#104: Are we planning enough for AI?

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Oli Carpenter (Host)

Disruption isn't new, but right now it feels different. Technology, economic pressure, geopolitical shifts, changing workforce expectations - they're all colliding at speed. And at the centre of it all is AI. It's already changing how work gets done. But are organisations thinking differently? Or are they trying to lay a new tech onto old ways of working? Today we're answering the big question: Are we planning enough for AI?

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Bruce Daisley (Guest)

The promise of AI is agency. Whether it's AI agency or whether it's human agency, getting stuff done.

Kate Sweeney (Guest)

It's a completely different way of working. It's a completely different way of thinking about how you do your daily tasks.

Bruce Daisley (Guest)

We don't know what this will look like in three years, but in six months, we'll know a whole lot more about what our next experiment is going to be.

Kate Sweeney (Guest)

Different groups of people are going to need to go on their own journey. We can't expect everybody to adopt in the same way.

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Oli Carpenter (Host)

Hello and welcome to The Green Room by Deloitte. I'm Oli Carpenter and I'm joined today by my co-host Hannah Gowen. Right now it feels like every conversation comes back to change. It's happening faster. It's more complex and harder to predict. So what's actually changed? Why does it feel more intense and more constant now?

As with the whole of this series of The Green Room, AI is central to this change. But are businesses seeing it as just another productivity tool or as something more fundamental? And have firms rushed to embrace AI in work without fully considering the impact?

Today we're answering the big question: Are we planning enough for AI?

Hannah Gowen (Host)

And to help answer that question, today we are joined by Bruce Daisley, who is an author and a future of work expert and technology leader. Welcome, Bruce. And also Kate Sweeney, who is the Human Capital Consulting Leader for Deloitte UK.

Let's start by exploring the external pressure that firms are currently experiencing and why that disruption feels more intense now. Bruce, you ran YouTube in the UK and then Twitter across Europe, Middle East and Africa, so you know about pressures that leaders are under. But what is it about now that feels different to what you've perhaps seen in the past?

Bruce Daisley (Guest)

Yeah, I ran Twitter under the previous owner I should emphasise. Yeah, I think the interesting challenge is that probably businesses used to think that there'd be these big surprise, disruptive shocks once every five or ten years, and they feel like they're happening every year right now. And so, to some extent, knowing that you're going to get something unexpected shouldn't be a disruption to the business plan. It should be just an anticipation of the business plan. I think that's the challenge that, before that you might turn up somewhere and explain in your budgeting, “look, this unexpected shock happened.” And I think to some extent now we’ve just got to bake it in, we've got to expect that there's going to be something that knocks the train off the tracks.

Obviously, it makes doing business immensely complicated because you lay down your best laid plans, you've got all your good intentions, and then something completely unexpected happens. But I think that's the current reality that just the cycle of news, the cycle of global politics, is just making things a lot harder to predict.

Oli Carpenter (Host)

It's definitely a complex landscape. And Kate, from what you're seeing from organisations and through Deloitte's latest Global Human Capital Trends report, what are some of those pressures causing businesses to think differently?

Kate Sweeney (Guest)

I mean, I completely agree with Bruce around the uncertainty, but I think as well it's that sense that AI is here. It's kind of, fundamentally everybody knows they've got some really big competitive decisions they've got to make, and the uncertainty around “how do you make them?” I think at the moment. You've got, on one side, people are really struggling, loads of experimentation but very difficult to scale, so people don't have the confidence to say, “we know this is the right way to go”. And the flip side as well, huge investments, huge investments in technology, and everybody's looking at kind of token consumption and token pricing, and we're not sure how to model it. So again, I think that forward view feels like a really difficult environment to be making decisions within and having any sort of certainty.

