Investor Download: the future for AI – Schroders

Alex Tedder, Head of Global and Thematic Equities, and Adelina Balasa, a Senior Cloud Solution Architect at software giant Microsoft, help tell the story of AI and answer the big questions about its future.
You can listen to the podcast by clicking the play button above. You can watch most recordings of the podcast on Schroders Youtube channel.
You can also subscribe, download, rate and review the Investor Download via Podbean, Apple Podcasts, Spotify, Google and other podcast players. New shows are available every Thursday from 5pm UK time.
You can read the full transcript of the podcast below:
Welcome to the Investor Download the podcast about the themes driving markets and the economy now and in the future. I'm your host, David Brett.

It's barely been six months since our world was perhaps changed forever.

Chat GPT, maybe you've heard of it? If you haven't, then get ready, because this promises to be the viral sensation that could completely reset how we do things. It is the embryonic version of online artificial intelligence.

OpenAI said that it's introducing its Chat GPT app to iOS and iPhones and that'll open the door to more users, more headlines as we're getting used to.

Google says it's launching its own artificial intelligence powered chat bot to rival Chat GPT, which mimics human writing on demand.

Launched on November 30, 2022, Chat Generative Pretrained Transformer, or Chat GPT as it's more commonly known, took the world by storm.

You have to be living under a rock if you haven't heard of Chat GPT. An American firm called OpenAI came out with this in just November last year. And in just about 50 days, it has gotten everyone gripped.

Chat GPT, a generative artificial intelligence focused on the creation of new content, became the fastest growing consumer application in history, hitting 100 million users within two months, double the speed of TikTok. Its success swelled the valuation of its developer OpenAI to nearly $30 billion. And it contributed to making a huge success of others overnight.

Welcome back to the exchange. Nvidia should change its name to nvid AI, or maybe it doesn't need to, as it's now become synonymous with the booming technology. Shares rocketing 27% on a blowout quarter.

So this is a stark reminder that we are in the middle of a massive AI gold rush right now and Nvidia has all the picks and shovels.

So you've got these big winners in the public space, just a few really big winners that are going to do really well out of this. And we can already see that.

That's Alex Tedder, head of Global anthematic equities at Schroeders.

So the market has been very efficient in pricing, in what this could mean. What the market hasn't done yet is taken a step back and thought about, okay, if this stuff really does what you guys say it can do, what will that mean for net value add in different sectors, different industries, and at the corporate level, that's where it gets really interesting.

Chat GPT was not the first publicly released artificial intelligence platform, but it is notable for being one of the most advanced and widely used AI platforms for generating human like responses to text prompts. However, the speed at which it has been embraced by the public and the pace at which the platform is learning has led to some dire warnings.

There is a risk that AI could lead to human extinction, and mitigating the risk should be a global priority. My worst fears are that we cause significant, we the field, the technology, the industry, cause significant harm to the world. If this technology goes wrong, it can go quite wrong.

The most nightmare scenario I can imagine with AI and robotics is a world where robots have become so powerful that they are able to control or manipulate humans without their knowledge.

Whether you feel excited or you feel apprehensive, we are shaping this future right now.

That's Adelina Balassa, a senior cloud solution architect at software giant Microsoft, which invested $1 billion in OpenAI back in 2019.

This technology is not going back. It's not going to disappear. It will be adopted like the previous ones.

So with the chat out of the bag, so to speak, along with Adelina and Alex, we're going to look at how AI is developing, what it might mean for society, and the potential opportunities for investors.

On Apple podcasts, Spotify, or wherever you get your podcasts, you're listening to The Investor Download.

So what is AI?

It's the internet, but bigger. And I think there is no one right answer to define artificial intelligence, mainly because we have not yet defined what intelligence is. But to put it into rough terms is the human's intention to replicate human intelligence, but in a computer. So building a machine that can replicate our own intelligence and even surpass it.

