Artificial intelligence (AI) has led to innovations and changes in investment management. The technology itself is new and requires massive amounts of data to make decisions, but the investment decisions themselves are often based on the fundamentals that are core to the tool kits used by most investment professionals. The choices for investment and asset management in the age of AI continue to increase, leaving investors with a lot of opportunity today—and in the future.

The investment techniques used in pure AI strategies would be familiar to investment professionals. Their added advantage that the machine or system is able, quickly, to digest tremendous volumes of data and continually learn, with most systems looking for data patterns that provide an investment signal. Some of these patterns are built on traditional technical analysis, such as moving averages and relative strength index, as well as more fundamental techniques like Sharpe ratios, beta, short interest, and correlations.

In many ways, the style of investing used by AI strategies is similar to many quantitative strategies. The core difference with AI-based investing is that the system not only has the ability to learn from new data but also has the discretion to invest as well as change the approach in changing market conditions. Traditionally, this last step has some form of human intervention and can be filled with tremendous investment bias, which often detracts from a manager’s performance.

One downside to AI-based investing is that these new technologies come with limited historical performance; this is particularly relevant for today’s investors, who have been experiencing a sustained bull market. The AI investment performance in a sustained bear market still needs to be proven.

There are also the pessimists who say that 90,000 asset management jobs will disappear as a result of AI by 2025. However, the reality is more likely that the skill set required will drive a different labour force adding technology roles and shedding more traditional finance and middle management roles.

AI investing is shifting the asset management industry around the world. The number of firms using it continues to grow, with large asset managers now investing heavily in the space. In Canada, however, a host of innovative smaller firms have entered into the AI investing space with technology-heavy offerings. As these firms drive forward with AI investment strategies, their strategies will be critical to watch.

Vancouver-based Responsive, for example, is an AI-driven wealth manager that offers managed investment accounts for both passive and active data-driven portfolios. They are using AI to monitor signals and make investment decisions using ETFs as their core asset. Toronto-based hedge fund manager Castle Ridge Asset Management is another example, coining itself as a firm where “machine learning meets portfolio management.” Its AI-based system is programmed to discover specific and sometimes unique market patterns. The signals anticipate events like strong earnings and stock acquisitions, allowing the fund to position ahead of the anticipated event, reaping any potential benefit.

For Canadians who prefer to manage their own portfolios through ETFs, Horizons launched its first AI ETF (TSX: MIND) last November. This is a 100 per cent AI-driven ETF that overweights and underweights regional, country, and index ETFs with monthly rebalancing. It is able to digest large quantities of data, and monitors more than 50 investment metrics to provide signals. With the launch of MIND, Horizons has brought AI within reach for almost all investors.

Investing in the companies that supply and service AI itself requires a more traditional lens, essentially using a fundamental approach to single-stock investing. The hardware side includes semiconductor firms, who are major suppliers of graphic processors; the software side is filled with large and small tech companies that are using data in innovative ways.

With increased choice, more innovations, and some research, investors are likely to benefit from AI’s growing importance across the financial industry —and particularly in asset management.