Bruce Daisley (Guest)

I'll add something to that actually, because I hear you exactly, and the really interesting thing, I turned up at about three or four events in the last few months, and on stage there were all these really compelling stories being told about what people are doing right now, what businesses are doing. And I was sort of chairing a couple of round tables, and the conversations that I ended up having were people who came up to me afterwards and said, “we're not actually doing much right now”. And you've got this simultaneous challenge where everyone recognises there's a fast pace of change, it's kind of overwhelming in the disruption it represents. But simultaneously, a lot of people are looking at their working week and thinking, “yeah, we've not actually changed much ourselves yet”.

And so you've got, I think, the added complexity that there's so much noise, there's so much fearfulness that you're going to miss the moment, and then additionally, people are thinking, “I just don't know what our answer to this is”. So it adds to the, probably adds to the anxiety of the moment, where everyone just thinks, “I don't know if people are doing more than us”. You know that feeling when you're in an exam and someone puts their hand up and ask for more paper and you're like, “Hang on, hang on. What? I'm nowhere near!” And it's just like, at the moment, we're surrounded with loads of people putting their hands up and asking for more paper, and we're not sure how we should interpret that I think.

Hannah Gowen (Host)

On that point, and Bruce you touched on it, around businesses are used to adapting to change incrementally every few years, and we've seen it with technology throughout history, right? But at the heart, with AI for business, is it just another wave of technology, or do you think Bruce it's something more fundamental than that?

Bruce Daisley (Guest)

I think that's the big debate, isn't it? And I suspect - I've got a couple of people I ask on these things, and I've got someone who used to work at one of the big AI labs, now works somewhere else. And for a long time I was saying to him - until the middle of last year - I was saying to him, what do you think?

And he said, “be cautious in thinking that this is going to change the world”. And I saw him at Christmas and he said to me, “I just need to have a quick word with you before you go, because I've updated my opinion”. And I was like, okay. And it was just after Claude Code had come along and now all of the coding products have improved. And he said, “I have changed my opinion, I do think this is more meaningful now”. And so every time I see him, I saw him a couple of weeks ago, and he's like, “yeah, it's really accelerating right now”. In fact, he's a software developer. He says, “effectively, I've got 5 or 6 agents at any point doing things for me, and I'm probably working about 4 or 5 times faster than I was before.”

So, look, I think people involved are saying something meaningful has happened when it comes to the software development side of things. And so I think that that's worth taking into account. I use a lot of the tools for editing and as a thought partner - I've got a friend who's a professor who uses it to help push his thinking - and I've definitely noticed a very significant change in the last six months.

So I'm of the opinion that this is quite meaningful. When it comes to our jobs, I think most of us haven't seen a big enough change yet where we say, “this would fundamentally change how I do my job”. So I would expect that that's coming”. But that's why, to some extent, there is still so much debate and discussion on this.

Oli Carpenter (Host)

It's interesting because there's definitely a sense that there are efficiencies to be had with the implementation of AI. But I think you're right in saying that some areas haven't quite figured out yet, have they? And Kate, how are you approaching those conversations around AI with clients that you're working with? Because, do they feel like it's a real opportunity, or is there just pressure to implement and get it into their organisation?

Kate Sweeney (Guest)

I think both. I think there's a sense of real opportunity and that pressure of “we're not quite sure how to respond”. But for me, I think your question about “is it just a new technology?” is actually a brilliant question, because I think one of the challenges is that organisations are treating it like it's just a new technology.

If you think about the challenge, we were saying people aren't really adopting it, they're not using it. And I think we're pushing it out as if it was a new technology, and we're all used to the next drop of software that comes and you just intuitively work it out. And actually AI isn't intuitive. It's a completely different way of working. It's a completely different way of thinking about how you do your daily tasks.

And until organisations start tackling that challenge, I don't think we're going to see AI scaling beyond a little bit of personal productivity. And I thought it was really interesting, Bruce, when you were talking about using AI as a thought partner, because a lot of what I'm seeing is that actually people aren't really, they aren't really trusting the AI. So they'll use it a little bit to sort of take meeting minutes and sort of accelerate reading of documents, but actually starting to use AI in their output is something that they're not yet confident and not yet trusting. And I think we've got a huge trust gap to overcome if we're going to start really accelerating and scaling AI.

