#102: How do we turn AI ambition into a national advantage?

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Steph Dobbs (Host)

The AI race is on. But what does it take not just to keep up - but to win? Turning AI into real economic growth means building the right foundations, from skills and infrastructure to regulation and investment. So how do we turn an appealing vision of the future into a reality?

Today we ask the big question: How do we turn AI ambition into a national advantage?

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Sharon Hague (Guest)

The big tension point is how do we get people and the technology working together in a way that actually takes things forward?

Oliver Seal (Guest)

We have that responsibility as individuals and as businesses to really start on that journey today.

Sharon Hague (Guest)

One of the key skills that we are all going to need is the skill to learn, because we're going to have to keep relearning.

Oliver Seal (Guest)

Fortunately, I think in the UK we're probably over indexed on professional scepticism compared with elsewhere. So hopefully that might be a national advantage for us!

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Steph Dobbs (Host)

Hello and welcome to The Green Room by Deloitte. I'm Steph Dobbs and today I'm joined by a new addition to our hosting team, the wonderful Hannah Gowen. Welcome to the team Hannah. How are you feeling?

Hannah Gowen (Host)

Very well thank you. I'm excited to be here.

Steph Dobbs (Host)

We're very excited to have you here. So for over the past few episodes, we've been exploring how AI is changing the world of work and why people need to be at the heart of business thinking when it comes to big technological change. But AI isn't just about a business challenge, it's also a national one. So what does it look like to take the lead rather than merely participate in the AI race?

And how can the UK turn the strategic vision behind the government's AI ambition into tangible achievements and lasting success that all of us can benefit from? What will make the difference in a country unlocking the benefits that AI brings rather than being left behind? So today we're answering the big question: How do we turn AI ambition into a national advantage?

Hannah Gowen (Host)

And to answer that question, today we are joined by Sharon Hague, who is the CEO of Pearson in the UK. Welcome, Sharon.

Sharon Hague (Guest)

Thank you.

Hannah Gowen (Host)

And also Oliver Seal, who is a partner at Deloitte and leads the firm's digital education practice. Welcome.

Oliver Seal (Guest)

Thank you.

Hannah Gowen (Host)

So over the last year we've seen a big surge in the conversation around AI. It's been unavoidable and we're now looking at it on a national scale. So it'll be interesting to hear, kind of, what you think are the key developments, both kind of technological, economic or geopolitical.

Sharon Hague (Guest)

I think firstly, to say, I think it's absolutely right for the UK to set really clear ambitions to lead in AI. This technology is rapidly transforming many aspects of our lives, will continue to do that and continue to do that at pace. So, I do feel embracing the technology and aiming to be a leader is absolutely the right thing to do.

And of course, here in the UK, you know, businesses, the economy as a whole. We need and want to see growth. There's a lot of government energy focussed on how can we achieve growth? And AI if adopted well, at scale, has the potential to help us all unlock that growth, which will obviously be a huge benefit to the country as a whole.

Pearson, we've been sort of tracking this technology over the last couple of years, and I was lucky enough to attend Davos earlier this year. And what I heard there is the conversation has moved over the last two or three years from being really about the technology itself, but now the conversation is becoming more nuanced and there's recognition that actually to really make the most of this technology is a core business and leadership issue. And I think here in the UK, we have many of the strong foundations to make this a success for the economy as a whole. But we're really at a key sort of inflection point. So now is really the moment to focus on how we can move from seeing the potential to really delivering that at scale.

And of course, you know, the big tension point is how do we get people and the technology working together in a way that actually takes things forward?

Hannah Gowen (Host)

Yeah, and I think you've kind of touched on there, Sharon, around how businesses are trying to navigate this and figure out how it works in practice. So, Oli, how do you think in your role you've seen businesses implement and their attitudes change, perhaps over the last year or so, and how is that impacting their strategic priorities and investment decisions?

Oliver Seal (Guest)

Yeah, if I could answer that with a bit of a story actually. So we responded to a tender with one university - I worked mostly with universities in our wonderful higher education sector in the UK - and they wanted a CRM. And in the tender exercise, AI was mentioned but there were no direct use cases for it. So in the first phase of that, which was over three months, we did deploy some of the foundational work for that and the data. And whilst we did that, we had to knock down some barriers around AI. Around making sure their general counsel was comfortable with our AI terms and conditions as an example, and that they were picking the right use cases that were ethical and right for them and would be there.

