← James Reed: all about business
James Reed: all about business
40. Microsoft’s 6 principles for developing the best AI strategy | Jed Griffiths, Chief Digital Officer
01:05:47
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- [00:00]
James Reed
Welcome to All About Business with me, James Reed, the podcast that covers everything about business management and leadership. With AI transforming the way we live and work, how can you be sure your business is using it effectively? Today's guest, Jed Griffiths is the Chief Digital Officer at Microsoft where he helps businesses harness the power of AI through, through human centered innovation. In this episode we discuss the real reason most companies get AI wrong and how you can use AI to recruit the best talent. Well, today on All About Business, I'm really delighted to welcome Jed Griffiths. One or two people have said, can we have someone from a really big company who knows a lot of stuff? And I think I've delivered today or the team certainly has because Jed, he comes from Microsoft, which is the most valuable company in the world at the moment and he's the Chief Digital Officer for the uk, Microsoft uk. And Jed is also a scientist, a proper scientist, he's a physicist and we're going to be exploring what Microsoft is doing in the world of AI, his views on startups. I'm going to try and get some information out of him about his time at the Atomic Weapons Institute, but he's been pretty cagey in the warm up and, and we'll see what we can learn but I know it's going to be a lot. So thank you very much Jed for coming in this after.
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Jed Griffiths
Thank you very much for having me. Yeah, looking forward to sharing some insights.
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James Reed
Let's just begin. What do you see in the sort tech landscape at the moment? What's going on out there? What should we be really paying attention to?
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Jed Griffiths
Yeah, it's a great question. It's actually the number one question I get asked by pretty much every executive board or senior leader I speak to these days. So in my day to day role I spend a lot of time talking to companies from different sectors, sort of various sizes, but mainly enterprises. And the number one thing that every board is asking themselves right now is how do I get the most value out of this new generative AI thing that's hit the market? Because if you look at what's happened since November 22nd when ChatGPT GPT exploded onto the scene, millions of users in a matter of weeks. Pretty much every board is now asking the question, what does this do for my business? What does this do for my strategy? And I think it's caught a lot of CTOs napping in terms of their technical strategy. And so a lot of businesses are pivoting. So the number one thing is how do I make the most of AI?
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James Reed
You said how important it is for a company to have an AI strategy? How do they go about that? What does an AI strategy look like in your view?
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Jed Griffiths
It's very important, I think, and there are a number of components. It's easy to say AI strategy, but to make it actionable, let's turn that into things. So the first one really is to make sure that you've got a really clear business alignment to why are you going to use AI? So where are we going to use this technology? Rather than just sort of spin up some pilots and not really make the most of them, how are you actually going to leverage AI to provide real business value? And that's really, really important because it's not cheap necessarily to go and put AI everywhere in your business. And you need to make sure that you're doing it in the right parts. The second thing then that comes very quickly after is making sure that you've got a really good, perhaps technology and data strategy that underpins that. And what I mean by that really is data is the fuel for AI. So if you've got poor data, then the AI you put over the top of that data won't be that great. You won't get the great outcomes. So you need to make sure that you've got the right data, that data is governable, that it's accessible, usable by people that really fuels and gets better AI outcomes. And then I think for entrepreneurs and where they perhaps have a benefit over some of the more incumbent businesses, is that they tend to be what we call digital native or cloud first businesses. So they don't necessarily have this technical debt from years of operating. They're able to sort of have that proposition and very quickly, you know, move to perhaps a cloud platform and get the most of the benefits of cloud to scale. Right. So they have that technology platform and that's really, really important because it allows them to be, to expand quickly, you know, the scalability of cloud serve lots of people. And if you're building an application, whatever it might be, but also it allows you to leverage the improvements in AI so you're not having to do so much of the this kind of infrastructure estate maintenance yourself, you're able to make most of new models and new capabilities as they come out and then build on a platform. And Microsoft platform for us is our Azure Foundry platform, which allows you to get the most of AI quickly. And then two other components of the AI strategy is what we've talked about, which is the AI governance and ethics, which is very, very important. Making sure that you will know where you want to and not want to use AI, and you'll be transparent with your customers as well, where you're infusing AI in that products or service. Finally, I guess part of your strategy is your skilling, is your people, of course. How are you giving people the right skills and tools that they need to use these capabilities to grow as this technology is moving so quickly, you know, how do they learn about AI and how do they keep current?
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James Reed
It's interesting thinking about our business. You know, we've been around in business for quite a long time, so we've got a lot of data, but we've probably got some legacy tech, so we might be in that camp. If you're a new startup, I mean, you can put all the new cloud stuff in place, but you haven't got the data right, who's going to win? I mean, it's sort of interesting.
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Jed Griffiths
So I love.
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James Reed
You want to put the data into a new cloud situation, if you can.
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Jed Griffiths
Yeah. So I love that actually. It's really good because there's this viewpoint, I think, with a lot of founders I speak to, that they're out there, they're out to build a product and disrupt a market and go. And some do. Right. We have unicorns that eventually reach that status of being very disruptive and creating a strong following quickly. But actually many startups don't go there that quickly. And actually one of the things that I would recommend is don't necessarily discount the kind of the big incumbents. Maybe you need to partner with them because as you say, they've got the existing client base, they've got the knowledge within the sector. You might have a great product and a great disruptive avenue in that sector, wherever it might be. But perhaps you need that big incumbent to work with you on something. Maybe there's a partnership there. Right. And there's mutual value. So never discount. As a founder, you've got that strong vision, that vision to be disruptive. But sometimes the partnership angle might be the one to go down. And actually in lots of enterprises I talk to, many of them now are trying to be entrepreneurs, right. So they've got this viewpoint that they kind of disrupt themselves. And so there could be a natural partnership they're looking to work with, with startups and, you know, do it together.
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James Reed
I think that's really interesting and a huge opportunity for everyone, actually.
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Jed Griffiths
Absolutely. Everyone benefits.
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James Reed
Yeah, that's right. In your sort of crosshairs, isn't it? That's what your job is about, helping businesses do that.
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Jed Griffiths
That's absolutely right, yeah. So my role at Microsoft really is to bring the sort of the breadth of Microsoft of what we have in the UK from our products and services. You might have heard about Copilot, obviously we've met a lot of those. But you use Copilot. That's fantastic. Yeah. So co Copilot, you know, but also our data and AI services, and then even in some of our more innovative sort of products and services that you can access through Microsoft. But it's to bring that whole plethora of capabilities to an organization to say, how can we help you innovate and change and create new value for your organization?
- [06:57]
James Reed
If, like me, you run a business or manage a team, you'll know how important it is to hire great people. Over the last 65 years, Reid has worked with thousands of businesses around the world, helping them to recruit and to grow. This is what inspired us to create Reed AI, your new AI hiring agent. It's here to save you money, to save you time, and to help you get the right match. Whether you're hiring your first team member or your 50th, read AI is here to make it easier. Try it free for 28 days exclusively available during our beta period. Go to Read AI and get started. Reid, AI, your higher power. So for people who don't use Copilot, just tell us a little bit about what it is, what it does well in a line.
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Jed Griffiths
You know, I love this piece of marketing, actually. It's that we call it the UI for AI. So this is the new user interface for AI and Copilot's your. It's your companion. It's an AI companion that gets to know you, your context in the workplace, documents you access, people you collaborate with, and then it allows you to have a natural language. You can even talk to it, right? You can just converse with this tool in a way that you would an employee. And then it reaches out into your digital library. You know, the files you have access to, emails you've sent, teams, messages you have, and it helps accelerate your day, right? So it can sort of summarize documents that you've been sent recently. It can look at your calendar and help you prioritize your week. It can summarize your emails with you in sort of Outlook and really help you respond to long, complicated email chains without having to read through them. So it's really your companion for sort of the modern workplace.
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James Reed
What I was thinking was like assistant in a way, but everyone has an assistant. Now with Copilot, that's right. So is this making us all much more productive?
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Jed Griffiths
Well, that is the aim. So there's two things that's really an aim. Yeah, that's still the aim.
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James Reed
What's going on there? Because people say, oh, we're not more productive, we're actually less productive. Especially the public sector gets blamed for this. So what's going on? Why is that not.
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Jed Griffiths
Well, a little bit of a personal point on this one. I really don't like the term productivity. I think not many industries really quantify what that means for them. Right. So if we look at.
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James Reed
Maybe you don't like it because it's not quantified or because it's a concept.
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Jed Griffiths
Yeah, I don't think organizations quantify productivity.
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James Reed
Well, I don't know what it means.
