pace of change if they choose to, where they choose not to, showing them that training or at least offering it to them to show how they can still be a part of it is really important.
We need that safe space to discuss things and ensure that we are still keeping a bit the forefront of our mind. What is the future of our work? What do we continue to learn? How is this keeping us relevant? It's not saying that it's going to completely take away your job, but be part of learning what your job or your new job or your new way of doing your job can be.
For me it also opens up another interesting conversation to have or for managers at the very least about what it means for your progress or where you want your job to be in the future.
Generative AI is a vehicle as we've spoken about earlier, which people are very much talking about, okay, it means we can be more productive and efficient. And that's really great, but like, that's still very much thinking I'm doing my job in the same way I was doing it today. And I've not thought about a new way to do it. I think the conversation is how can I do my job more creatively? Or how can I do my job more innovatively? And therefore what has it shown me that I didn't know before or a space that I can open up that I didn't know existed before. And I think the role of a manager, and it's something that we've discussed in this podcast previously with Sarah Partridge and also Wayne Clarke is about the role of the manager in that aspect of actually what does a great manager do. I think bringing that conversation forwards is one that can help people overcome that fear and resistance.
How are you baking in Generative AI into your ways? Where do you want to go? Okay, can Generative AI support you in that? Is that the right direction for you? I think that's all really nicely wrapped up with a progress conversation. We're thinking about not just the future of how to do our jobs, but the future of what we want our jobs to be.
Scott Docherty: Yeah, absolutely. And alongside that, as a manager having that conversation, there is an important element that they need to encourage, which is a sense of psychological safety. So if we want to address the fear that individuals have potentially around this technology, then we need to create an environment that makes them feel psychologically safe to engage with the technology in the ways that we're wanting them to.
So to actually go away and experiment, to be creative, to try and innovate with it. So there are elements of, you know, we need to create that environment where they can fail and they don't feel like they're going to be punished for any said failures. Be it, they've tried to use Generative AI in a certain way and it's not gone to plan or they have put the wrong data where they shouldn't have. Okay, well, if that is the case, we need to obviously have guidelines and policies around that, but we need to at least give them the feeling that they can go away and experiment with these things. And there's practical things you can do around that in terms of showing vulnerability in terms of inviting participation. So creating those spaces where there are communities of employees coming together and actually trying out the tools in different ways. But also things like reframing what failure looks like. If someone has tried to use Generative AI or a tool in a certain way and it hasn't worked, okay, is that a failure? Is actually that an attempt at, creativity that hasn't worked quite as planned this time, but next time, who knows? So I think there's a big bit there with the fear element, which is around psychological safety. So to the point around what managers can do, I think there are small little things that they can do, as I say, around reframing failure, around inviting participation, even around expressing appreciation. So saying, you know, well done to someone for trying, that goes a long, long way from an end user perspective and from an individual perspective.
Sophie Brazell-Ng: Yeah, I think that's a really great practical idea. Develop an inclusive culture. Reframe the questions that we're asking.
Sophie Brazell-Ng: The other item that I would really encourage people to think about, and we've talked about in our podcast with Dr. Kristina Curtis, is the COM-B model. And the COM-B model helps us deliver behaviour change. Now that's having the capability, the opportunity and the motivation to do something then results in a behaviour change.
That's a really nice way to frame the question around Generative AI. Do people have the capability? Do people have the opportunity? And do people have the motivation? Addressing those aspects of it can really help unlock a behaviour change around using Generative AI. And by actually embedding that into your culture and your way of thinking, you can really start to overcome fear and resistance.
I would strongly say though, it's just really important to not try and get rid of fear and resistance, cause that's really important and do not ignore it because it is going to be there. It's helping people move through it, helping people understand what they can do about it because fear and resistance is incredibly natural in this particular example.
Scott Docherty: Yeah, and completely understandable. I think we've all had that moment where we're hesitant on a new thing coming down the line. With Generative AI, it's felt like there's been a collective question mark around what it's going to do to who and when. And it's completely natural that people are worried about what that's going to do to their jobs because a lot of the narrative around it has been efficiency, productivity, and you know, if it does have that impact on your job, what are you going to do with the extra 30 percent time that you've saved by having this tool? That's scary. That's scary for people to have to think about, right, okay, I've got an extra 30 percent time in my week now, what do I do with it? But what we want to do is provide spaces that allow people to think about how they might use that time more effectively, how they might think differently, how they might be able to go and look at parts of their job, family or role that they wouldn't have actually delved into before because they don't have to sit in number crunch for four hours in a day.
That's taken off their plate. So actually they can do more strategic thinking or they can do that deeper level thinking that they were never given the space to do before. But again, they're not going to do that unless you put them in an environment in which they feel comfortable to do that. So creating that space as much as telling someone about a technology is absolutely vital to seeing that play out.
