So what is delaying the adoption of AI in industries such as finance and investment management? An exploration of the asset management industry may provide some answers. Machine learning at its core enables us to take vast amounts of unstructured data, organize it, and translate data into recurring patterns. The patterns are then used to conduct deep analysis and draw insights. In case of the financial industry, the insights are further used to predict upcoming events, drawing on the predictive and prescriptive nature of AI.

Early efforts to apply AI to investing have proven to be largely successful. A recent report by Eurekahedge noted that their AI/Machine Learning Hedge Fund Index had outperformed their overall Hedge Fund Index by nearly 200bps per annum over the past five years (annualized returns of 7.35 percent vs 5.51 percent). Institutional Investor Alpha's annual list of the highest-earning hedge fund managers also bears this out, as the majority of the managers in the top 10 (such as Bridgewater Associates, Citadel, the D.E. Shaw Group, Millennium Management, etc.) are known to incorporate AI into their investment processes.