Second phase, three months later, we’re there deploying those first use cases. They were meant to be proof of concepts, but those proof of concepts very quickly moved to being in live use.

So we went live a week ago. The pace has started to really pick up now, they're talking to me and they're going: “Oli, I don't want you to be picking AI use cases. I want every use case to consider AI, just like we consider any other technology and anything else.” And now they're talking about: “right actually, we need to really start thinking about reimagining the way we do business, the way we answer student inquiries, the way we do student case management, the way we pick up welfare issues, the way we enhance student learning opportunities. But we really need to think about what that does to our business model.” So it is, that's… we've not even been working with them for a year, and this has all happened there.

Whereas actually I think two years ago, yes, there was predictive analytics. Yes, there was machine learning. There's been that for years. But that is the pace that people are picking this up with now, I think.

Steph Dobbs (Host)

And you allude to it there, but I guess that piece around the rapid development of the technology that's going on, it's obviously shifting alongside geopolitical factors and the competition from other countries as well. And Sharon, you alluded to it, but we're at a critical juncture when it comes to this, aren't we?

Sharon Hague (Guest)

You've got the technology rapidly developing. You hear so many stories of people that get themselves familiar with a tool, and then they go back two weeks later and it can do something it couldn't do when they first started. So the pace is incredible. And what we're really seeing is this growing gap between the pace at which the technology is moving and then the pace at which people can keep up.

Which not only requires businesses and organisations to really rethink how they are structuring the work, it's also rethinking completely how they keep their workforce skilled, how they retrain people, how they upskill them. Because I think when this technology started to emerge, there was very much a focus on, we're going to recruit people with these new skills, you know, we're going to recruit 100 data scientists, and we're going to do… but of course, that can't possibly keep pace with the rate at which the technology is developing.

And the key to success is how you get the people and the technology working together. So you've not got one replacing the other. You're actually using the technology to really augment what people can do.

And I think that's why it's a pivotal point, because this realisation is happening that actually this isn't just a sort of swap some stuff out and everything else settles back in place. It's a really, fundamentally rethinking how you shape roles, how you train and skill people, and also the skills that people need are fundamentally changing. So, you know, I've had quite a few conversations actually in the last few weeks where people, you know, we're all quite rightly concerned about early careers and people at various organisations have said: “yeah, but all the work that the early careers people have done in the past has gone, you know, and, you know, it takes you years to develop how to say, make decisions.” But for me, what that actually means is, yes, some of the work that we've typically given employees to do has gone.

But then decision making and making huge decisions isn't something that you suddenly acquire when you've got 20 years’ experience. You make lots of small micro decisions, so you've actually got to think of that, okay, that's a skill that early careers people need, and how do we develop that?

Oliver Seal (Guest)

If I can build on that actually. I get really upset and quite annoyed when I hear that people who come from school or from graduates, their jobs aren't there. Actually, the evidence isn't there for that, I don't think. I joined Deloitte as a graduate in 2006, which ages me a little.

Steph Dobbs (Host)

You're showing off.

Oliver Seal (Guest)

And I was a teacher before then, and I actually found the first roles that I got given were boring. They were reformatting PowerPoints, they were checking other people's work, they were checking the numbers in Excel spreadsheets. And I did that for six months. That didn't teach me the things I needed, how to facilitate a workshop, or how to make decisions or how to articulate a client’s needs.

I mean, I'm really pleased that in my projects I've got six early career people, I've got two degree apprenticeship people in my projects, and I've got four graduates and they're all doing spectacularly well. They've all already come equipped from their courses, either at school, from their personal life or from their university education, with the ability to use AI in a much more advanced way, I have to say than me, I'm catching up. But what they've got is they've got ability to take on knowledge. They've got critical thinking.

