Investors who have experienced a major correction in a holding that aims to harness game-changing technology shouldn’t grow disheartened as this is part and parcel of the hype cycle and may be the perfect time to buy in, according to Nick Hartley, co-head of active equities at LGIM.
Hartley said investors in artificial intelligence (AI) should strap themselves in for a bumpy ride as the sector could be teetering on the edge of the precipice that characterises the early share price journey of any technology that claims to be “the next big thing”.
Spending on AI-focused technology is forecast to reach €58bn by 2021, and 75 per cent of respondents to Arm Holdings’ 2017 Global Artificial Intelligence Survey said AI would be implemented in their company over the next three years.
However, Hartley said it is vital when investing in much-hyped technology that investors separate fact from fiction and work out what is already priced into shares, for example.
The manager said the Gartner Cycle is one of the most important tools for working this out.
“Gartner is an IT consultancy and focuses on this more for its corporate clients,” he said, “but it also works very well from an investor’s perspective.
“It shows that typically you can make a lot of money either if you are in very early and you ride the hype, or if you get past the peak and you buy at the trough of disillusionment.”
“So alarm bells are flashing when you look at the peak of expectation in AI – we’ve got deep learning, virtual assistants, machine learning, autonomous vehicles, smart robots. A lot of the things that are associated with AI from a Gartner perspective suggest this is peak hype-cycle right now.”
Hartley said the way that investors first reacted to the internet perfectly follows the Gartner Cycle – the huge amount of hype in the late 1990s created an enormous stock market bubble which then burst, bringing expectations about the technology crashing down with it.
However, he pointed out that if you overlay Amazon’s share price on to the Gartner Cycle, for example, it shows the hype is utterly insignificant compared with the value created.
Amazon's share price since launch
Source: Google Finance
“One of the quotes these guys [LGIM’s PR team] wanted me to use but I refused to because it is such a cliché is that ‘people overestimate technology in the short term and underestimate it in the long term’,” he continued.
“The reason it is so overused is that it is so true and I suspect that is probably the case here.
“If I had to summarise, there is a lot of hype, but is that hype going to affect companies’ earnings in the next year or two, even for the companies that are front and centre of the opportunity? Probably not. But is this a potentially significant investment theme over the next 10 years? Perhaps.”
Hartley said there are three components critical for AI to become financially successful: the technical capability for AI and machine learning, access to a large volume of data from which it can learn, and the ability to deploy and implement AI at scale, and then ensure it keeps learning and improving.
The manager said the final step tends to be the largest barrier, pointing to the example of IBM when it tried to apply its machine-learning tool Watson to cancer diagnosis.
“IBM Watson acquired an extensive database of medical images, clinical trial data and historical patient diagnoses, as well as partnering with some of the leading academic hospitals in each field to help ‘train’ Watson,” the manager continued.
“However, adoption of this service has been disappointing so far. Its oncology product is used in only 50 hospitals, despite IBM’s confidence that the diagnoses and treatment plans recommended by Watson generate superior outcomes for patients.
“For IBM, the challenge here is to deploy its intelligence at scale. It has the technology capability, the industry expertise and the data, but lacks the avenue to deploy its insights at scale on the frontline of cancer – IBM doesn’t own the hospitals.”
The application of AI has been far more successful in the travel sector, with the changing nature of how people book their holidays meaning the technology has become indispensable to the industry. For example, 20 years ago, the ‘look to book’ ratio was 10:1 – meaning 10 enquiries would result in one booking. With the advent of the internet, that ratio has risen to 1,000:1. For a single return trip, such as London to New York, there are 600,000 possible trips, with at least 10 different fare classes per trip and about 5,000 possible fare combinations.
Hartley said that given the mathematical challenge, working out which options to display to the consumer based on search criteria is vital – and this is where IT provider Amadeus comes in.
“The company has used AI and machine learning to improve the user experience, using the predictive capability of its algorithms,” he explained.
“As a technology company focused solely on the travel vertical, Amadeus has both expertise and significant volume of data from which to work (Amadeus processed more than 595 million travel agency bookings and boarded over 1.3 billion passengers in 2016).
“Crucially, though, by being placed firmly at the heart of the travel ecosystem, it has also been able to deploy its learnings at scale: as a marketplace model, its use of AI increases its relevance to travel providers by improving the conversion rate (the look to book) and supports their core business.”
Data from FE Analytics shows that 24 funds in the IA universe hold Amadeus in their top-10.
Hartley finished by saying there is an “elephant in the room” that needs to be discussed when talking about AI, pointing to another survey conducted by Arm Holdings in 2017 asking which of three AI-related scenarios concerned respondents the most.
“What people were most worried about was AI machines being hacked and losing large amounts of personal information,” he explained.
“On a relative basis they weren’t concerned at all about machines becoming more intelligent than humans.”
He compared this with the views of Elon Musk, the founder of Tesla, which relies heavily on AI. Musk said: “I think we should be very careful about artificial intelligence. If I had to guess at what our biggest existential threat is, it’s probably that. So we need to be very careful.”
The late professor Stephen Hawking went even further, saying: “The development of full artificial intelligence could spell the end of the human race.”