Man vs. Machine: The Influence of AI Forecasts on Investor Beliefs

Abstract

Do investors trust an AI-based analyst forecast? We address this question through four incentivized experiments with 3,600 U.S. participants. Our findings highlight that, although investors update their return beliefs in response to the forecast, they are less responsive when an analyst incorporates AI. This reduced trust stems from a lower perceived credibility in AI-generated forecasts. We reveal other important nuances: women, Democrats, and higher AI literacy investors are more responsive to AI forecasts. In contrast, AI model complexity reduces the probability of return updating. Additional manipulations show that forecast providers do not amplify reactions to their content. Overall, our findings challenge prevailing notions about AI adoption in financial decision-making.

Keywords: Artificial intelligence, behavioral finance, analyst forecasts, ChatGPT, trust, experimental economics, asset allocation, return beliefs, gender differences, financial literacy, AI literacy, financial decision-making, Expected returns, AI

JEL Classification: G02, G11, G12, G51, G53, M41