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Jed Griffiths
Right, right. So if you've got a bunch of job roles and they're using copilot and they're getting time back, that's great. Right? That's great. From a personal productivity perspective, you know, I get maybe half an hour, an hour, maybe more back by using these tools and what you do with that time, you might choose to invest in a bit of learning. You might take on that stretch project you never had time to do before. And that's great. From a personal productivity perspective, when you look at the organizational productivity, that might be slightly different. And I think the challenge is for organizations to think about can we quantify what this extra time back means for us as a business? What are we going to do with that? Does that mean that we change our processes in some way or do we give back to the employee experience of the well being? I see organizations saying, look, you know, you can have that time back. Right. Invest in that as you will to.
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James Reed
Or you could just go home early.
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Jed Griffiths
Well, I don't know. I don't know. Maybe that's what people do.
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James Reed
Maybe if they've done the work. I suppose it's a different way of thinking about it.
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Jed Griffiths
Yeah. But it all comes down to what this hangs off really is your organizational strategy. So how you're going to use AI and how this, how it's supercharging both that personal productivity, but also adding organizational productivity. You know, is it changing the fundamental processes of how you do your work and how you, you know, how your business gets?
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James Reed
So if you're running an organization, if you're a manager or a CEO or you're running a team of people, you should be thinking about that. You're saying, oh yeah, the number one people are going to have a bit more time because of these new tools, how can we most productively use that time?
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Jed Griffiths
Absolutely right. Yeah. I think that's essential. And that's for sort of two reasons. One, it helps with the adoption. It's going to help people understand why they should use a tool like Copilot. Why should they sort of invest in learning about AI skills and how to prompt? Many people have heard about prompt engineering or writing good quality prompts. How do I get the most out of this tool? Both to give me that personal productivity, but also then to be more creative for the business to think about new avenues of maybe revenue generation or new growth, whatever it might be. And I think that's the transition point. Then organizations need to then from a top down perspective have a clear strategy for what they want to do with AI. I think that's the key. A lot of organizations are sort of stuck in neutral and trying to scale their AI pilots and it's because they don't have a clear strategy for what they actually want to do with AI.
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James Reed
We had two young entrepreneurs in the podcast studio a few weeks ago, Richard Nachi Hollingsworth, and they've developed an AI assistant, it's called Fixer. They were telling us about it and they'd actually gone to America and been sort of encouraged and cajoled and sort of boosted in all sorts of ways by that experience. But they've just raised $10 million for this venture, which is about five people I think at the moment. So that's one of the things they said, and I want to test this with you, is that they think 2025 is the year where you're going to see a lot more AI startups. You know, we've been talking about companies and how they deploy it, but you know, new businesses coming into the scene with new offerings. Is that something you're seeing or as Microsoft, because you'd be at the forefront because you'd be supplying on the tech?
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Jed Griffiths
Yeah, I think that's absolutely true. We're seeing that number increase. I mean we have at Microsoft, we have a Microsoft for Startups program that helps people build with our platform and build these new exciting differentiated AI solutions. But yes, they're on the increase. I think the UK is a great place to be a tech startup. People are looking at this technology and looking for avenues to disrupt incumbent businesses. Think about new business models, new ways of bringing data together in exciting ways to create. You say you create new services or new products. So I think it's a really vibrant, you know, it's definitely a vibrant scene.
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James Reed
Why do you think the UK is a good place then to do this?
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Jed Griffiths
The UK's got a really high propensity for sort of creativity and innovation. So if you look at some of the, you know, the benchmarks and metrics over the years in terms of ip, we're right up there, I think in the top three or top five countries. In terms of IP generation, our education system is really, really good. We attract talent into zones like London and Manchester, particularly where there's a strong concentration of technical and digital skills. So I think, you know, it's a good place. It's, it's got good networks, you know, it's good, good infrastructure. So it's a good place to, to begin a startup.
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James Reed
So it's like a cluster effect where you get lots of people coming together. Yeah, I suppose in London, from all over the world really.
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Jed Griffiths
Yeah, exactly right. You know, the UK has this reputation, but then I think, you know, the challenge might be scaling. So perhaps, you know, a lot of the conversations I've had over the years with technology startups or in, you know, before joining Microsoft, I've done a lot with the Institute of Physics in supporting more deep tech or physics based startups. The challenge has always been scaling. So getting that sort of seed funding and accelerator funding or working with networks to get you going, that's one thing. And that's, you know, you can do that relatively easy. In the uk. The challenge is how do you move from technology, your initial sort of technology focused offering into a much more product based offering where you can get over the, you know, the traditional valley of death, right, where you have the Valley of death. That sounds bad. It does sound bad, doesn't it?
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James Reed
Valley of death.
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Jed Griffiths
Come on, tell me.
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James Reed
You need to know this.
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Jed Griffiths
Yeah. Right, so, so the valley of death really is a, is where you have your initial sort of your minimal viable product, right? So you've, you've done your initial prototyping, you've got your initial perhaps product, but you need to, you need to scale, right? You need to sort of reach new markets. You need to get recurring revenue to.
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James Reed
Sell it to somebody.
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Jed Griffiths
Exactly right. You need to start getting some market penetration. You know, for various reasons. Either it's cash flow reasons or, you know, especially in deep techs, you see this where your, where your product is tangible. When you're building a physical thing, that's much tougher, right, because you've got to go and manufacture that, then you need to distribute that. Maybe you're a biomedical devices supplier or you've got a great New handheld kit for the GP surgery. That's going to be hard. That's a regulated industry. So there are going to be some delays and some challenges to getting that product out to the market and penetrating the market. And if those challenges are too great to surmount, then you end up falling into the valley of death where the funding doesn't support you to really reach that scale and really penetrate and sell into the market you're looking for.
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James Reed
So there's a lot in this valley that can kill you, by the sound things. But I mean, two things that struck me when you were saying that. One is there's maybe not a hinterland of manufacturing and design capacity that you can go and get new things made at volume quickly. And the other, maybe there isn't the money. Is that a fair summary of that?
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Jed Griffiths
Yeah, I think so. And I think there was a great actually report that came out around venture capital in physics that the Institute of Physics published recently, which is a pretty good read and talks about some of these barriers. But one in particular is for deep tech especially. I talked about these. You see this a lot.
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James Reed
What do you mean by deep tech? Explain.
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Jed Griffiths
So deep tech would be science based startups, Right. Where you're infusing some kind of digital AI or technology product with a physical product. So it might be some kind of augmented reality or virtual reality, or it might be drone technology or automotive technology, you know, quantum. Yes, something. It's something that relies on a physics or chemistry or some kind of engineering principle or IP that then is scaled through some product. Right. That's how I see deep tech. And the challenge there, of course, is a lot of your costs will be in extended sort of research and development cycles. So when you think about, if you perhaps contrast that with maybe a fintech or a finance tech business, then it's predominantly software based. And the thresholds for moving from that series A to series B and getting your funding, they're very well quantified. And you know, your revenue can come quite quickly, you can go to market quite quickly as a deep tech, as an R and D, with that long R and D cycle, you're still looking for funding as you're refining your products and you're seeking new markets, you're looking to expand. So there's some.
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James Reed
So you need very patient investors.
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Jed Griffiths
Definitely.
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James Reed
Who know what they're doing.
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Jed Griffiths
Yeah. And investors who really understand what the commercialization routes are for deep tech products as opposed to more traditional.
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James Reed
And there's a shortage of them in the uk. Is that the case?
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Jed Griffiths
I don't know if there's a shortage. I just think perhaps from some of the sort of, you know, anecdotes from speaking to startups in this space and some of the, you know, the reports I've read, things like, you know, Bohurst and Pitchbook and the recent government papers that have been issued around this, so that there's a, there's an issue, there's a number of factors, but there's something we're not quite getting right in the UK to really maximize on that scaling factor for some of this technology.
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James Reed
So what happens then? So you, so these new, these, these new businesses are heading off and they get to this place, the Valley of Death, as you call it, what happens? They sell out? Do they go bust or accommodate? I mean, do they, these entrepreneurs get out too soon? What, what's the sort of outcome of this?
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Jed Griffiths
Yeah, well, I think all too often they, perhaps they, they collapse. Right? They're unable to disappear. Yeah, I think so. I mean, I know that.
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James Reed
Well, there's a sort of Darwinism about that as well, isn't there? You might not have been a very good idea.
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Jed Griffiths
Well, potentially. And I think you're saying it might.
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James Reed
Be killing good ideas as well.
