Working Paper: NBER ID: w29995
Authors: Joshua S. Gans
Abstract: The adoption of artificial intelligence (AI) prediction of demand by a monopolist firm is examined. It is shown that, in the absence of AI prediction, firms face complex trade-offs in setting price and quantity ahead of demand that impact on the returns of AI adoption. Different industrial environments with differing flexibility of prices and/or quantity ex post, also impact on AI returns as does the time horizon of AI prediction. While AI has positive benefits for firms in terms of profitability, its impact on average price and quantity, as well as consumer welfare, is more nuanced and critically dependent on environmental characteristics.
Keywords: Artificial Intelligence; Monopoly; Demand Prediction
JEL Codes: D21; D81; O31
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| AI adoption (C45) | transition from uncertainty to certainty in demand predictions (C69) |
| transition from uncertainty to certainty in demand predictions (C69) | firms' profitability (L21) |
| AI adoption (C45) | firms' profitability (L21) |
| AI adoption (C45) | average price and quantity (P22) |
| AI adoption (high demand) (C45) | raise prices and quantities (E39) |
| AI adoption (low demand) (C45) | reduce consumer surplus (D11) |
| AI adoption (C45) | higher returns in make-to-order environment (C69) |
| AI adoption (C45) | ambiguous implications for consumer welfare (D18) |