You know, I was talking to one person who was a history graduate, history gets a lot of kicking unfairly I think, I'm a physicist, but history gets a lot of kicking. One of the things that history teaches you is to evaluate sources and to show empathy with those sources, to look for gaps for other evidence that might be missing in the evidential trail. These are all skills I need in a digital transformation. I need people who can take in a lot of information, can evaluate that information, and then use AI tools to evaluate those sources and check those back.

And actually, I found that AI source, AI technology can be - with the right training and skills applied and the right safeguards put in place - accelerators for early years talent and make them more effective, more quickly. So hopefully this is an optimistic message for people currently studying in in either school or in graduate for good degrees.

Sharon Hague (Guest)

I was a geography teacher and I did learn to do more than just colouring maps, but…

Oliver Seal (Guest)

I loved Geography.

Steph Dobbs (Host)

I was a history graduate as well, so I agree with you.

Oliver Seal (Guest)

I mean, I'm in a good place here.

Hannah Gowen (Host)

Sharon, Pearson, like you say, are working with various companies as well as individuals to help deliver AI skills training. So what do you think are the benefits for wider society as well as our economy in terms of the UK achieving its AI ambition?

Sharon Hague (Guest)

For me, if we can deploy AI technology well, we can free capacity. We can free people from doing tasks that don't actually contribute to new business innovation, new ideas, growth opportunities. You know, focusing on really, I mean so many businesses are in a tension aren't they, where they've got their kind of business as usual, they can see new business opportunities, but how do they create the space to really focus on the growth? So this could be a tool that could really help with that.

I think the UK has some tremendous strengths. You know, you've talked about higher education, our reputation internationally, international research, education – the UK is very, very highly valued. There's a real opportunity for us to lead in this field, which is something that is going to continue to be an area of focus, attention and growth into the future. So I think there's huge benefits from a national scale.

We, at Pearson, we've also done quite a bit of research. We were looking at productivity in the UK, and one of the areas that we identified is sort of transition points. So when you're transitioning from education into work, when you're transitioning perhaps because your job has significantly changed, perhaps you've been made redundant, perhaps you get to a point in your career, and you want to change direction. All of these transition points, there's often a pause or a gap.

You know, I've got a young person at home who's many of their friends, you know, it's taken them a year, 18 months from university to actually get employment. So, you know, that's a huge loss of productivity. So really, you know, if we can help leverage the technology, if we can think about how we reskill and retrain people more quickly, there's an opportunity just in reducing those transition points alone to add nearly £100 billion to the UK economy, which is about 5% of GDP. And that's just one example of how we could leverage AI to really help transform the UK growth trajectory and economy.

Oliver Seal (Guest)

I think that's really important. I think there is enormous opportunity to grow the economy, but that growth has to be inclusive. I think every industrial revolution to date has, in the end, created more jobs than before the industrial revolution. Whether you go back to the initial ones in the 1700s, all the way up to the internet revolution that we've just lived through.

The AI revolution, I think, will be no different in that, the danger we have is that we create a core of long term unemployed out the back of those - so who are those people left behind? So I think people working in education, such as Pearson and my clients, need to be able to respond to that, I think. It's very important that we think as a nation, maybe with government, down to individuals, but also businesses taking that responsibility for thinking about how we look out for those people who are going to fall through the gaps and how off the back of that we support them, benefit as well from this revolution, and we don't let them get left behind.

Steph Dobbs (Host)

So I suppose as part of that, then let's try and think about how we can build some of the foundations to realise on some of these ambitions that we're talking about. So what fundamental foundations are needed if we're going to build to make sure that the UK is actually ready for an AI driven future? Sharon, let's maybe start with you, you've already talked about the investment in technology that's needed - you know, there's things like computer capacity that will be needed, advanced data systems, infrastructure - but of course we need to match the investment with skills. Why is the match needed between skills and the technology?

Sharon Hague (Guest)

Well the skills are absolutely fundamental to realising the benefit and making sure that, you know, people have the skills they need to work in reshaped roles or to use the technology and apply it. So it's absolutely critical and one of the - you know, we've done quite a significant amount of research - and one of the conclusions that we've come to is that, you know, the technology is moving so fast, it's going to continue to move quickly over, you know, people's careers, individual’s careers, so one of the key skills that we are all going to need is the skill to learn, because we're going to have to keep relearning. It's not going to be like – well, you know - we left university and you kind of think, ‘oh, thank God, no more learning, I can just work now!’ You know, we're going to have to keep adapting to new technology and the ways in which technology is changing. So, for me, this kind of, you know, really is a fundamental shift across all ages and stages and partly how we make sure that people are real kind of lifelong learners.

