Here are the AI developments that finance pros should be tracking

Artificial intelligence and machine learning are rapidly redefining the financial landscape, unlocking new opportunities but also introducing complex challenges for financial institutions, investors, and regulators.

“This is definitely not business as usual,” said Andrew W. Lo, a professor of finance at the MIT Sloan School of Management and the director of the MIT Laboratory for Financial Engineering. “We’re living through an inflection point in technology, but what exactly is that inflection point? And when and how will it impact specific business lines and companies?”

Lo’s new executive education class — Artificial Intelligence for Financial Services: Tools, Opportunities, and Challenges — is designed to help decision makers navigate the changing landscape. The course, which features a cross-disciplinary group of faculty members and experts, covers practical applications across the buy and sell sides and the banking, insurance, and risk management sectors.

In a recent conversation, Lo outlined some of the topics that he believes financial professionals should be tracking now:

In sum, Lo’s course aims to give participants an idea of where AI and financial technology are headed in the next five years so that they can better assess how new tools and technologies may reshape products, markets, and organizational capabilities.

“We need to understand not only the pace of progress but also ways to extrapolate the impact of AI on our professional and personal lives,” Lo said. “There will be big changes coming down the pike.”

Andrew W. Lo is the Charles E. and Susan T. Harris Professor at the MIT Sloan School of Management and the director of the MIT Laboratory for Financial Engineering. His recent projects include an evolutionary model of financial markets based on his Adaptive Markets Hypothesis; new financing methods and business models for accelerating biomedical innovation; quantitative approaches to deep-tech investing; applying AI, especially machine learning and LLMs, to financial advice; quantamental investing; and health care finance. His most recent book is “The Adaptive Markets Hypothesis: An Evolutionary Approach to Understanding Financial System Dynamics.”