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Jed Griffiths
Well, it could be and I think that's right. You know, I couldn't say I'm not. I profess to be, you know, an expert in the whole sort of startup ecosystem, but certainly from some of the ones that I've spent time either mentoring or supported through the, the Institute of Physics, you know, they all report these challenges on the deep sec side, especially of being able to overcome these, these scaling challenges. Right. And getting those products out there. Yeah.
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James Reed
Now. So you mentor startups?
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Jed Griffiths
I do, yeah, I do. I do have a few that I've mentored.
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James Reed
I think every startup should have a mentor. We were talking to a young woman who said she got such valuable advice from her mentor that saved the company. Oh, wow. Okay. Yeah, well, I'm not, I'm not sure.
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Jed Griffiths
If any would report that. My advice is directly sapien.
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James Reed
You don't know that.
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Jed Griffiths
I don't know that. Right, so go on.
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James Reed
So how does it work? How do you do your mentoring of startup?
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Jed Griffiths
Sometimes through networking mainly, you know, somebody might, might say, hey, you know, Jed's done a few of these. Go and talk to Jed. Or through the work.
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James Reed
So you're available for people?
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Jed Griffiths
I'm available certainly for deep tech, I think, because I'm a physicist and I look at that.
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James Reed
But I think there might be someone out there who'd be interested in your support.
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Jed Griffiths
Yeah, absolutely right. And I'd gladly offer that. In fact, the Institute of Physics has got, you know, a mentorship scheme that, you know, accesses the sort of member networks and enables deep tech or physics based startups to get this kind of scaling advice. But there's a load of this out there, out in the UK as well. There are a lot of networks and everything from our catapult centers right through to some of the regional funding and network support that we have in the UK for startups, you can get a lot of advice. The key thing that I tend to offer is how to go from technology to product. So how to think around. Could you think of the anatomy of a tech founder is probably someone PhD, maybe they've spun out of a university or they, they've organically come up with a great idea. Founders tend to be hyper focused on that idea, which is great. They've got that singular vision. This is going to be great. This is the technology we need to invest in, researching that. But there's a long way from that thinking to creating a product that someone can realize the value of invest in and scale and get some return. And I think sometimes that's a hard barrier for some founders to cross, which is why mentors and networking and having a good support system around you of people who've done it before and navigated those challenges is really important.
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James Reed
And you're well placed. You're like the sort of bridge between the science and the commerce in a sense.
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Jed Griffiths
I find myself being in that space at the moment. Yeah. And I think very important. Yeah, I think the transition into, over the last few years, moving into Microsoft and seeing what's happened with AI, spending a lot of time with large enterprises, spending time with startups. I was at a Barclays Eagle Labs event a few weeks, a few months ago and spoke to a lot of tech startups there and talked to them about what challenges they're facing. What's the market like? Like, I think there's been an explosion. Right. And so having people close to you who can help you navigate that is essential at this time because there's so much. Yeah. There's so much movement in the, in especially in the AI market right now.
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James Reed
You said you'd move relatively recently to Microsoft, which I know.
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Jed Griffiths
Yeah.
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James Reed
Give us a quick heads up what you were doing before.
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Jed Griffiths
Well, I, I could tell you, but I, I'd have to kill you. No, it's a stupid joke.
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James Reed
We've got to witness this here.
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Jed Griffiths
Yeah.
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James Reed
Come on, open up.
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Jed Griffiths
Yeah, no, it's fine. So, so, yeah, my, I have a sort of an eclectic journey into Microsoft and I don't mind talking about this because I think squid, the concept of a Squiggly career, I think is really important.
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James Reed
Yeah, there's a book called Squiggly.
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Jed Griffiths
Yeah, there is. Right. Yeah.
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James Reed
And it's very successful.
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Jed Griffiths
And so, yeah, so I, I spent sort of 19, 20 years or so in nuclear defense, you know, before coming into defense. Yeah, that's right. Atom bombs. Yeah, essentially in, in and out of that 19 years. Yeah, around about that 19. Almost two decades. Yeah.
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James Reed
So that's pretty different to Microsoft.
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Jed Griffiths
It's very different. Yeah, absolutely. Completely different. I mean, not many people do sort of almost two decades of work and then completely pivot their career into something very different. That's, that's a difficult thing to pull off. I'm quite, quite surprised I managed it, but it was good fun. You know, I always characterize myself, even in the role I'm in now as a technologist, as a physicist, within essentially, you know, a senior software sales role. If I'm objective and I look at my skill set and who I am, I approach the world and the way I think as a physicist sort of.
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James Reed
Approaches the world still. Yeah, so the atomic weapons space, you know, we've seen the film Oppenheimer. I mean, you're like one of those people in the white coats doing that.
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Jed Griffiths
I used to wear a white coat, but I used to, I, I, Yeah.
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James Reed
You'Re a real scientist working, I mean, and this is, you know, you can't make mistakes in that sort of environment, can you?
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Jed Griffiths
Yeah, put it mildly. That's right. Yeah.
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James Reed
So that's quite a different one. So there's a trial and error that we have in startups.
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Jed Griffiths
That's a really good, a really good point to make because if you think about the world of nuclear weapons and defense, that's a world that absolutely, you need to be 100% correct. As you say, it needs to run, you need to have high process control, you need to make sure that everything is operating as it should. And so because of that high risk hazard. If you think about the usual mantras of innovation, let's move fast, let's break things, let's be creative. That that really doesn't fly in certain industries and say it's not just in nuclear defense. One of the key learnings that I've taken into my role now is actually when I work a lot with other regulated industries like finance or the energy sector, where they also have very strict rules and Regulations about what they can and can't do with technology, for instance. Those learnings have done me well in how to think about driving innovation in heavily regulated environments. So there are still things you can do though, right? Just because something is locked down, it doesn't mean that you can't build mechanisms for innovation.
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James Reed
Interesting. But you can't test the product.
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Jed Griffiths
No, luckily we can't test. Luckily we don't test the product. I think that's, that's probably the, the best way to say it. Or at least we don't.
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James Reed
So no A B testing.
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Jed Griffiths
No, no, that's right, yeah. Which is probably a good thing.
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James Reed
I think it is a good thing. I'm really pleased that there's no A B testing. But then you, you mentioned that you pivoted and you modestly said you were quite surprised. I'm not surprised that you'd done successfully in the new role. For someone thinking about pivoting, what should they be reflecting on? I mean, we talk a lot about transferable skills in recruitment. Yeah, but what were you thinking about and how did you make it work?
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Jed Griffiths
My career was quite an interesting one. You know, being a physicist, working in research and development, then a bit of manufacturing and then moving to sort of a technical policy and advisory role, you know, to policymakers in government around the sort of nuclear program and then transitioning into organizational strategy and innovation thinking, you know, working with lots of other organizations on what we just talked about, you know, how to create innovation in a regulated space. And then moving into Microsoft, you know, that changed. The reason I looked at that was I could see where the world was going in terms of how prevalent digital technology and, you know, AI and how that was changing how businesses were thinking around, running their business and driving.
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James Reed
This was before Chat GPT.
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Jed Griffiths
Oh, yeah, that's. Yeah, that's before it landed. Right. But, but actually.
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James Reed
But you can see it coming.
- [24:36]
Jed Griffiths
Yeah, you can see it coming. And you know, being a bit of a nerd, you know, I'd read these sort of journal of Computer Science type articles around the nature of what were then sort of adversarial, generative, adversarial networks, or GANs, you know, where that technology was going, transformer technology, you know, this was sort of the 2017 mark. You could sort of see on the horizon. Wow, this is pretty. This is different, you know, this is a different technology base and that's going to evolve and it's going to accelerate and it's going to be really, really important. And it has. Right. And it's ultimately led To.
- [25:05]
James Reed
So you wanted to be part of that.
- [25:06]
Jed Griffiths
I wanted to be part of it, yeah. That's basically what happened. And so I realized, what is it that I could offer? And it boiled down really, it was my approach to thinking. And that's if I think now where we are with AI as well, some of the core skills that I certainly look for in candidates or that I was trying to put forward in myself when I made that pivot, was how do you think about the world? How do you assess information? Can you navigate complex environments and someone's telling you one thing, how do you check that's true? How would you set about an experimental thought? Experimental thing. How would I set about testing if you told me something?
- [25:42]
James Reed
That's.
- [25:42]
Jed Griffiths
That's right.
- [25:43]
James Reed
That's why I'm interested. You. You described your approach to thinking.
- [25:46]
Jed Griffiths
Yeah.
- [25:46]
James Reed
I want to know what that is.
- [25:47]
Jed Griffiths
Yeah. It's rooted in the scientific.
- [25:49]
James Reed
So it's rooted in the scientific.
- [25:51]
Jed Griffiths
Yeah, yeah.