Hannah Gowen (Host)

What do we think are the first steps that we need to see education providers specifically take in order to integrate AI into learning, to prepare students and a new generation of students who are entering an AI powered world? What needs to change in terms of preparing these young people for the future?

Oliver Seal (Guest)

So it’s sort of four levels, I think, of development that I'm seeing in my clients. So, I think led a little bit from the fear of screens and some of the damage that that might be doing to our young people, I think there is one layer of layer that it should still really be paper and pen, and we should stick with that. So that's sort of the avoider layer, I think I call it the ostrich layer. There is some value in some of that, I think.

The second layer is one where maybe you're sticking with the traditional ways of learning, but adding some AI specific modules. AI is something that's done over there. We set it aside and we do a module on it, now that has power and it has benefit. More progressively perhaps is, for example, University of Surrey have announced recently they've redesigned their courses to build AI into every course.

So I think they gave the example of, in politics, they're using ChatGPT to look at some electoral results for politics students. And then the actual exam is to then critique the output of the AI, to really come back with a balanced view on that. And then there's the sort of fourth model, which is to reimagine education entirely and maybe start AI led. So you almost think of the AI tutor as the first point, and then the humans are almost managing the AI interactions with those.

That's quite rare at the moment. I think the second and third model is probably where most places are in. And it's hard to say exactly where the right balance is, and I wonder whether it's not a one size fits all. It will depend on which age group you’re teaching, what you're trying to teach, and the personal learning styles of the individuals who are being taught.

And it's probably a bit of a mixed bag, but interested in…

Sharon Hague (Guest)

Yeah, it's really interesting the way you categorise it. I think it does very much vary by age and stage, because I think there's a lot of evidence to suggest that particularly young children do need that sort of physical manipulation. They need to learn to write with pens. So I think it will evolve or look different at each stage of education.

I think that the digital divide and equal accessibility has been a very key factor in the UK in thinking about how technology is used, particularly in schools, because I think it's an important principle that we want children as much as possible to have equal access and to have the same opportunities when it comes to devices. So I think that's part of some of why there's been a lot of debate about how to actually implement it. But I think it's really interesting to see the government is now sort of embracing it and there's some interesting initiatives that they're undertaking around how can they make things like AI tutors widely available, the things that they've been doing to make easy access to materials for teachers because, of course, time saving for teachers and then enabling them to spend more time with students is something that can add a real value, particularly at school age education. So I think there are definitely lots of opportunities there.

And it's going to be a slow journey because, you know, you've got to do your best to make sure that that's 100% effective for young people because they only get that one chance to go through their education.

Steph Dobbs (Host)

What about sort of bridging that gap between whether it's leaving school, whether it's leaving university or higher education through to business? Oli, what role do you think the business themselves have to play in bridging that gap between the two?

Oliver Seal (Guest)

I know that universities are really trying to reach out more and more to employers to really understand the daily lives that employees of their businesses are really facing, to try and make sure that they're matching the skills that you're learning within that degree course to that. So I think for businesses, I think being open with the skills that you're really needing and thinking critically about where the gaps are. And then reaching out to whether it be in the public sector such as universities and private sector, such as businesses like Pearson, really engaging in that debate and not thinking you're alone in that. So I would encourage all business to engage with that and really experiment, push the boundaries and engage with that ecosystem that we are a market leader in, in this country.

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Hannah Gowen (Host)

We heard on a previous episode in this series that “the pace of change is faster than ever before, and probably not going to slow down”, and we touch on how businesses are having to adapt at pace to figure out how to upskill their own workforce and transform in line with AI and keep that pace.

So what have we learned about effective skills development through AI and workforce transformation that can be applied as just a general learning across the economy?

