Human behavior vs Artificial Intelligence’s logics: new evolution trajectories in the context of Asset Management

Abstract

Due to its revolutionary premises, the implementation of Artificial Intelligence (AI) in the financial services’ context is generating wide hype both among academics and practitioners. However, in many financial services, AI takes the form of incremental innovation rather than disruptive innovation: the aim of this work is to shift attention on the area in which the AI adoption can have massive disruptive potential for the entire financial system, i.e. the Asset Management field. Here, AI’s adoption affects the investment decisions process, which is at the base of the financial system’s primary function, i.e. the transfer of resources between economic subjects. For the first time, it is possible to fully replace human investors with AI-based computerized agents, which can consistently overcome human cognitive faculties in terms of reasoning, problem-solving, learning but also creativity. All this is not addressed today by the academic literature, thus resulting in a great research gap that needs to be addressed. Specifically, this work will define a theoretical framework to fill this gap: through the theoretical analysis of strengths and weaknesses of AI-based computerized investors compared to human investors, this work finds and provides new AI’s evolution trajectories in the Asset Management field for the next future.