- [25:51]
James Reed
So you don't believe anyone. You want to go and check it.
- [25:53]
Jed Griffiths
Well, that's not fair. Yeah. So that. I don't believe anyone.
- [25:58]
James Reed
But you are. You are always testing.
- [26:01]
Jed Griffiths
It's just a mindset, I think. I think something.
- [26:03]
James Reed
One of the scientific mindset.
- [26:05]
Jed Griffiths
Yeah, I think it is. It's one of the wonderful things about why I think people who are STEM professionals or have had a career in, you know, science, tech, engineering, mathematics is where stem. The scientific method is a wonderful way of framing your thinking for life because it gives you that rigorous process of essentially critical thinking. And as we move now into an era of AI where information could be at your fingertips, summarized or synthesized from huge volumes of other information sources, it's the number one skill of how do I think through this? Is that likely to be the right answer? What might I do? How might I probe and test this? And how do I need to. To, you know, turn that into something useful so I can. I could do something with it?
- [26:43]
James Reed
It does seem particularly important at this point, especially critical thinking with these new emerging technologies.
- [26:50]
Jed Griffiths
Yeah, I think it is. I think someone told me recently from LinkedIn, the sort of. The top, sort of 15 skills or so on LinkedIn. I think strategic thinking, adaptability, critical thinking are now up in the top five, I think, or top 10 of skills that employers are looking for.
- [27:04]
James Reed
So that suggests to me more young people should be doing STEM subjects projects.
- [27:08]
Jed Griffiths
Or they should be thinking around what I call the kind of four Cs. Right. You know, the. The four Cs of collaboration, communication, critical thinking, and creativity. Right. How do you Maximize.
- [27:19]
James Reed
Say them again.
- [27:20]
Jed Griffiths
Yeah, you're going to. Collaboration, communication, critical thinking and creativity. The four Cs. I love the four Cs. Right. So, so good.
- [27:29]
James Reed
I like that.
- [27:29]
Jed Griffiths
Yeah. Many, many organizations or many disciplines I should say you can leverage the four Cs and they're totally transferable and I think they're really, really, really good skills. Maximize on in the era of AI, because now you've got this incredible tool set that's going to be able to reach into data applications or huge fields of complex data or massive amounts of documentation, pull all this insight out and you need to figure out what are you going to do with that? How are you going to make the value of that? What are you going to combine that with to do something useful? That's a skill set and I think that's where the job market's going to shift is employers are going to be looking increasingly for people who can think a little bit bigger, bigger picture and understand how they can leverage the, these tools to do the more sort of lower end mundane information finding but actually turn that into value.
- [28:17]
James Reed
How do you learn those skills, do you think?
- [28:19]
Jed Griffiths
Well, that's a good question. I think they can be taught for sure. You know, there's, like I said, that's why, going back to the question about the scientific method, that's one of the.
- [28:26]
James Reed
Things that it sort of gives, you know, studying science.
- [28:29]
Jed Griffiths
Absolutely.
- [28:29]
James Reed
I mean there's quite a lot online now about communication skills. You can do courses that are very modestly priced.
- [28:36]
Jed Griffiths
Yeah, yeah, that's.
- [28:36]
James Reed
We've got lots actually on our courses page on reading do. Yeah.co.uk so those, so those are things that anyone can go and learn. You don't need to be a physicist, do you?
- [28:46]
Jed Griffiths
No, not at all. I just think by, by, you know, I guess I'm lucky really. I think I never really had a life plan. I just always said, hey, look, I'm really interested in science, I'm going to do that. But over the course of my career I've discovered that actually a career in physics has stood me in really, really good stead for these sort of adaptable skills that I can apply virtually anywhere really. And it's essentially it's thinking, it's sort of teaching you critical thought. Again, philosophy actually. I've got friends who, who've got, you know, degrees in philosophy and, and then the old joke when we were in university about the, the applied STEM or the, the arts degree and so on and so forth. Oh dear. I always remember there was a. Maybe I shouldn't say this one on the podcast, but I always remember on the hand, on the hand dryer in the, in the toilets in the physics department, it was someone that had sketched with a pen, the permanent pen arts degree. Pull here. And it was just the kind of paper towel and that.
- [29:39]
James Reed
Okay.
- [29:39]
Jed Griffiths
Obviously for the purposes of listeners.
- [29:41]
James Reed
No, well, you have a dys.
- [29:43]
Jed Griffiths
Yeah, that's right. Yeah, Dyson one. Exactly. Yeah, yeah, please. But, but, but I think, you know, you know, I don't prescribe to that at all, but it's really, really true. Perhaps I was a bit jealous because my, my course is like 30 odd hours a week and I'd look at my colleagues in philosophy and doing three hours and spending lots of time. They did. Yeah.
- [30:02]
James Reed
So where are they now sort of thing. I don't know.
- [30:04]
Jed Griffiths
But actually they're laughing now because if you think about, you know, going back to the four Cs, right, and you think about this one around critical thinking, it doesn't get much more critical thinking than philosopher, Right. Than the kind of philosophy sort of art of a philosopher. Right. The way they think, the way they approach problems. So when you're looking at AI, some of the people I've seen do really well with prompting, with getting AI to do what they want and using multiple tools or now agents, as you probably would have heard them on the sort of agentic era, they're coming from more of those communicative disciplines where they're used to structuring an argument because that's AI like structure, that if you construct your argument.
- [30:40]
James Reed
AI likes a philosopher, doesn't it?
- [30:41]
Jed Griffiths
Does it does.
- [30:42]
James Reed
That's what I studied. Pleased to hear that. Somehow you called it agentic. The agentic age. Tell me, what's that? Is that a Microsoft Word? Where's it come from?
- [30:53]
Jed Griffiths
I think Satya Nadella coined that one in our. Yeah, I think he's very good at coining things.
- [30:58]
James Reed
I have the hugest respect for Satya. I come to some of your seminars and he's always so interesting and I like the fact he opens up to customers and tells us what he's thinking. Yeah, he's come up with agentic.
- [31:10]
Jed Griffiths
Yeah, he has. Right. I've had the pleasure of meeting him a few times and he has a talismanic quality to him. I think he's, you know, it's a fantastic leader who's able to bring that clarity of business and direction, but also really champion the importance of a good corporate culture, you know, an organizational culture that underpins good performance. And I think Satya really embodies that. I think that's why he's been such a successful CEO and why, you know, why people. He has such a strong following. Right.
- [31:33]
James Reed
Microsoft has turned around really under his leadership, which I find very interesting. So he's written a book, hasn't he?
- [31:40]
Jed Griffiths
Yes, he has, yeah. Hit refresh.
- [31:42]
James Reed
Hit refresh.
- [31:43]
Jed Griffiths
Yeah.
- [31:43]
James Reed
Well, we should all read that, I think.
- [31:45]
Jed Griffiths
Yeah, definitely. Mandatory reading for mandatory. Yeah, that's right. When you join Microsoft, you force refresh.
- [31:52]
James Reed
Okay, well, I'm going to read it because I want to. You've used the phrase agentic, the agentic age. This is sort of stuck in my mind.
- [32:00]
Jed Griffiths
So. So this has been the holy grail, I guess, of AI researchers for decades, which is we create a digital system that can take action on our behalf, you know, given some instruction, then go away and. Well, yeah, right. I mean, you can do that now. Right. So but can it do sophisticated things for us? You know, given some basic instructions and go away and complete a task and come back? And we're starting to see that now with generative AI. And it's in part because you've got this new.
- [32:26]
James Reed
When you say sophisticated things, what are you thinking?
- [32:29]
Jed Griffiths
Well, it might be that it goes into, let's say in a business context, I don't know, ordering a laptop in your business. Right. If you break that down, I think many people out there have been in a work environment where the laptop goes wrong. So you go to IT support and there's probably many, many steps right in that process to get that laptop replaced.
- [32:46]
James Reed
It doesn't bode well. You're not thinking this is going to be a good experience.
- [32:50]
Jed Griffiths
Yeah, sometimes that can happen. Yeah. Not at Microsoft. I should not.
- [32:54]
James Reed
So go to IT support. And what will happen in this new agentic?