Hannah Gowen (Host)

You've touched on scale there, I think that's a really important point that we can move on to. We know that AI is already delivering benefits – we’ve touched on some of those already - businesses really pushing forward to invest heavily to try and scale across their organisations. We asked a couple of episodes ago if people were the superpower behind this technology and those transformations, but if we look at the organisational side of things - I'll open this up to both of you - where are you seeing the biggest gaps right now in terms of the potential that AI has, and what organisations are actually managing to deliver?

Kate Sweeney (Guest)

So I'm seeing a couple of things - and I think probably the software area and coding is definitely where we're seeing things progress fastest - but if I look at organisations and how they're trying to change, I think what they're not doing is looking at how do we rethink work. So, what we're seeing is people who are effectively using AI to reproduce the current processes and the current ways of working, and that's never going to deliver benefits.

And actually what we need to do - the businesses that I'm seeing that are making strides - are where they're actually asking a completely different question, not “how do we AI what we do now?” but “how do we actually completely rethink? How do we get down to the tasks and talk about what do we want our agents to be doing? What decisions do we need humans to be taking? How is that whole world going to look different?”

And at that point, you can start seeing how you can completely imagine a bit of an organisation, you can scale it up, and then you're going to have people in agents working in a totally different way, taking decisions in a different way, using information in a different way. And I think until we get there, we're not going to see the big step forward.

Bruce Daisley (Guest)

Yeah, there was something really interesting I saw - Microsoft run this sort of annual report called the Work Trends Index, and they've been doing it for the last three or four years. Last year they said, we're entering an era where intelligence on tap will rewire business. And what they meant was some of us use ChatGPT already, or use something, when you're planning a holiday or when you're planning a meal, or when you know you go there and you ask a quick question, you get something back. In fact, it's why so many of us are using AI in our real lives more than work.

But they described that situation in work, and what it immediately poses the question, if you go to the AI and you say, “I want to do this”, whether it's to write you a marketing plan or to write you something for the next 12 months, if everyone in your competitors does that, if everyone in a rival firm does that, isn't there a danger that we end up with the same answers? And everyone comes back, and you've got you've got your plan for next year, and so has everyone else.

What it poses for me is, it poses a question - exactly to your point - have you taken a step back and thought about, well, what are the principles we bring to this before we start? What's the difference about our organisation? What's the culture that we've got? What's our point of disagreement with the world outside? And I don't think many firms have started with that.

And so - whether that's your tone of voice, or whether that’s the way that you deal with customers, or the way that you treat people who deal with your business - unless you've established that at the outset, I think there's a danger that AI could lend a bit of momentum to homogenisation, that you effectively just become exactly like every other business in your field.

And it poses a really big question: what are our prior opinions, and have we even thought about them? And so, you know, that's a big gap that I don't think we've thought about.

Oli Carpenter (Host)

Yeah, a very good point because I suppose, you put the same stuff in, expect the same stuff out, right? So how are you seeing, Bruce, businesses really tackling that AI challenge? Because Kate, you alluded to earlier, sort of just simply layering AI on top of current ways of working just won't work. We need to get to that granularity across the enterprise.

So, Bruce, any examples you can bring to light in terms of how businesses are really tackling that?

Bruce Daisley (Guest)

There's a really interesting thought experiment, actually, because one of the things that comes out in that Microsoft report is they say we're going to go to an era - exactly to Kate's point - where work looks very different.

Effectively they say, think about what your working week looks like right now. For most people, that is 20 to 30 hours of meetings, right? To some extent. And if you look at the model, they say, yeah, it won't look like that. You won't have standing meetings every week with the same people. It will be more project based. They use a metaphor - it's going to be like film production, where a crew assembles, works on something intensely, then disassembles and works along. And it's such a leap from what we do right now. So I've said to people, “can you imagine an environment where your world, your working week isn't constructed around your calendar to the same extent?” And people have said, “yeah, I think I'd be uncomfortable with that”.