AI has been around for centuries. Early examples date back to ancient Greek mythology and the concept of automata, which means self acting. However, the modern field of AI began to take shape in the mid 20th century. The first neural network model was developed in 1943 by Warren McCullough and Walter Pitts. And the term artificial intelligence was coined in 1956 by John McCarthy, who is widely regarded as one of the founders of the field. In the decades that followed McCullough, Pitts and McCarthy, AI development continued at a pace. Arguably the most influential person in the space over the last 40 years has been Jeffrey Hinton. Widely regarded as the godfather of AI, Hinton's been developing algorithms key for training artificial neural networks since the 1980s. And he's been a leading proponent of deep learning at company such as Google, which has led to a significant breakthrough in areas such as image and speech recognition. But AI really captured the headlines in 1997, when then world chess champion Gary Kasparov was defeated by an IBM supercomputer called Deep Blue in a six game chess match.

Gary is… are we missing something on the chessboard now that Kasparov sees, he looks disgusted, in fact. And he should get an Oscar and he should get $300,000. Kasparov, after the move, C Four has resigned.

To win against Kasparov, Deep Blue used its sheer computing power to overwhelm him – 100 million to 200 million chess moves per second.

What he did afterwards is that he actually learned how to work together with a chess machine. So have player and chess computer versus player and chess computer, which was probably the best thing he could do. And then afterwards, we had Google and their deep learning algorithm, where they beat Lee Sedol at Go.

Go is a nation board game that originated in China about 3000 years ago. It has a near infinite number of moves and is played with intuition as much as calculation. Mr Lee is a professional Go player of multiple international championship titles. This five game match between Mr. Lee and AlphaGo was seen as an important event in judging the progress of artificial intelligence. As Go had been widely thought to be too complicated for computers to challenge top professionals…

While chess has ten to the power of 40 possible outcomes, go has ten to the power of 80 possible outcomes.

And that was the neural networks, and that was showing the world what we can do with neural networks.

A quarter of a century later, Chat GPT was unleashed on the world. How Chat GPT has changed the game and how AI could impact our future, that's coming up in part two of the show.

Get in touch with us by email at or visit our website,

Despite Chat GPT being just over six months old, it sparked a sudden rush of concern among experts about the pace at which AI is starting to move.

I think language models have been around for a while. The factor that made it so widely available is the fact that Chat GPT was launched publicly and anyone all over the world now has access to this technology.

Because so many people are using the Chat GPT app, it's allowed the model to grow exponentially. And for some, that's too frightening a pace. The godfather of AI, Jeffrey Hinton, suddenly quit Google this year, citing concerns over the flood of misinformation and the existential risk posed by the creation of true digital intelligence.

It's technology that could be superior to the human brain, and one of its pioneers now says part of him regrets his role in creating it. 75 year old computer scientist Jeffrey Hinton says he quit his job at Google so he can independently share his concerns about AI technology.

But in a lengthy interview with the New York Times, Dr. Hinton said he now regretted his work and is worried that AI technology will flood the Internet with misinformation.

Meanwhile, Elon Musk, Steve Wozniak and hundreds of experts signed a petition asking for a six month pause in artificial intelligence research, citing potential dangers to humanity.

It's obviously raising alarms. It's meant to do so. 22 words. Let's read it. Mitigating the risk of extinction from AI should be a global priority, alongside other societal scale risks such as pandemics and nuclear war.

So far, so terminator…

3 billion human lives ended on August 20, 1997. The survivors of the nuclear fire called the war Judgement Day. They lived only to face a new nightmare the war against the machines.

But let's not get too far ahead of ourselves. The most immediate fear for people is that the machines will take over their jobs.

That certainly is a view that could happen, but it's not set in stone. We don't want that to happen, actually.

People's fears might be overblown. A report by PwC for the Department for Business, Energy and Industrial Strategy, for instance, estimated around 7% of existing UK jobs could face a high probability of automation in the next five years. Even then, that doesn't mean that humans won't be needed as part of the process.

This is where our own CEO's view is that this should help people do their jobs better or eliminate boring jobs, but create jobs where actually human creativity, and that part of the intelligence that we cannot describe or we cannot have machines replicate it. And there is a statistic that says 65% of the knowledge workers actually prefer to delegate some of their work to AI to be more productive.

A knowledge worker is a professional who's primarily engaged in the analysis and manipulation of information as a core part of their job, and they typically work in fields such as finance, law and healthcare, among others.