- [32:58]
Jed Griffiths
So you can imagine, you know, if you think about, you know, we certainly at Microsoft we see this scale, scale of agents. Okay. So at the one end you have the sort of retrieval aspect of an agent. So very simply, this agent might know the IT help desk process really, really well. And so it's got all the documentation in there. And so you, the user say my laptop's broken and you'd press Enter and the agent would look at that and assess that and then find out and tell you just spit back some information. Okay. You need to do the following things. So that would be a very basic sort of query based agent. Right. And it might use your personal circumstance to do that. Maybe say, you know, if you're a director or you work in a field engineer, it Might give you a different process. Then you might go on to sort of a little bit more sophisticated, sort of a task based agent. So in that same example I gave there, you say, oh, my laptop's broken. So what that agent might do is then not just give you the process, but it might reach out and pull the forms that you need to complete, or it might complete them for you. Right. And it might execute a set of tasks based on your context and get you some of the way there so that you know, you can start to action this problem. And then you might go on to a much more sophisticated or these kind of more autonomous agents where it says, you might put in a prompt, say, oh, my laptop seems to have stopped working. I can't do the following things and press Enter. And then that agent might go, okay, what's the problem here? Looks like there's a problem with the laptop. Maybe I need to look at the laptop procedures. Maybe it calls another agent that goes to the stock or the warehouse, for instance, or the ordering system orders you a new one. Right. Or maybe it triggers a help desk ticket for you or sort of solves that, you know, with you. So it will go and execute, it will assess by itself and execute a number of attacks.
- [34:39]
James Reed
So you're seeing AI do some or all of this already then?
- [34:42]
Jed Griffiths
That's right, yeah. You know, across organizations, one of the key things, going back to what I was saying about that personal productivity and that business value, a lot of organizations now are saying, well, hold on a second, this means that these agents are now really, really closely aligned to our business process processes. So what are the business processes that I can get the agents to do so that I can get my human operators really to focus on the more value add parts of the work. Right. Because nobody really wants to spend their whole day filling in spreadsheets or doing IT service test tickets. Yeah, everyone does. Right? Nobody wants to fill in forms. But you like interacting with your staff and you like talking and solving people's problems and they are more inherently human based activities. Whereas the whole, whole filling in the documentation and doing the ordering, well, nobody really wants to do that.
- [35:28]
James Reed
That could be infinite in its application.
- [35:30]
Jed Griffiths
Right. Which is why I think there's just so much value to what's going on with AI right now. I love this quote. Actually, I'm not sure if I can take credit for it because. Go on, yeah, take credit. What is it? Yeah, so being a physicist, working in manufacturing and coming out in sort of early part of my career, if you're aware of how manufacturing processes work. They have this thing called Lean, right. So if you go to any manufacturing etc and you think they'll have some kind of Lean or the kind of Six Sigma, if you're aware of that as well, Right. Process optimization, removal of waste, optimizing the factory floor, making sure everything is in the right place, the right time. And this sort of came out of the 90s, really. Really? Yeah, right, exactly.
- [36:07]
James Reed
It's transformational.
- [36:08]
Jed Griffiths
It was indeed. Yeah. So you think about what Lean did to manufacturing in the 1990s. Process as, you know, measure your process, put metrics in place, eliminate waste, drive through value, all that good stuff, right? What AI now, what generative AI and agents are doing, in my view for, for the knowledge work is basically what Lean did for manufacturing, right? So if you think about knowledge work and professional services or auditing or tax or legal consultancy, a lot of that work is in the IP of humans, okay? It's tied up in insights, in tacit information, hard to measure sometimes in documentations, in advisory and, you know, complex rules. And we never really had had a tool set that could access that before. Right. It was difficult. You could do it, but it was difficult. But now with generative AI and its ability to go through a lot of that documentation to reason with you and you can converse with it, suddenly you can start to put shape around that, you can put metrics around that. And I think the exciting thing for me is AI is going to start doing a degree of Lean and process optimization now in knowledge wise work, you know, in, in knowledge workers, that seems to be happening.
- [37:19]
James Reed
But I mean, when I was listening to you, I was thinking about manufacturing and how it's changed. Not many people work in manufacturing now. I mean, Lean did result in lots of people leaving manufacturing going on. Is that something we should be concerned about now in knowledge work? I mean, all these people at home with their laptops doing stuff and if what you say is correct, that's going to be very disruptive to the labor market, isn't it?
- [37:43]
Jed Griffiths
I think it could be disruptive, but I think, I know you read in the press around we're looking for headcount reductions and job losses because of AI. I actually think it won't be all that bad. In fact, if anything, I think it will allow us to really humanize work. I think a business that really thinks about this in the right way is able to push the mundane and the not engaging aspects of those knowledge tasks.
- [38:08]
James Reed
Some business leaders, leaders, they're probably not the most sort of empathetic of so we're going to go from a 15, 000 person organization to two or something like that. And you think, well, is that really the best way to motivate your team to embrace these new technologies?
- [38:22]
Jed Griffiths
Yeah, perhaps not. Probably not, right?
- [38:24]
James Reed
No, but. So that's odd to me that people would sort of pronounce that maybe they're trying to get the share price up or something, I don't know. But then there is this experience that we've all had that with more technology there seems to be more work, not less, you know, over, over the. Certainly my career, lots of marvelous innovations, I'm busier than ever and our business is busy, so that's our lived experience. But this technology is different, isn't it? Maybe it will be different.
- [38:51]
Jed Griffiths
I'd like to think that it will be different because, you know, it all goes back to what I was saying about when you give people time back in a work context, what do you, what is your expectations of what they do with that time? And this is why it's so important, I think, to do hand in hand, the optimization, you know, using AI to optimize people's workflows, but then that time used productively. Right. In the right way. So is it opening up new business models? Is it changing the way you operate or is it an opportunity to say, excellent, we can give that time back to our employees? No more 14 hour days in some, you know, certainly some professional services, you know, long, long working days and burnout in many sectors. I mean, the legal sector especially suffers from this. I think there's a real opportunity to change the way we think about work. And my personal hope actually for AI as it diffuses more broadly through the economy is we actually humanize work. Going back to what you were saying around redistributing the workforce as it were, very few people's jobs are just one task. AI is good at. Task based work, absolutely fantastic. But there's still some tasks that, that it's not ideally suited for. That's what humans are for, right? So what we're really looking at is how do we rejig it so that AI does the task that it's really good at and we rehumanize work. Right. And I would love to see that, you know, people spending and investing a lot more time in the 4Cs building those collaborations, you know, those networks with people spending more time with customers, spending more time in employee well being, you know, spending more, being able to spend more time, perhaps your children, your family, because you've really implemented AI work well and you've been able to strike the balance between a good business model and the work life balance. For me that's like, that's a really positive message. That's really weird.
- [40:32]
James Reed
It's exciting. That's gamechanging. That's a life improving offer. If we can make it right, that's it. I'm through like that. Now I'm, I'm in recruitment and been in recruitment for a long time and there's a lot going on in the sort of AI recruitment space. What are you seeing? Well, I mean what, what do you, how do you think it might change recruitment? I'm just, I'm just being cheeky here, but I want to hear what you think because you're in. Yeah, sharpen.
- [40:58]
Jed Griffiths
It's a good question because I think a lot of organizations in your sector are starting to really think seriously about this technology and what it does. And actually there are probably three broad areas really that it's really having an impact on. The first is the traditional back office processes. Invoicing, finance, sort of onboarding, those kind of things. Right. Being able to sort of automate and speed up those processes. Being able to use much more kind of predictive analytics. And that's really important. Those are the sort of, the generic. In fact, they're quite generic. Right, Those kind of back office processes.
- [41:31]
James Reed
That was the first place we introduced AI years ago.
- [41:33]
Jed Griffiths
Exactly.
- [41:34]
James Reed
Cash allocation function, I think it was. Yeah, it just went through the work like a dose of sorts.
- [41:39]
Jed Griffiths
Absolutely right. And those sort of processes now become supercharged. So what's happened now is, you know, one of the things that generative AI is doing in this sort of back office process is allowing people who don't necessarily have the sort of data science or engineering skills to work, work with large volumes of organizational data that you would have in your ERP or enterprise tooling. You can now sort of push some of those tasks out to people who don't have that skill set. You can put AI in between and so people much closer to the work can ask questions of maybe organizational resourcing or costing or whatever it might be and get that data and get that insight from the kind of source of truth, the organizational data, without having to task a separate team and get them to do that, that analytics for them. Right. So that's great. Right. Because that's going to just bring those data driven insights of an organization straight to the people who need them in the front line for recruitment. I think in particular, one of the things I think it's going to do is really help the consultant in terms of that time for profitability, because as I understand, there's quite a high turnover in this industry as well. It's a long time to onboard a consultant. They bring their network and the knowledge that they have of their area, and so then you're looking at your client base, what's in the market right now, what are you trying to match in terms of roles and candidates. And so there's quite a long sort of onboarding process bringing a new consultant in. And then of course, if they leave after a matter of months, that's quite a problem. So I think one of the things that the recruitment industry is going to gain from AI is reducing that time to profitability. When you're onboarding a new consultant, they'll be able to access training candidate databases quicker, you know, job spec creation, those kind of things. They'll be able to do a lot of that much, much faster, faster, and then be much, much more effective much.