And that's a really interesting start point, because if you're uncomfortable with breaking away from this rigid way that your work looks now, then I suspect you're not going to be prepared for these changes and these disruptions. And I understand it - we all hang on certain dependabilities. “I know what Monday looks like. I really know what Wednesday looks like, so I can plan aspects of my life around it”.

And if we don't have those things - I think as a thought experiment, it's a really interesting way to think - okay, well, really on a cosmetic level, we all talk about change, but are you ready for little bits of change that might disrupt the flow, the comfortable way that you do your job right now?

Kate Sweeney (Guest)

But I think it's a great example of turning the way we think about work on its head. And I think something else we're going to have to spend a lot of time on is, what do we value in the future? We all want to feel valued, but it used to be that you'd feel valued by responding really rapidly to emails, or turning up to meetings, or doing all of those sorts of things.

And actually - in a new world where you've got thought partners that are AI - sitting in your room and thinking with an AI could be a real place where you're adding value. So starting to think differently as a business about where does our value come from? And for individuals, how am I adding value to work?

We've done a lot of work with journalists actually thinking about how they adopt AI, and one of the big challenges that they're leaning into is a real sense of almost, letting the side down if I start using AI. Am I somehow betraying my journalistic values? Is one of the big, big themes and another one around fact checking. So we were finding that 60% of journalists were fact checking what the AI was telling them, and then 60% of them were finding errors. So again, we've got back into this trust thing around, can I trust the AI that I'm working with?

And so some of these barriers to overcome, if we're really going to embed AI in the way that we're working, are going to be quite significant.

Bruce Daisley (Guest)

Here’s an interesting one for me, I love all of that. And I think what it triggers in me is, we often talk about agents, right? We talk about AI agents. But the idea of agency is going to be more important, full stop. So we've all been the person on the video call who unmutes at the end and says, “nothing from me this week”. We've all been the “nothing from me”. And that speaks to a lack of agency. We've all sat there with, you know, we've maybe been doing emails while the meeting's been going on, and the promise of AI is it's going to be more focussed on everyone is there to make a contribution – agency. Whether it's AI agency or whether it's human agency, getting stuff done.

And it poses really interesting questions about, are our teams set up to do that? Do our teams feel empowered? It's really interesting, there's a piece of work that's been done over the last 30 years, and it asks everyone in the UK workforce whether they think that they've got task discretion at work. Do they feel that they can choose how to do things?

And the figure in the 1990s was two thirds of workers said they had task discretion, they could choose how to do things. The latest number that came out last year, said a third of British workers feel that they've got task discretion. Most of us don't feel like we've got agency in the way we do our work. And in the era of AI - let's presume that the level for knowledge workers is slightly higher than that - but in the age of AI, we need to feel empowered that we can make decisions, take actions, instruct AI, and it does require a rethinking and a reorganisation of how we actually do our work, I think.

Oli Carpenter (Host)

Yeah, it's a fantastic point and it speaks quite strongly to our Deloitte Global Human Capital Trends report, which highlighted that while 88% of organisations have said it's important to orchestrate how people, skills and resources are organised to get that work done, apparently only 7% are making that really good progress towards doing so. So I mean, Kate, what firstly, what do we mean by this?

And I suppose from your perspective, what's the answer to successful human and AI collaboration and AI implementation across firms? What does good look like?

Kate Sweeney (Guest)

What does good look like? I think we're all genuinely exploring that question about what does good look like? I think one of the challenges that businesses are having - which probably is behind some of the statistics - is still tackling that problem in quite a compartmentalised way. We've got IT functions rolling out technology, we've got HR functions thinking about people, we've got finance functions trying to… we’re going to need to join all of that thinking, this is going to be a much more multifaceted problem as we start to engage.