But in terms of knowledge workers out there, our own statistics are that there is so much time spent or so much time wasted finding the right knowledge that you need to do your job. And what we see here and this hype about generative AI, the positive impact of this AI is that it actually helps knowledge workers find the information that they need much faster. And leaders are twice as likely to be more concerned with employee productivity than cutting down the jobs. So of course you can automate as much as you can, but when it comes to the bottom line, you cannot possibly have a big enterprise or a successful company where you just rely on AI. And actually one of the best practises, especially in large language models that we recommend, is that you should always have a human in the loop and do not leave AI to make decisions for you. Do not automate 100% and always design from the very beginning with a human in the loop.

And far from causing a jobs market crisis, Alex Tedder thinks that AI could actually contribute to helping solve one, one that we're experiencing right now.

From my standpoint, if you take a step back, you think about the west. In the west we have a labour shortage, generally speaking, and it's only getting worse because of demographics. And actually in Japan parts of the east as well.

Japan is on the brink of failing to function as a society. A stark warning from Prime Minister Fumio Kishida, who said the country had no time to lose to reverse its population decline. To address a growing labour shortage in the ageing nation, the government has slowly started relaxing its tough immigration policy to bring in more foreign workers.

It's estimated that Japan may face a shortage of more than 11 million workers by 2040, according to Recruit Works Institute an independent think tank which underscores the economic challenges the nation faces as its population ages rapidly.

Since the Pandemic, hundreds of thousands of people have dropped out of the workplace. They've become economically inactive in the jargon and that is contributing to a genuine problem. Companies simply cannot fill the vacancies for the jobs the economy requires to grow and recover.

In the UK, the percentage of businesses experiencing a shortage of workers has been around 15% since October 2021. That's according to the Office for National Statistics. A problem brought on by Brexit and demographics and exacerbated by the Pandemic.

But we're going to begin this hour with a not so bravo topic. We're talking about jobs and a major hiring cris. A problem really bigger and older than the great resignation you've heard so much about. It's a problem you're not going to find in the unemployment rate, which is, of course, at near record lows. And it's because a large number of American men, in particular men in their prime working years, are actually not working and they're not even looking for work. The result is a bit of a mystery and also a major hole in the American economy.

In the US, about 3.5 million workers are missing from the workforce. That's according to Federal Reserve Chairman Jerome Powell.

So many economies have got a labour shortage, right? So from my standpoint, this couldn't come at a better time because this will allow smaller number of people to be more productive, and that's what you need in the west and in developed economies. And then in emerging economies, what it does is it allows people who actually don't have or haven't had access to a lot of the things that you have in the west in terms of the databases, the knowledge sets, the institutions to access stuff directly and to use it directly in a way they couldn't before. So my view is going to contribute to the raising of living standards in developing markets very substantially going forward.

But it's not just job security people are worried about misinformation and the handling of data is a big concern too. A Forbes Advisor survey showed that 76% of consumers are concerned with misinformation from artificial intelligence tools.

There is the responsibility of the government, there is also shared responsibility with all of the organisations that use AI. But I think many organisations are wondering, what is the ethical way to use it? How do we use it in the responsible way? What are our guidelines? How do we do it? And so I think it's the governments that need to put that in place. And actually, quite a lot of guidelines are already in place by in Europe, the EU AI Act, which is in draught. In the UK, we have an AI white paper and transparency best practises, so quite a lot is already there. But I do think that governments need to make it an actual legislation that we need to follow in order to have the trust in AI. If you don't have trust, you can't progress. And I look at AI as the top of the iceberg, and there is so much underneath that is unseen. And actually these large language models have been built using open source data from the Internet, but it doesn't help you with data lineage. This is why what we actually want and the patterns we are building is to have an equivalent of Chat GPT, both on your own data to help you with that trust, and you must implement a data lineage.

You must say, okay, I have this answer, but this is the document where my answer is coming from. This is the pattern that we advise most of our customers who adopt large language models to implement, to adopt.

Whether or not you fear AI, it's here to stay, and it's going to have a dramatic impact on our economy and our investments, and that's what we'll cover. In the final part of the show.