Sharon Hague (Guest)

One of the things that we have found through our research and working with many organisations is that the old models of training and learning skills for the workplace - where perhaps a new platform or system’s introduced, and then you have this announcement, and then every single person in the organisation is sent off on a training course - that model is just no longer going to really be relevant or apply in a world where technology and AI is moving so rapidly. So, you know, what we're seeing is - and working with companies to do - is identify how that skilling and training can actually happen in the flow of work so that as things change and evolve, you're learning through doing while you work. Because of course, when you go off on a training course, you know, we've all been on these amazing training courses, come back and think: “oh yeah, I'm going to completely change how I do that.” And then of course, you get sucked into all your emails and everything else that's piled up while you're away and you've completely forgotten most of it. You know, you've forgotten half of it within two days of being back in the office.

And with the technology changing so rapidly, you can imagine, if you're in a huge organisation – like you know, Pearson or Deloitte - by the time you’ve trained everyone the technology has moved on and half of what's been learned is irrelevant. So, we have been working with businesses to develop tools where you can actually sort of upskill as you're working. We've been working with Microsoft, for example, on a communications tool that helps people develop their communication skills as they work. So it will listen to, you know, if you're on a Teams meeting, it’ll listen to your inputs in the Teams meeting and then analyse your contributions and then give you feedback on the professional skills that you demonstrated in the meeting.

So perhaps your vocabulary, your expression, whether you were persuasive, how you could have taken your communication to the next level to actually have an impact. And so you get that feedback immediately or within a few minutes of the call having happened. It's encouraging but gives you specific points for improvement, links out to learning activities that you can then perhaps practice with an AI tutor. You know, being persuasive and perhaps changing how you made a particular point.

And then you can carry on with your work and you can apply those skills that you've learned in the moment. You know, think about performance reviews, where you get to the end of a quarter, and you're trying to think back of everything that you've done and where you might - you know, if that's happening throughout the flow of work, that will make a huge difference to how quickly and effectively upskilling happens. And I suppose taking that out then to what does that mean for all of us? It's back to this willingness and having that skill of learning and applying learning and willingness to learn and recognising that that is a skill that we're going to need to continuously apply throughout our careers.

Steph Dobbs (Host)

Definitely. I suppose inclusion’s such an important part of this as well, isn't it? Because the really important part of if we're going to achieve our AI ambitions is to make sure that everyone's actually included in that journey, so it doesn't matter which generation you're from, different backgrounds, different skill sets, etc., how do we actually make sure it's fair and accessible for everyone Oli, when it comes to the opportunity there is to benefit from AI?

Oliver Seal (Guest)

So some AI I think is already beneficial to people like me who are dyslexic. So I really benefit from the ability to have software that can transcribe and summarise what I say, and therefore speed up drafting of that first email, that first word document. I'm lucky because I have that software provided by Deloitte. And you're absolutely right, I think there's a really important role for businesses, at all levels, to engage in that - from an SME level to sole traders to large businesses, such as Deloitte or Pearson – on thinking how to engage with the community to bring that in, but also with governments.

So I think where government can play a role is to make sure that any economic benefits that come off the back of AI are shared fairly and appropriately with people, so they are not left behind and can benefit from that as well. There is obviously SEND - special educational needs - really is a big agenda at the moment, and I think real innovation and investigation into how - not just for Dyslexia, but for all types of special educational needs - different technologies can be deployed to really support that and bring people with those needs into the workforce. And they already play a very productive role in society. But to really enhance that going forward, I think.

Hannah Gowen (Host)

I think you've both sort of touched on at various points during the conversation about the role that the government has to play. And you may be familiar with the AI growth zones, which is a government initiative which is set to create areas where investment can happen more quickly. There's loads of elements at play in order for us to reach this national ambition. So whether that's grid connections to power, the technology - as we've touched on - bringing down energy costs, reducing planning barriers, and as we've touched on throughout the conversation, having the AI ready workforce.

Oli, what do you think policy plays in terms of its role in ensuring that fair access, that inclusive access to AI's benefits and preventing that digital divide?

Oliver Seal (Guest)

Firstly, I'm not a policy expert - I work mostly with universities - but I do have a view. I think it's really about - there are some small, not so sexy changes that government can make, and are making I think, but I'd encourage them to do it and do it quicker perhaps. Around making sure that our large amounts of financial support, that is available in the UK, can be easily directed - so UK money - can be easily directed to that problem and those growth zones. We've got a fantastic financial services sector, how can we change the way they work?