If you just think at the moment about making an investment, we need to hire people. You can understand the costs associated with that. You've got specific roles that you're hiring. Everybody can have a clear picture. Whereas if we move to a world where we've got agents and humans working together, you decide to make an investment, we've got more digital agents responding, and they're going to be working at different times of the day.

The economics of understanding consumption, because AI isn't going to stay - we will have AI agents who will learn and who will adapt and who will evolve - so it's going to be a continuously moving picture. And I think for leadership teams, understanding those dynamics and working out what do we need to be monitoring in the future? What do we need to be looking at?

How do we think about our workforce in a combined way of humans and agents together, and bringing together all of the sort of disciplines who've maybe been quite siloed in the past? I think leading businesses is going to be a different challenge in the future.

Hannah Gowen (Host)

I think that point around silos is really interesting, and it's almost like, yeah, complete rethink of traditional ways of working is needed. Bruce, if businesses purely treat AI as a productivity tool, which I think we're at risk of doing in some cases, are we risking it becoming the opposite of a productivity tool? So something we spend more time using than the benefit it actually delivers, a sort of AI productivity paradox?

Bruce Daisley (Guest)

Yeah, I think there's definitely a risk of that. You know, the interesting thing, an obsession about productivity sometimes can squeeze out some of the things that don't necessarily seem productive but have a real value to them. The obvious one is the connection between people in offices. You know, like interaction between people in offices look superficially unproductive. Actually, it's one of the things that makes us feel empowered, energised, enjoy our work.

You know, the thing I often return to is the biggest predictor of whether we enjoy our jobs and engaged by our jobs is whether we've got a best friend at work. And actually, the numbers of people reporting having a best friend are at the lowest levels ever. Now, if you're obsessed with productivity, you'd see two people standing over by the kitchen having a chat, and you'd think, “come on back to your desks, let's get some work done, let's get some something produced”.

And what you're actually doing is destroying productivity because you're destroying the connection, the engagement that people have got. So yeah, most definitely, we can become obsessed with what seems superficially to be moving us in the right direction. The obvious example is that we've seen firms with AI token targets, and what they found was the AI engineers just started doing irrelevant tasks.

The old adage sometimes called Goodwin's law, any measure that becomes a target ceases to be a good measure. You're told to do something, you achieve that goal, but you didn't actually achieve anything beneficial. And so this is the danger of that, if we're obsessed with productivity, sometimes we can miss the fact that people feeling engaged, empowered, inspired by their jobs isn't necessarily a straight line to productivity.

Kate Sweeney (Guest)

I think that's right. What we're seeing is people doing some knee jerk reactions to AI as well, a retail organisation that we've been working with, they implemented AI in replacement of call centre workers. And actually what they found was immediately they were having lots of problems, call rates were rising, and they're now rehiring and building a hybrid workforce that's bringing together their agents and teams.

So again, their immediate thought around AI is a cost saver has actually been shifted. We need AI to be a competitive advantage. We need to be able to be using AI to drive better customer service. But they're having to reframe and really rethink through that question about how are we defining value broader than just cost saving?

Oli Carpenter (Host)

And to build on that Kate, how are some organisations tackling that? Because, Bruce, you very rightly pointed out that the danger of this AI implementation at such a large scale is that it can dilute the culture of an organisation - and ultimately you don't want to be losing those watercooler moments, do you? So are there ways that organisations are tackling that culturally Kate?

Kate Sweeney (Guest)

I'm seeing the best organisations are holding on to their culture and are framing this whole change as, “how do we enhance what's brilliant about us as an organisation now?” and being very deliberate. And I think where organisations are struggling is where they're not giving it any thought, where they're seeing this as a sort of a technology implementation, a technology replacement, rather than “how do we augment our organisation?”

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Hannah Gowen (Host)

We talked a lot about what's not working and the challenges that business are facing, but what does it look like when organisations do get it right? So what examples - perhaps Bruce we’ll start with you - have you seen where firms, businesses, have got it right in how they work with AI and what are the characteristics that stand out most of that best practice?

