As with many conversations I have with investors these days, this one quickly turned to artificial intelligence (AI). The recently retired fund manager I was talking to put it well: ‘a car won’t go by itself; it needs to be driven or at least to be told where to go. But if you want to travel to the next town, it’s a lot easier by car than on foot.’
And that is the nub of the AI question for high-value-added intellectual activities like investment. It’s not really about whether the AI can do it better than the human, but how the AI can help the human to do it faster, more accurately or at lower cost.
A lawyer at the same gathering added that, when he started out, a key part of the trainee’s job was ‘discovery’ - poring over reams of documents to find the information for their boss to interpret. Same thing in investment - where, quaintly it now seems, a company I used to work for had the catchline ‘the information advantage’. By that, it meant a big team of numerate but relatively unskilled youngsters trawling through annual reports to populate a database with financial ratios that in turn enabled investors to do the real work of picking stocks.
One of the most interesting potential uses of AI is in the expensive, resource-heavy business of investment analysis. Can the machines really do it better? The answer is both yes and no.
The reality of that ‘information advantage’ was that it was the difference between a little bit of pretty basic knowledge and none at all. The effort that went into generating that marginal edge was significant, expensive and time-consuming. It is work that AI promises to do in a fraction of the time for a fraction of the cost. Like the thousands of people who used to work with horses in nineteenth century London or New York, those data grunts will have to find a new way to earn a living.
So, AI is potentially a labour-saving device - a multi-purpose vacuum cleaner or dishwasher. Another way in which it could improve our lives as investors is by eliminating many of the unhelpful behavioural biases that cloud our ability to make good decisions. People are generally more interested in stories than data. AI doesn’t care.
A recent study of AI and stock picking from Chicago University’s business school tested whether the revolution could move yet further up the food chain than the data gathering that provided my former employer’s information advantage. It looked to see if AI could take on the analysts looking to turn basic financial data into predictions about the future direction of corporate earnings. This is a key part of the investment process for active fund managers, providing the raw material for their stock selections. The study found that machines did it slightly better.
More interestingly, it found that portfolios constructed using those earnings predictions performed better in a statistically significant way too. It’s early days yet, but the jobs at risk in a whole range of professional settings are getting progressively more senior, and worryingly quickly.
One danger of AI is that it makes the complex business of managing our money seem easier than it probably is. Ask a simple question of an AI tool and it will, as if by magic, come back with an answer that appears to be your silver bullet. You want ten income stocks with a dividend yield above that on a cash fund? Here you go. A portfolio of growth stocks trading at less than 10 times expected earnings? Try these.
Actually, this is not new. Thirty years ago, the first screening software emerged that allowed investors to plug in a set of criteria and spit out a shortlist of potential investments. The problem for most of us was the cost of these services. AI democratises the process. But it also turns it into a black box. I trusted the numbers that underpinned my Online REFS stock screening software because I could see my young colleagues putting them into the system. When I ask Chat GPT a question, I have absolutely no idea where it has gone to find the answer.
AI plays on our predilection for shortcuts. We want that list of ten stocks to be the answer, so it is tempting not to ask too many questions. But as they used to say in the earlier days of computing: garbage in, garbage out.
I am excited by what AI promises for investors, but I am also relieved it arrived at the end of my career and not the beginning. Many of the things I have been paid to do over the past 35 years or so are of little value today. To continue the horse analogy, I’ve adjusted a lot of bridles and cleared out plenty of stables. Now I need to understand internal combustion or move aside.
I am confident, however, that there will always be things that people do better. We are social animals. I want the investors managing my money to be AI-enabled but human. I want my financial adviser to ask after my kids. I don’t just want the car, I want someone to show me how to drive it.
The AI revolution is at least as disruptive as the internet boom that preceded it. It will be divisive. It is great news for a small number of people who are already highly skilled and highly paid. It will be painful for a much greater number whose contribution is no longer so highly valued. Winner takes all is not a recipe for social cohesion. But it’s not going away.
Tom Stevenson is an investment director at Fidelity International. The views are his own.