Maybe at quite a small level, the pensions schemes and etc. to invest in AI, to really pump prime that growth so that the the AI benefits from the great skills that we're going to build here, aren't then lost to the Singapore underground I think is a big investor in AI, for example. So I think that's one change. I do think there's a great opportunity to kind of combine the inclusion and the way that we think about where that investment happens.

And I think, again, this is already happening. So the northeast of England and Scotland, for example, are already areas where there is an opportunity for greater economic growth and more investment. They're also areas that have got huge amounts of power and untapped energy. And I think, thinking about where we invest in that and then for the - either again - the public sector and private sector to make sure the skills are then in those places.

And I know the universities in both those areas really think about hydrogen and wind power, for example, and how those complementary skills are being developed. I think it's really important.

Hannah Gowen (Host)

And you've touched on a point I just want to pull on there, as a Brummie, very keen to talk about what this kind of upskilling and development looks like outside of London. Obviously in a lot of these business-based conversations, there is a London focus. So, Sharon, perhaps for you, how important is it actually that these regional skills and people outside of the other big cities have access to that skills - and that development - opportunity?

Sharon Hague (Guest)

Yeah, absolutely. Because I think there is the potential, isn't there, that you perhaps have - it could be regional or it could be a divide between very large companies and small and medium sized enterprises. So it's incredibly important that we work collectively to make sure that those opportunities aren't concentrated in only certain types of organisations, benefitting - or in certain parts of the country. And I think you've touched on some of the policy around, how directing of investment and so on to different regions and support of industry in different regions.

But I think, you know, UK companies as a whole, there is a big opportunity for encouraging - public private partnership can be a really good way to help spread the opportunity. I think UK companies actually invest far less in training and learning in their organisations than, for example, European counterparts. So creating incentives for companies of all sizes to invest more. You know, the government has been doing a lot to create more vocational and technical pathways through education and much of that - to the ability for that in different parts of the country to reflect the jobs that actually exist in that area, rather than it being, you know, training lots of young people for a particular pathway where actually there aren't any jobs in that region.

So I think that's going to be really positive. And then, you know, I think there are also things that, from a policy perspective, can be done to encourage large companies through their supply chains to actually help with that kind of upskilling and making sure that many organisations of different sizes, through the supply chain, benefit from some of these developments.

Steph Dobbs (Host)

So let's maybe move to think about the future, moving forward and how best we can all prepare for it. Because I think the benefits of national AI usage, of course, sound great, and it's something we've been discussing a lot in this series so far. But this isn't, of course, just about technology. It's also about how we can set it up so that we can all actually benefit from it.

So what are some of the biggest hurdles that the country is facing when it comes to the AI race? Oli, let’s start with you, how can we as a country prepare for some of these hurdles?

Oliver Seal (Guest)

I think one of the biggest hurdles is that, as a country, I feel like we've lost our mojo a bit. And so I think one of them is about confidence. And as Sharon puts it, really making sure we then back that confidence with investment around digital skills. I think there's a bit of a feeling that we are expecting government to do it for us, and I think we need to - both at an individual level and a business level, and in a business ecosystem - think about how we can work first, then move to hit those barriers.

There are obviously some really important barriers that need to be overcome at a national level as well. We need to make sure there are enough AI tokens to do what we need to do. We need to make sure that there is the suitable, reliable power that's behind that. We need to make sure that we're building on our really good value systems and our respect for the rule of law, and therefore building the trust that is going to be really important for this technology to take off.

The data is held securely, we're maintaining appropriate levels of sovereignty, for example. So I think they're the barriers - ones we can tackle ourselves. And I think again, the government is doing a lot here, but I don't think we should wait for the government to do it. We have that responsibility as individuals and as businesses to really start on that journey today.

Hannah Gowen (Host)

And you've just touched on a keyword there being trust, which is a theme that we're going to explore a little bit further down the line in a future episode in this series. But what role does trust really play in this AI ambition, and how do businesses tap into that and make sure people feel that they can trust the technology that perhaps is new to them, when they're not sure how it will affect their opportunities in the future?