- [43:19]
James Reed
Quicker in the organization, which would change the economics.
- [43:21]
Jed Griffiths
Right. And going back to that business model thing I was talking about. Right. So you're changing the personal productivity of the consultant. The role of the business leaders is to think about how that translates into adjusted business models for value. Right. And that's the AI strategy bit. And then this final one, I think is the client engagement, the candidate engagement, the piece of anecdote. I know many recruiters lament not being able to go back to all the unsuccessful candidates and tell them, hey, look, really sorry you didn't make it this time, or, you know, this was the. These were the things that perhaps, you know, would have been good to improve on. Well, AI is a great tool there for providing a much more personalized set of responses or engagement. Right. You know, you can, you would be able to sort of create those feedback mechanisms much more readily for the candidates. You might be able to create personalized sort of journeys for candidates so that they can navigate a recruitment process much more smoothly, you know, and have that.
- [44:12]
James Reed
Sort of AI because there's a lot of disappointment involved.
- [44:14]
Jed Griffiths
Right.
- [44:14]
James Reed
You apply for jobs, you don't get them. You go for an interview, you don't hear.
- [44:17]
Jed Griffiths
Yeah.
- [44:18]
James Reed
Or you don't get the job.
- [44:19]
Jed Griffiths
Yeah.
- [44:19]
James Reed
And we want to place everyone clearly, so maintaining good relations is. Is very important. You could see AI supporting that.
- [44:26]
Jed Griffiths
Yeah, I really could. I think, I think, you know, the recruitment industry's actually got, you know, there's some real innovation that could be made in this sector. Right. You know, if you think, I agree. I like to think sort of blue sky. So you know, let's imagine a world where, where everyone has their own kind of personal AI career tooling. Right. So the recruitment industry or creates a kind of this competitive world where you're offering to, I pay, I don't know, a subscription a month or something like that. And I get this personalized AI tooling that's guiding me through my career advising. What's coming up, what should I be thinking about? What skills? I mean that'd be amazing. Right. So there's real opportunity to create these personalized candidate and career experience based on the knowledge and the experience that recruiters have in the market and job market.
- [45:09]
James Reed
We're seeing people use AI to create their CVs shall we say? And it's used for creating job descriptions and then the job description goes online and someone applies. You get this situation where AI is talking to AI.
- [45:23]
Jed Griffiths
Yeah.
- [45:24]
James Reed
You're smiling.
- [45:25]
Jed Griffiths
I am because I've read a few of these perfect CVs recently where we put out a job spec and the spec then the candidates replies outstanding CV you created.
- [45:34]
James Reed
And the AI thinks wow, that's the perfect person. I mean who are we kidding here? I mean maybe the AI is better at choosing people, I don't know. But it's sort of, I mean it's quite easy to game it, isn't it?
- [45:44]
Jed Griffiths
Oh well this, this is really interesting. So this is like the, you know, going back to things that I talked to boards about. This has been kind of the recruitment industry's number one pain point at the moment in that, you know, it's very, it's, you have to stay one head, one step ahead of the game in terms of how you're doing candidate pre selection and what you're looking for now. And be quite creative in that.
- [46:03]
James Reed
Because we have a screening business.
- [46:04]
Jed Griffiths
Exactly.
- [46:04]
James Reed
That's really busy.
- [46:05]
Jed Griffiths
Yeah.
- [46:06]
James Reed
Because more and more people want to have people double check.
- [46:08]
Jed Griffiths
Yeah. And I think this is just one of the, you know, one of the things that happens when a technology like this hits the market. There are waves of disruption for a little while while everyone reconfigures. Okay, how are we going to updates their cv? Yeah, right. How are we going to deal with this cv?
- [46:23]
James Reed
But we used to say, I mean I've written a book about CVs and, and it was considered fine to tailor your CV. So if you're going for a sales job you'd emphasize your sales experience.
- [46:33]
Jed Griffiths
Yeah, of course if you're going for.
- [46:34]
James Reed
An admin job you'd emphasize you. I mean, but Now I think that people just said, this is the job I'm applying for. Chat. What should I say? Yeah, that's right. And it comes back and it's sort of.
- [46:46]
Jed Griffiths
And it's become difficult. Right. And I think that's where the, the innovation needs to, to come from is. Okay, how can you then use the technology to have a much more engaging interview process? Right. How do you change the selection, interview process with this technology? Right. So to really, for me, you know, things that I would be looking for is how do you find, find. Has this candidate Got the four Cs I'm looking for?
- [47:06]
James Reed
Right, so get AI to check for that.
- [47:08]
Jed Griffiths
Well, I don't know, Maybe. Maybe you could, maybe it couldn't.
- [47:12]
James Reed
Creativity. I don't know.
- [47:13]
Jed Griffiths
Right, well, this is the innovation. I think that the sectors, it's, you know, the sector's got a huge opportunity to invest and think about, well, what does that look like? You know, I'm not an expert.
- [47:21]
James Reed
Some people are using it to screen people out as well, aren't they? You know, they use AI to, to sort of assess people on a sort of video interview, ask set questions.
- [47:30]
Jed Griffiths
Right.
- [47:31]
James Reed
Looks at you if you're perspiring a bit or your eyes are dilating. So, you know, this is what I'm hearing. I don't know if it's true, but it frightens me that that might be happening.
- [47:39]
Jed Griffiths
And I've heard similar things.
- [47:40]
James Reed
It's a randomness and craziness of that. Yeah. Doesn't bode well. But you've heard similar things.
- [47:46]
Jed Griffiths
I have, I have. And what do you think about that in other industries as well? You know, you hear people saying, well, I could use AI for this and, you know, I could use AI to, you know, make decisions about whether someone's eligible for, for this program or not. And then I always, my little internal alarm bell goes off at that point. Because one of the things that's exceptionally important when you think about AI is how you approach it from an ethical and responsible point of view. You know, where will you use AI? Where won't you use AI?
- [48:12]
James Reed
That's where you need your philosopher.
- [48:13]
Jed Griffiths
That's right. Well, and that's what you need for an organization. And I think this, you know, going.
- [48:17]
James Reed
Back to how does that work? How do people deal? How do companies address that for your listeners?
- [48:22]
Jed Griffiths
If there's one piece of advice I could give, whether you're an entrepreneur, you know, setting up a business or you're, you know, an established business, set about creating some form of ethics or governance board for AI. AI so that you really have this multidisciplinary senior team of people whose role it is to dictate this is where we're going to use it, and these are the reasons why. And this is where we're not going to use it. You know, these, these use cases are deemed too sensitive or prohibited in our industry and we, we just don't feel comfortable and then build a degree, you know, a set of principles and a degree of transparency and accountability around that. That is the. If you're embarking in the world of AI and you're dealing with people's personal and private data and you're making decisions about the kind of future prospects you need, something like that.
- [49:04]
James Reed
Well, you need to be able to justify a decision, I suppose.
- [49:07]
Jed Griffiths
Well, not just that, but I think people will expect, now society will expect organizations to operate with degrees of transparency and trust and they will need to. Certainly at Microsoft, that's something we treat extremely seriously around how our six AI principles then turn into how we have six AI principles.
- [49:24]
James Reed
It would be helpful just to hear what they are in summary. So if other people are thinking how they to want, want to ensure, protect, secure their business, what they might consider.
- [49:37]
Jed Griffiths
Sure, yeah. So the six principles of AI principles at Microsoft, they came from our ETHER Committee, which is AI ethics in Microsoft. How we think about what's the current state of the art is with AI and how we should think about it. And sort of back in 2017, 2018, when we began this journey, we said, look, if we're going to do this generative AI thing or if we're going to do AI and we're going to serve these products to the world, we need to make sure that we're doing a responsible. So our six principles are fairness, reliability and safety, privacy and security, inclusiveness and transparency and accountability. So those are the six principles and those guide everything we do. Those principles are then translated into operational things that we do at Microsoft to make sure that the products and the services that we build, our software development, you know, how we partner, how we build solutions, we can make sure that we're adhering to those principles, principles in how we want to bring AI to the world.
- [50:28]
James Reed
And they're sort of constant, they haven't changed.