Bruce Daisley (Guest)

Yeah, I was chatting to one retail firm -and the retail firm was a marketing, sort of branding department - and the woman leading it, she told me, she's just tried to build it into the muscle memory of her team. That before anyone brings anything to group consideration - she was giving me an example of a buyer's guide for a certain product - the first thing she said is, “well, where are you on the drafting process of this?

Did you use AI first? Then did you improve what the AI did? Is that what I'm reading?” and she tried to build it into their processes. Or I saw something where a few of the fashion retailers have started experimenting with AI models. And the interesting thing for them is that - I think knowing that this is a bit of a tinderbox of potential consumer backlash - they've been paying the models the normal going rate, so every time that the model is reused, they earn the same fee, but it reduces some of the costs of photography and staging.

And I guess both of those give you a sense of, neither of these are the finished article of probably where they'll end up in three or four years, but they’re experiments. And for me, it's those little bits of experimentation where people are saying, “look, we don't know what this will look like in three years, but in six months we'll know a whole lot more about what our next experiment is going to be based on the fact that we've done these ones”. Because I've also worked with other organisations and they've told me - the old adage used to be beware the busy manager, right?

You know, we're all busy. And it's true, when you're busy and someone says, “by the way, have you used AI this week?” You're like, “where, where, how, how, when am I meant to do that?” And actually having the ability to think, look, using AI this week might just be a 30-minute experiment, that in a team meeting together you talk about what you've done and what you've tried.

I think that spirit of experimentation is probably the secret.

Oli Carpenter (Host)

Kate, you mentioned trust earlier, obviously a really important part of making sure what you get out of AI is accurate and that we can rely on that. With that in mind, do you think organisations are experimenting enough? Are they using AI to test new ways of working, or do you think there's more that can be done?

Kate Sweeney (Guest)

I think the organisations that are winning are absolutely experimenting in exactly the sort of way that Bruce was talking about, and I think everybody needs to be thinking about how they can experiment. But I would say there's lots of experimenting, but one of the challenges I think will have is if organisations aren't doing it deliberately - a bit like Bruce, you were saying earlier on about deciding what your voice is going to be with your customers -I think there is something about the risk we have a little with AI is we're back to the world, where everybody has their own spreadsheet. With AI, with too much experimentation, the risk is we've got everything out there. So how do you, yes experiment, but then orchestrate that as well? How do you make sure you're sharing learnings very rapidly across the organisation?

How are you working out which of those experiments work? Binning some of them accelerating others. So there's got to be an orchestration layer across the experimentation I think to really get the benefits.

Oli Carpenter (Host)

Fundamentally, I suppose, it is reimagining work almost in its entirety to make sure that AI is working for them, not just with them. Is that right?

Kate Sweeney (Guest)

Yeah, absolutely, if we think about how again - I think most people haven't really reimagined work for a very long time - we think about when big tech's happened before, the big ERPs came in and the questions you were asking, the businesses were asking at the time, it was either, “am I going to follow the processes that the technology lays out, or am I going to force customisations? Because what we've done for years needs to be inflicted on the technology”.

And that was the kind of dynamic that people were thinking about. And now I think we can ask a completely different question, which is: what work do we need to be done and what do we want agents to be doing? And if we're going to get agents to do that work, what's the role of the human? What are the decisions that we don't want, will never be delegated to an agent? What are the controls that we need to put in place to make sure we still feel accountable for the agents?

I mean, we know there are examples now of people who are getting fined and are being held liable because their agents are giving incorrect information. What does it look like to be a manager in a world where you're managing in that kind of an environment? So I think there are some big-ticket questions organisations are going to need to lean into around this.