Sophie Brazell-Ng: Yeah, I love it. Absolutely one here for another day, but I find it really interesting you're talking about we can gain an extra 30 percent of our time in a week. And that actually, when we say that, we feel like we need to fill it. And actually when we think about a 9-5, and again I've spoken about this with Sarah and Kristina before, is the way of working in the world, we've created this construct around 9 - 5.
We've suddenly found Generative AI, and that's freeing up that time. All of a sudden we're saying, Oh, we can be more productive and efficient. Why don't we just take it and turn it around and say, we've actually created this technology that allows us to slow down.
Scott Docherty: And that's, I guess, based on our perception that work is about outputs, which, you know, so long as we're meeting the outcomes that are required, do the outputs that you're producing matter as much? And if those outputs are being picked up by Generative AI and you are able to achieve over and above the outcomes that you're trying to achieve via other means, then that's excellent.
Work isn't necessarily all about doing stuff, and having conversations can be a useful use of time if it gets to the right outcome. It might not necessarily produce a spreadsheet but it can produce ideas, it can produce innovation, it can produce creativity and those things, again, hard to capture on a KPI.
Sophie Brazell-Ng: Yeah. And I strongly encourage also people to listen to the episode that we recorded with James Radford around purpose and this is opening up ideas around actually if we get more time, can we actually connect with our purpose in a better way.
Sadly, I'm going to have to start closing the podcast, it's been a really great conversation. What I would like to know from you Scott, I've actually got two questions as we close this off. What is your biggest top tip when preparing to implement Generative AI in an organisation?
Scott Docherty: My top tip would be, I think I touched on it earlier, is changing how we're viewing Generative AI. I don't see it as a distinct piece of technology that you're going to implement, you're going to leave to your people and then pat yourself on the back. And well done. You've met your KPIs and you've achieved the outcomes you're trying to get to.
We need to view this as a longer term transition. There are going to be ongoing changes that are going to be fascinating, exciting, are going to offer up a whole range of different opportunities for organisations. And therefore I think we need to consider the way that we set up as an organisation and it needs to be appropriate to that. So we need to set up structures and set up approaches that aren't distinct and focused on particular technologies or particular use cases, but is more open minded in the way that we're going about it.
Sophie Brazell-Ng: Love it. I'm just going to add an extra one for myself. This is all a little bit more practical. For me, it's all about experimenting and encouraging people to experiment.
I'm finding it really interesting as I experiment with Generative AI and understanding the different prompts. What works? What doesn't work? What is Generative AI responding to? How is it enabling me to think in a really different way? As a practical tip, I'd really encourage people to start actually researching prompts that you can use and I drip feed them into the day. There's a lot of different newsletters, podcasts, YouTubes that you can listen to that give you some top tips on how to prompt and how to prompt well. I think that's an incredibly interesting art form and I really encourage you to at least kind of look and understand different prompts that you can use. Aim to understand three or five different prompts a week. Save those in a bank, they will then allow you to copy them and use them really regularly moving forwards and encourage others to do the same. Share them, get other people to tell you what is working, what's not working, what have they found out that you can take advantage of. So very much a practical takeaway from me.
Well, thank you very much, Scott, for a really, really exciting and engaging conversation. As we're finding, it is a topic that nobody really knows the answer to, but it's really important that we have channels to discuss it and have conversations around. With that in mind, how can people contact you if they want to find out of more information or want to have a chat with you about some of your thoughts on Generative AI or how you can help them implement it in their organisation?
Scott Docherty: Yeah, happy to be contacted. Anyway, I think easiest ways are probably via LinkedIn or via the Clarasys website. More than delighted to have any conversations, be that explorative or just wanting to have a general chitchat about your feelings and thoughts on AI and how that relates to people at any point.
But yeah, probably via LinkedIn or the Clarasys website, you can find my contact details there.
Sophie Brazell-Ng: Awesome. I've been Sophie Brazell-Ng. If you would like to contact me, similar to Scott, via the Clarasys website, directly on LinkedIn or links to my email address will be all in the show notes as well as all of Scott's details.
If you would like to contact me about work or how we can help you in that space, I would love people to contact me about any prompts they've come up with. So back to my practical takeaway, I'd be happy to share my prompts with you, but I'd love for you to share your prompts with me. So please don't hesitate in sharing some of those.
Thank you once again for listening to the Game Changers podcast, and I hope you will be tuning in for the next one.
Clarasys: Thank you for joining us for another episode of Nevermind the Pain Points. If you enjoyed this episode, please subscribe on your favourite podcasting app or site. We would love your feedback, so please leave a review or drop us an email at podcast. clarasys. com. And for more information about us, visit our website clarasys. com.
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