Oliver Seal (Guest)

We've got Pearson here, and one of the things that I really think there's a big role for all education institutions, teachers, colleges and universities, but also publishers. And I know that's not maybe the core business anymore, but publishers have editors and they curate information and I think that's still important. I think AI will generate information, content, but you still need those sources that are trusted at the core of those. So I think from an information trust perspective, we've still got to look up at the brand.

But then those brands then need to put in really strong governance to make sure what they are putting out is trustable and is high quality.

Sharon Hague (Guest)

I'll tell you a little story. I went into a school recently and did a presentation to some sixth formers and I thought, oh, I'll talk about, you know, AI, how it's reshaping the world of work. And one of the pupils put their hand up and said, we know that our teachers are using AI to generate some of our work for our lessons. How can we be sure that the quality isn't going to deteriorate?

Oliver Seal (Guest)

They should be on this podcast.

Sharon Hague (Guest)

And I just, firstly, I was slightly gobsmacked If I'm honest by the question. But I thought that is incredible. You know, you've got a 17-year-old sitting there thinking, “actually, I can tell my teacher is using AI to generate some of the work for my lesson. How can I be sure this is good enough for me to actually meet my ambitions?

You know, I want to go to X University and I need to get this grade. I need to make sure I've got the quality of teaching that I deserve.” So I think that is just a fantastic example of how important trust is - that we imagine it's just big organisations maybe thinking about trust, but actually it permeates right the way through society.

Oliver Seal (Guest)

It's a great example again, though, that the 17-year-old is more AI native than we are, so it's really refreshing to hear they're putting forward their kind of professional scepticism into that. So trust is important, but you do need to balance it with kind of a professional scepticism. And I think we've got to get that balance right. Fortunately, I think in the UK we're probably over indexed on professional scepticism compared with elsewhere.

So hopefully that might be a national advantage for us!

Steph Dobbs (Host)

I suppose it also emphasises the fact that it needs to be sustainable. Whatever changes happen down the line, as the 17-year-olds show us, you know, this isn't something that can suddenly be changed and we're all fine. Whatever national approach we end up taking, it has to be sustainable over a period of time. Are there any advantages we can sort of gain, I suppose, from looking at things from a sustainable approach, Sharon?

Sharon Hague (Guest)

Yeah, I mean, I think it has to be sustainable because if it's a business - adopting AI in a way that isn't going to deliver the outcomes for that business is not going to be something that's going to be successful in the long term. So I think that's why, you know, earlier I was describing how this is quite a challenging moment, because this is now where I think businesses are realising this isn't just a quick fix. You know, you drop something in and then suddenly you release loads of capacity or cost reduction and everything's fine. That this is a huge undertaking to really get this right.

I think the other thing is we all have to accept we're learning, right? This is a huge transformation, and therefore we are all going to make, you know, missteps along the way and need to learn. But then if we can make sure that we have those fundamental principles in how we're operating, then that will keep us in a in a good place. But this is such a huge transformation.

It is going to take a bit of time to get it right. And there will be some things that don't work as intended.

Steph Dobbs (Host)

This has been a really fascinating discussion, so thank you both massively. But I suppose before we finish, for anybody listening, I just want to say if you're enjoying this episode, please make sure you do tune in to the rest of the series where we're going to be exploring a bit more about how to make the most of the AI opportunity. You can also catch up in all the conversations so far, and we started this series by asking: What will be the last job on earth? So finally, to wrap up this episode, it's time to ask the big question we always come back to: How do we turn AI ambition into a national advantage?

Sharon, let's start with you.

Sharon Hague (Guest)

So I think by rethinking how we upskill and train people across all sectors and stages of our workforce journeys.

Oliver Seal (Guest)

I'd say double down on what we're already great at, build on our world leading education sector that we have in this country to achieve what Sharon's just talked about. And the other one is we need to just start practising. We need to practice what we've learnt and use AI and stop doing what's not good, but really double down again on what is great with AI.

Steph Dobbs (Host)

That's great. Well, thank you so much for joining us.

Sharon Hague and Oliver Seal (Guests)

Thank you.

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Steph Dobbs (Host)

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

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