There's some big figures being banded about how much AI will contribute to our economy, and we'll get to those shortly. But let's take a step back and let's look at some smaller figures which are still pretty big. Alex Tedder believes there's up to $500 billion of annualised potential savings by applying artificial intelligence to do something that a knowledge worker is currently doing. But that's just the tip of the iceberg.

So the way the market's looking at it right now is that four to 500 billion is the addressable market. That's what annual sales of software and semiconductors could be that are linked directly to the implementation of artificial intelligence. Four to 500 billion annually, which is a big number. But that is really just a subset, right? Because what you have on top of that is the fact that this tool is a productivity tool primarily that allows you to do lots of other things that you couldn't do before. And so from an economy standpoint, the implications are much, much bigger than four to 500 billion annually.

How big? According to a recent report by PwC, AI could contribute up to $15.7 trillion to the global economy in 2030. To put that into perspective, that's more than the current output of China and India combined.

So what you can see is you very quickly get to big numbers that are very attractive for companies. It's all about how enterprises use this. And when you start to think about that big picture and how it might map out, you can see why the market's so excited about this thing. I mentioned the four to 500 billion of annual revenues that will come directly from AI. If we sort of capitalise that at a reasonable number, you're looking at about 2 trillion of capitalization that's related directly to AI. If we think of Microsoft, the size of Microsoft today, and indeed the size of Nvidia today, which has just doubled or more than doubled this year. It's already discounting a lot of that 2 trillion of incremental. So the market has been very efficient in pricing in what this could mean from the point of view of revenues in the semiconductor sector and the software sector. What the market hasn't done yet is taken a step back and thought about, okay, if this stuff really does what you guys say it can do, what will that mean for net value add in different sectors, in different industries and at the corporate level, that's where it gets really interesting.

And whether you're active or passive, it will still play, right? It'll play into how people allocate capital between different asset classes and different regions and different sectors. And that's where it gets interesting is that there'll be winners and losers at the corporate level from this in terms of how they adopt that AI and how they implement it, how successful they are in improving productivity and improving creativity. There's going to be big differences in how that comes out at the corporate level and that's where I think the opportunity is from an active passive standpoint. So you've got these big winners in the public space, just a few really big winners that are going to do really well out of this and we can already see that but there aren't that many and there aren't many other ways to get exposure to AI in the public equity space. The interesting part is on the private part, that's where you've got all these startups.

So AI's potential is huge for us, the economy and investors. But what will the future look like?

These models are fantastic. I mean they are game changers, no question. Things are going to look very, very different. But ultimately the way to use them will still be you'll still be up to humans to use them intelligently. In other words to make decisions based on them. The machine's not really going to do that for them, not for many, many years to come. I think there are reasons wherever I look across multiple industries and there's sort of a sector agnostic view which is it's going to help productivity broadly in the way we've talked about. And then there's the sector view. There are multiple industries where it's going to change things dramatically. Healthcare, which is another one, coding is another one we haven't really talked about. There are just some really big changes to come. So you've got to be optimistic about that and you got to think big because the implications from that are substantial.

Well, that was the show. We very much hope you enjoyed it. If you want to find out more please head to and we're endeavouring to record as many of these shows in the studio on video. And if you want to watch them in their full unabridged version then go to Schroder's YouTube channel. If you want to get in touch with us, it's and remember, you can listen, subscribe and review the Investor Download wherever you get your podcasts. New shows drop every Thursday at 05:00 p.m. UK time. But above all, keep safe and go well. Cheers.

The value of investments and the income from them may go down as well as up, and investors may not get back the amounts originally invested. Past performance is not a guide to future performance. The information is not an offer, solicitation or recommendation of any funds, services or products, or to adopt any investment strategy.

Please remember that the value of investments and the income from them may go down as well as up and investors may not get back the amounts originally invested.
This marketing material is for professional investors or advisers only. This site is not suitable for retail clients.
Issued by Schroder Investment Management Limited, 1 London Wall Place, London EC2Y 5AU.
Registered No: 1893220 England. Authorised and regulated by the Financial Conduct Authority.
For your security, communications may be recorded or monitored.
On 17 September 2018 our remaining dual priced funds converted to single pricing and a list of the funds affected can be found in our Changes to Funds. To view historic dual prices from the launch date to 14 September 2018 click on Historic prices.