Hannah Gowen (Host)

And we've mentioned the T word there, which is trust. I think that's such a big theme, isn't it, with AI and how we're all - businesses, consumers, individuals - grappling with this new technology. Our next episode will explore the link between trust and AI, but how do you balance that trust alongside widespread change implementation? How do businesses and individuals adapt to that change? What has to change first, and how do you bring the people along? Because ultimately the people are at the heart of that, Bruce we’ll start with you.

Bruce Daisley (Guest)

The New York Times did an article about six months ago, which was, 22 new jobs that AI will invent - and I guess it's in the spirit of the fact that, you know, we might know people who work in search engine optimisation, a job that didn't exist 20 years ago, or the YouTube creators that didn't exist 20 years ago, what will be the new jobs? And the theme that really came out through those new jobs was trust – so who's the person who's on the hook for what the AI has created? Who's the person who's thought about the tone of voice of what the AI has created?

And it just reminds you that we've seen a couple of court cases where people have turned up - there was a case in Australia where something happened, there was a case in America where something happened - where a report has turned up, and actually the AI had maybe gone too far. And what you find is that actually that trust is all about humans. Who's going to vouch for what the humans have created? So that's why your journalists point is such a good one, because it's down ultimately to the journalist to go and check those links, to go and check those things, because I don't think most of us will accept an excuse that the computer did it.

You know, most of us won't accept that, we want a human to vouch for those things.

Kate Sweeney (Guest)

And part of - I think when we were talking about that sort of organisations thinking strategically about what they want to do with AI, what their customer voice might be - part of that is also going to be about what is the trust that we are going to build in by design, whenever we do anything with AI? So what's the transparency we're going to build in? What's the traceability? How are we going to monitor and govern AI going forward?  And I think for people using it, understanding that is going to be really important.

But then also we need to keep working on AI. And I think if you think culturally about different people, it's got to look different. So we've been working with some sales teams and sales teams are notorious for, well, if it doesn't work the first time, I'll never go back because I'm so quick and I'm so speedy. So getting them to realise that actually it's never going to work the first time because you haven't taught it yet, you haven't spent time. How do you think about the AI, not as a tool that hasn't worked, but actually as a new person who joined your team, who you need to give prior examples to and context to, and all of those sorts of things?

So different groups of people are going to need to go on their own journey based on the culture of how they work now. And we can't expect everybody to adopt in the same way.

Oli Carpenter (Host)

That's a very good point, Kate, because I suppose ultimately, when an organisation is going through a huge change where they're implementing AI, that pace of change is only ever going to be as quick as the slowest team, if that makes sense, right?

Kate Sweeney (Guest)

Absolutely. I think everybody's framing AI as a tech problem, whereas actually it is a people and an organisation and an adoption and a culture and a trust issue. And if we look at the way investment’s happening - at the moment, we're finding that kind of 90%+ of investment in AI is in the tech and 9% in all the human engagement activities.

And everything that we have been talking about on this conversation has been about the human engagement and the way businesses are going to work. I think we really need to see that, a shift in where the investment and the time and the thinking is going.

Hannah Gowen (Host)

And if there is that sort of level of investment across the board, we're all trying to do the same thing - we touched on that a bit earlier - if everyone's trying to do the same thing, you might end up with the same product. So, how do businesses stand out in this sort of AI race when we've got a new baseline almost for what normal is, what makes a business better?

Bruce Daisley (Guest)

I would personally say that creating space for these discussions is quite important, and for me, that requires a little step back. I've worked with a lot of organisations and the way that most people are experiencing work right now - back to the busy manager thing - is that the level of work intensity is incredibly high. People are in back-to-back meetings, they feel overwhelmed.

And all I would say is that, typically when we look at creative businesses or businesses that are innovative, the one thing that they describe when they take you through their working week is a set time aside for innovation. They set time aside for creativity. And so the only thing I would say is that setting time aside for discussions about how you're all using AI, or I love the metaphor of not all having your own spreadsheet, but more, can we all agree, once every month, we're going to get together and discuss what everyone has experimented with? And look, it might be something they experimented with in a personal capacity which has got applications for work. I've really enjoyed watching YouTube clips about prompt engineering, about learning how to use tools better, and I just think unless we're bringing the currency of conversation, of discussing what we're all doing, then we're kind of bringing our own spreadsheet to the situation, and none of us are learning.