- [50:30]
Jed Griffiths
Yes, those principles are constant. I think that's actually a good point. The principles have been constant. How we've operationalized them has shifted and changed in feedback and you know, from our own learnings and also from, from the market. So we, we actually have something called the Responsible AI standard that we, we had a first iteration of this in 2019 and where we talked about the principles and AI and actually the market gave us some very good feedback and saying, look, you know, essentially these are great principles, but they're not very actionable. And so in 2022, we had a second release of the AI standard. And what we did there was go a little bit deeper into those principles. So they break down into a number of goals that sit underneath each of those and some sort of guidance to help build sort of metrics and guidance for engineering teams. Say, okay, if I'm looking at fairness and I'm building a system, how can I make sure that I'm aligning to that, that, that goal of fairness? Right.
- [51:19]
James Reed
I think when there's so much is changing, which it is at the moment, it's good to have some constant distance. It really helps people.
- [51:24]
Jed Griffiths
Definitely, yeah.
- [51:25]
James Reed
Anchor to certain key things. Are you saying just so I understand that any company that's doing this at any scale should have a sort of policy of that sort with a board or sub board that oversees this?
- [51:37]
Jed Griffiths
I think that's important. I think, yeah. You know, obviously depending on what you're doing and what industry you're in, you know, will dictate the level at which you go to. But I think it's very, very important because, because of the nature of generative AI and its how, how very powerful it is in creating these human like, responses. You know, there's a duty of care that if you're dealing with a, if you're, if you're a B, 2C company and you're dealing with, you know, you know, you're going out to the mass market, you need to make sure that the people interacting with your product are clear where you're using AI, you know.
- [52:07]
James Reed
They should know it's AI.
- [52:08]
Jed Griffiths
No, it's AI. I think that's right. Yeah. You know, we, we certainly, we make that clear. And also if you're using the Microsoft products, you'll see occasionally AI does occasionally make mistakes. You know, generative AI by its very nature is a probabilistic tool set. So it does occasionally return.
- [52:22]
James Reed
It does make mistakes.
- [52:23]
Jed Griffiths
Yeah. People say hallucinate, right? I don't like the term hallucinate. I think people hallucinate AI makes errors, but it will occasionally make mistakes.
- [52:28]
James Reed
Why does it make mistakes?
- [52:30]
Jed Griffiths
Oh, my goodness, how long have we got? No, essentially I'm interested.
- [52:33]
James Reed
But you're all the scientists. Why is it. Because it seems like it.
- [52:37]
Jed Griffiths
So when you think about, it's almost.
- [52:39]
James Reed
Making stuff up if we look at.
- [52:40]
Jed Griffiths
The kind of cool technology, the transformer based technology that things like GPT for instance, generative, pre trained transformer, what it really does in a sort of base form is it's kind of predicting the next word in a sentence. Pretty much like autocomplete on your phone. But it's doing so on steroids. Right. So it's doing that, but it has a great deal of context about that sentence or that paragraph or say the prompt or the input that you've put in. So it's just got a lot more context than your standard sort of autocomplete. But at its heart what it's doing is it's predicting the likelihood of the next words or the next string in the sentence. Much more innovation's gone on since the first, the transformer technology landed a couple of years ago and then now it does quite a lot. It's actually quite complicated in a lot of what we call reasoning at inference time. So that how the models are able to make decisions around that context when you ask it something. But in essence that's what it's doing. So occasionally when you've got subjects where it doesn't have a huge amount of data on or you know, where it perhaps hasn't got that, let's call it statistical background of information to rely upon, occasionally it will hallucinate, as they say, it will create the next word or next string of words or it'll create references perhaps that, that aren't true. Now that's the model in its sort of raw form.
- [54:01]
James Reed
How can you check it?
- [54:02]
Jed Griffiths
Right, exactly. So that's the model in its raw form. What you do, if you think about how you use generative AI in practice, you actually surround those systems with a huge number of safety systems. So other sort of technical measures that you put around the model to check. Right. So you know, groundedness, you know how well rooted is this response in the kind of the user's query. And you can look at sort of harmful or biased information as well. You can do a lot behind the scenes to make sure that the output of that model is actually pretty consistent and safe and everything. That said, occasionally it does make errors, but you can do quite a lot in the safety systems to cut that down. And that's where actually were a tremendous amount of innovation at Microsoft. Microsoft is spent in doing that.
- [54:44]
James Reed
Yeah. So the cost of AI, I mean it started off pretty expensive, you know, to run these great computer systems. It's coming down, isn't it?
- [54:52]
Jed Griffiths
Yeah, that's right, yeah. Like any Technology.
- [54:54]
James Reed
Yeah, but quite dramatically and quite surprisingly.
- [54:56]
Jed Griffiths
Yeah. I mean, it's dropping, you know, massively. And I think. I think that's.
- [55:00]
James Reed
Where does that leave you at Microsoft? Because you've got this huge infrastructure, haven't you? The support.
- [55:04]
Jed Griffiths
Yeah. And we're improving that, you know, infrastructure sort of every year. Absolutely. I mean, in the uk, we've got massive, you know, multiple, multi billion pound investments in building new data centers in the UK to make sure that we're providing the, you know, the right, you know, the sovereign capabilities in, in the data centers in the UK to, to serve the UK market, you know, high.
- [55:22]
James Reed
Is that what people want? They want the data center?
- [55:25]
Jed Griffiths
Well, it gives you that low latency and performance. You can deploy the models close to where the people are. Right. Ultimately, you still have to move electrons over cable. So to, you know, to provide this.
- [55:33]
James Reed
Capability, you have to keep these centers nice and cool.
- [55:36]
Jed Griffiths
Yes. Yeah, absolutely.
- [55:38]
James Reed
So UK is good for that?
- [55:40]
Jed Griffiths
Well, you know, not. Not as most.
- [55:42]
James Reed
We could serve the WHO whole world. It could be a new usp.
- [55:45]
Jed Griffiths
Sadly. Sadly, no, but that's a shame. But you're right, actually, talking about data center technology, there's a huge amount of innovation in that space. People look at the sustainability of data centers. What I love about what we've done at Microsoft and how we've done that is the type of data centers you'll see will vary depending on their geography. So they will make use of the natural environment. In the Nordic Springs, we've got data centers that use geothermal power and then they use much more of the natural environment to create cool. And obviously that's different in hotter climates where, you know, they haven't got that and they need different sort of cooling requirements. And there's a huge amount of innovation in terms of chip cooling and things, and even using AI within the data center to optimize the chip usage as well. So there's a tremendous amount of innovation going into data centers.
- [56:28]
James Reed
So this reduction in cost and the huge infinite number of applications from what we're hearing, means that the agentic age is truly upon us, doesn't it? I mean, it's going to be. Yeah, this is going to be huge.
- [56:42]
Jed Griffiths
It's going to be massive. Yeah, I think it, I think it.
- [56:44]
James Reed
Really change everything, isn't it?
- [56:46]
Jed Griffiths
Well, change a lot of things. I mean, I think, I think to a degree where we won't. It's very difficult to forecast exactly what.
- [56:51]
James Reed
Impossible, I thought.
- [56:53]
Jed Griffiths
Yeah.
- [56:53]
James Reed
I mean, when we started out on the World Wide Web, you know, in the early 90s.
- [56:57]
Jed Griffiths
Yeah.
- [56:57]
James Reed
I mean, no one thought of social media, did they? The consequences of that are huge. So there'll be a lot of things that I guess no one's even.
- [57:05]
Jed Griffiths
I think that's, I think that's right. Yeah. And that's like with any, you know, AI is a general purpose technology. You know, what that means is it can be applied in, you know, many different industries in many, many different way. And some of that sort of unforeseen, but like many general purpose technologies, it creates new jobs and new roles that nobody thought of before. Right.
- [57:23]
James Reed
So if you're a young person listening to our conversation, how would you advise them to sort of get to grips with AI? What sort of things should they be doing? Because it seems to me pretty obvious. I mean, you left a very good job at the Atomic Weapons Institute to get into AI pivoted successfully because you could see this is where the action is.
- [57:40]
Jed Griffiths
Right.
- [57:41]
James Reed
I mean, I think people listening to this will, will be doing the same thing. This is where the action's going to be for, I'd have said decades to come, but certainly the next couple of decades. How do you get started? What's the. Because this is all new.
- [57:55]
Jed Griffiths
Yeah, I think, and it's really interesting because the, maybe the answer to that a number of years ago would have been, you know, go straight into sort of AI development and co development. But actually that, that might, that might not necessarily be the answer. Yeah. And, and it's, you know, I'm not saying that we're not going to need coders, by the way.
- [58:10]
James Reed
You know, certainly I can write good code.
