Artificial Intelligence (AI) and Future Retail Investment

This paper evaluates artificial intelligence's (AI's) foray into financial markets and the resultant implications for theory and practice. I argue for reevaluating mainstream financial theories and proactively building governance frameworks. I also advocate for external audits and oversight that factor in retail investors' interests. The imminent realities of an AI-dominant trading landscape necessitates reconceptualization of market efficiency as a spectrum. Adaptive systems-centric thinking offers promising pathways for future theory-building. Behavioral and ethical disciplines provide important fodder for understanding and modeling the increasingly complex and multi-layered human-AI interaction, ensuing biases, and ethical matters. In governance, I propose controlled testing environments via regulatory sandboxes. I call for retail representation during the oversight process to minimize bad quality training data and curb model biases. Meanwhile, resources need to be channeled towards AI-aware financial literacy programs. Strategic safeguards are also critical for balancing the promise and risks as AI reshapes investing. Lastly, I press for greater algorithmic transparency and proactive regulation and catalog research areas fertile for transdisciplinary and cross-institutional exploration