Oli Carpenter (Host)

Well, as we come to a close, it'd be good to start thinking about some of the takeaway advice that we can give to our listeners. And Kate, if I turn to you first, what are some of those first real, crucial key steps that leaders should be taking to help set their firm apart when it comes to AI usage?

Kate Sweeney (Guest)

So I’d probably say two things. I think one, absolutely, as we've been talking about a lot, is really thinking strategically about what they want AI for and how they want to stand out in an AI era. And the second thing I would say is role model. It is very, very clear that AI adoption is happening where it's being role modelled by leaders.

And I think leaders have to be really brave and start experimenting themselves and finding ways to fit it into their 30-minutes a day, because they have to lead from the front in this space.

Hannah Gowen (Host)

And on the culture point, Bruce, how do firms ensure that new AI tools that they're building into their workplaces become part of the culture, too, and not force change upon the workforce as if it's the usual IT update?

Bruce Daisley (Guest)

I think there's an interesting challenge for all of us, trying to come to the decision together about what we want to be famous for, what we want our team to be known for, what are the standards that we hold ourselves accountable to? Because I think, quite often, the group that we're part of have got strong opinions on that.

You know, they've got strong feelings about, “this is what sets our work apart” - maybe from the competition, maybe from what we did in the past. And that, I think, in the context of AI, can help us think about, what are the things we want AI to help us achieve? What were the things that we want AI to help us sustain actually?

And so just thinking about who we are and what we do can be an important part of setting us up for success in this new era.

Oli Carpenter (Host)

You shouldn't let AI dilute your brand or differentiate who you are with what you're trying to deliver I suppose.

Bruce Daisley (Guest)

I think that's it. Quite often our brand, it lives as much in our hearts as in the overt logo and things like that. It's about when someone comes to work for your organisation, what do you tell them that this organisation is famous for? What do we care about here? Because most of us know that, maybe instinctively.

But the more you can bake that into your plan, the more that you can say, “well actually, that's what we're famous for, but we want to make sure that we're even more famous for it next year”. And I think that context is really important in an era of technology. The people part - back to what Kate has said and what we've all agreed - the people part can easily be seen as a side issue, whereas in fact it's the real differentiator going forwards.

Oli Carpenter (Host)

And finally, we always bring it back to our big question. So, Kate, if I come to you first, are we planning enough for AI?

Kate Sweeney (Guest)

Well, the one-word answer would be, collectively, no, I don't think we are. I think we are a little bit the kids with the new toy, and it's really exciting. And I think we need to step back and plan ahead and tackle some of the questions that we've been talking about this morning.

Oli Carpenter (Host)

Thank you. And Bruce?

Bruce Daisley (Guest)

I would agree, no is the answer. Look, it's daunting, isn't it? You know, whether it's young kids booing speakers at university graduations, you’re witnessing a lot of uncertainty and anxiety, people are a little bit scared. It's like you hear 50% of jobs might go and you “think, okay, as long as it's not me, I'm okay”. And I think that fearfulness is preventing us having conversations about what do we want to be if this works out well? Where do we want it to take us?

And I don't think we're having those discussions, and I think even just having conversations about, if we want this technology to help us, how will it help us? That can help us at least move in the right direction, I think.

Oli Carpenter (Host)

It feels like we're on the precipice of something very exciting, but also quite daunting at the same time. But well, it's been an absolutely brilliant discussion with you both. Great insights, great energy, have loved the discussion. Bruce. Kate, thank you so much for joining us in The Green Room.

Both Guests

Thank you, thank you.

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Oli Carpenter (Host)

Thanks for listening to this episode of The Green Room by Deloitte.

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This podcast is produced by our very own pod squad. Original music by Ali Barrett.

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