- [58:12]
Jed Griffiths
I can write code. Yeah, but you still need code. You still need to know what good looks like. You know, just, just a quick aside on that. I am a friend who's an author, obviously. Author is getting very worried around, you know, around AI's capability to sort of write, write, copy and text and. But you still need authors, right? You still need people who know what good writing is to, to make sure that we're still, you know, doing that, you know, that that role won't disappear. It will change, but it won't disappear.
- [58:37]
James Reed
No, no, I'm just writing a book.
- [58:38]
Jed Griffiths
Yeah, exactly.
- [58:39]
James Reed
Yeah. That's what you've got to have something that's.
- [58:41]
Jed Griffiths
Say these things are important. I mean, look at what, you know, what sort of mass manufacture did over, over the centuries. We still have artisan furniture makers. Right. You can make, you can make every piece of furniture.
- [58:52]
James Reed
Not as many.
- [58:53]
Jed Griffiths
Right. Not as many things change.
- [58:55]
James Reed
Not many wheel rights. Yeah, that's right.
- [58:56]
Jed Griffiths
No, exactly. Yeah. But a lot of these, a lot of the roles and the jobs.
- [59:00]
James Reed
Yeah. So that's gonna. So the world could be a continuation. But I'm, I'm thinking, you know, if I want to get started, so I should be using the, these apps a lot. I should be thinking about how to interrogate them and learning by trying.
- [59:12]
Jed Griffiths
Yeah. Going back to your question, I've got sidetracked. The sort of skills that you really need to think about are how do you use the technology? Right. So unless you. I guess it depends if you want to go into sort of AI coding, programming. Absolutely. Those traditional routes are still absolutely. Right. Completely valid. But if you're thinking more around the application of AI, then it's perhaps it's a bit different. Right. And perhaps you need to be thinking more around, well, what do I know about particular industries or problems out there? You know, how do I get more immersed in the capabilities of this technology? So a lot of that will depend on you being much more experiential. So the number one thing that I say to anyone who perhaps hasn't ventured into AI is get hold of some tooling and start playing. Because it's the kind of skill set that is learned from experience. You know, you don't sort of sit down and read a manual about generative AI and then get good at using it. You have to use it to get good at using it. And that's because of the nature of the tooling. So if you're looking at, you know, you've got some great business ideas or you think that you can really disrupt your industry or create new value with this tool tool, then the best advice is to try and do that. Right. Try and spend time playing with the technology, look at some, maybe some of the solutions that are out there, maybe look to create some new solutions with. Again, it's lowered the barrier, right, the skills barrier. That's what it's done. In terms of writing code, I mean, certainly as a physicist, I Wish I had GitHub Copilot 10, 15 years ago when I was writing some code, I would have killed Query. I wasn't a great coder as it was, but now it would been have been so much easier to just to use the tool to accelerate my learning. So there's all these, you know, it's an amazing learning tool.
- [60:42]
James Reed
People coming into the job market. What tools might you recommend for people who want to teach themselves a few things?
- [60:48]
Jed Griffiths
Actually at the moment, there's just so much out there, you know, that's Actually free to access on Microsoft's own pages, actually we have something called Microsoft Learn. We've had that for a very, very long time. And actually what people don't realize is that it's free. You know, you can get a lot of this content learning about, you know, our tools and products, but also also were generally about AI products. Additionally, as part of our sort of commitments in the UK and supporting the growth of the UK economy and the diffusion of AI, we had something called the get on Skills program. And we pledged to sort of skill over a million and a half people in AI skills over the last few years. And I think we've hit our target now, which is amazing and we're continuing to do that.
- [61:26]
James Reed
If you want to get on, Get On Skills, how do you do that?
- [61:29]
Jed Griffiths
You, if you go online and look up. Yeah, exactly. You know, get on or AI Skills learning, you'll see a number of sort of free programs that are out there. There is actually a tremendous amount of free Learning on, on AI out there. Even LinkedIn do some amazing courses as well that are, that are free. There's a really good one for business leaders on, you know, if, you know, it's two years in and if you're embarrassed as a senior leader to say, hey look, I, I haven't really been paying much attention to this, but there's a great grounding course on LinkedIn for, specifically for leaders. It's about, I think about four or five hours long. It's a free course. And yeah, there's so much great content out there to give you a good starting point for how to think about this technology. And I think that's the key part.
- [62:05]
James Reed
Yeah. So one of our guests said, you know, the AI wasn't going to take a job, but someone who knew how to use it might.
- [62:12]
Jed Griffiths
Yeah.
- [62:13]
James Reed
And so it's about learning how to.
- [62:14]
Jed Griffiths
Use it and I think that's true. But, but again, you know, I like to, the way my mind works, I like to think by kind of big picture stuff. And if you look back over time and the diffusion of these general purpose technologies, that's, that's always been, you know, whenever the new technology comes along.
- [62:29]
James Reed
Do you think of it as a general purpose technology?
- [62:31]
Jed Griffiths
Very much so, yeah.
- [62:32]
James Reed
What are the general purpose technologies?
- [62:34]
Jed Griffiths
Well, you know, Electricity. Yeah, right, electricity, you know, the Internet, those kind of things, you know, very general, where you can apply them in many different ways. I think Jeffrey Ding has written a great book on this actually the Diffusion of General Purpose Technologies over Time. It's a fantastic read I always like to do a recommendation, but that's good. Yeah.
- [62:51]
James Reed
Try and get Jeffrey into studios.
- [62:53]
Jed Griffiths
And it's a great. It's a great read because it talks about this. Right. You know, the one thing history can teach us is how these sorts of big technology inflection points affect society and the kind of things we need to do and what we can learn from that. Right. And it's the same.
- [63:06]
James Reed
Yeah.
- [63:06]
Jed Griffiths
Yeah.
- [63:07]
James Reed
Well, it's exciting to be living in this moment and you've certainly lifted my spirits around all of this and I think it's. Yeah, the opportunities are vast. So thanks so much for coming to talk to me today.
- [63:18]
Jed Griffiths
Yeah, pleasure. Thank you so much for having me. Thank you.
- [63:23]
James Reed
I'm going to ask you two questions, though.
- [63:25]
Jed Griffiths
Okay.
- [63:25]
James Reed
Which I ask all my guests, and the first question is, what gets you up on a Monday morning? Because we love Mondays here a week. So what gets you up on a Monday morning?
- [63:36]
Jed Griffiths
Well, it's normally one of my young children.
- [63:38]
James Reed
That's a good answer.
- [63:40]
Jed Griffiths
But.
- [63:41]
James Reed
But no, really, what time do they get up?
- [63:43]
Jed Griffiths
Varying. Yeah. Normally. Normally before 6am, some of them, but.
- [63:47]
James Reed
So they'll be entrepreneurs.
- [63:50]
Jed Griffiths
But no, what gets me up on a Monday morning is I feel very privileged to be in the position I'm in now, to be able to work with business leaders and really clever technical leaders from all across the UK and to be able to help and steer and advise how they navigate AI in their industries as they're experts in their industry. So that's an amazing privilege, I think, and I want to make the most of that, to make sure that I'm adding as much value as I can in helping them do that. So that. That definitely gets me out of bed in the morning knowing that, you know, a piece of advice or some guidance that I can give can help members of an industry change a business and do some great work. So that's, you know, that's. That's pretty cool.
- [64:28]
James Reed
Yeah. And the last question is, where do you see yourself in five years time?
- [64:32]
Jed Griffiths
Oh, my goodness. This is. This is literally interesting in this space. I think earlier I said, you know, I've never really had. Had a life plan. I've always sort of just gone, oh, that's interesting. I'll do that. I have that kind of a mind. I'm sort of attracted to things I find interesting in the moment. And so never really had a life plan and sort of looked at things and said, oh, that's interesting. I'd like to be part of that. I don't actually know. I don't know where I'll be in five years. I'd like to think that I'll be able to learn from the experiences I've had now in this career pivot I've had in the last few years and then move on to something that cashes that in and provides more value somewhere else and hopefully doing something, something interesting.
- [65:09]
James Reed
Yeah, I got a feeling you'll be somewhere Interesting in 5 years time. We might have to invite you back to find out where that is.
- [65:14]
Jed Griffiths
Okay, let's do that. Put a date in the calendar. We'll get AI to all this. Thanks very much.
- [65:20]
James Reed
Pleasure talking to you.
- [65:21]
Jed Griffiths
Thank you.
- [65:23]
James Reed
Thank you, Jed, for joining me on all about business. I'm your host, James Reed, chairman and CEO of Reid, a family run recruitment and philanthropy. If you'd like to find out more about Reed, Jed or Microsoft, all links are in the show notes. See you next time.