Economic analysis of AI personalisation under product competition and data externality

In the era of AI, many firms are integrating AI into product design to enhance their competitive position in increasingly competitive markets. As proprietary data accumulates, some firms pursue deeper personalisation to better align AI-enabled products with user preferences. However, the effectiveness of AI personalisation is shaped by several factors, including personalisation costs, data externalities, and product competition. Against this background, we develop a game-theoretical model to examine the AI personalisation strategies of two competing firms, incorporating cost–benefit considerations and data externalities. Our key findings are as follows: (1) data externalities significantly influence competitive pricing, demand, and profitability; (2) the interaction between personalisation costs and data externalities shapes two firms' personalisation decisions; and (3) AI personalisation can either enhance or reduce consumer surplus, depending on the strength of data externalities, potentially leading to social inefficiencies. This study contributes to a deeper understanding of the strategic role of AI personalisation in product competition and its welfare implications, while offering valuable managerial insights for stockholders and managers seeking to maximise the value of AI in the design and operation of their production systems.