Focusing on questions raised by the AI Pioneers in Investment Management report, this publication explains how cross-functional teams can help investment professionals and organizations develop investment processes that incorporate AI and big data.
Where should our organization begin on its artificial intelligence (AI) journey? What is my role in that process, and how should I prepare myself for it? If these questions have been lingering in your mind, then this report is for you.
We have been getting these questions the most from all over the world since the AI Pioneers report was published two years ago. Our data suggest that more and more investment firms and professionals are now convinced that AI and big data will play an important role in the investment process, so naturally, more and more people in the profession will be asking these questions, if they have not been doing so already.
We attempted to offer a straightforward answer in our previous report. The solution seemed obvious, yet we are even more convinced now that our approach is the right one, based on our field research and survey data. Over the past two years, we have seen so many examples of firms that have followed this approach succeeding in their AI and big data adoption efforts, and almost as many examples of firms failing that have not followed this approach. The approach is what we call “T-shaped teams.”
This report draws on extensive CFA Institute field research to highlight how investment organizations can put themselves on a path to successful AI and big data adoption. Developing cross-functional T-shaped teams that improve collaboration between the investment and technology functions, accomplished by building on individuals’ T-shaped skills in investment and data science, has enabled investment organizations to successfully adopt AI and big data.
The report also illustrates the T-shaped-team approach to AI and big data adoption in investment firms and how roles change across functions in the T-shaped teams from early to intermediate and advanced stages of adoption, using case studies on three firms of different sizes and with different investment approaches. It provides a how-to menu for aspiring investment organizations and professionals to start building the relevant organizations and skill sets that will help them succeed on their AI journey.