When Investment Meets Competition: The Logic and Responses of Product Market Structure Evolution in the AI Era

Abstract

Artificial intelligence (AI) investment is fundamentally reshaping the landscape of product market competition, yet its systematic impact and underlying mechanisms remain inadequately theorized. Based on the practices of China’s A-share listed companies, this paper develops a comprehensive theoretical framework from both supply-side capability reconstruction and demand-side structural transformation perspectives to analyze how AI investment influences product market competition. The study yields three key findings. First, AI investment fundamentally transforms firms’ competitive strategy sets and capability boundaries through three channels: reducing marginal costs, enhancing demand forecasting accuracy, and expanding product functional spaces. Second, the intrinsic characteristics of AI—including increasing returns to scale in data, algorithmic black boxes, and cross-scenario knowledge transfer capabilities—drive the competitive boundaries of product markets to shift from the traditional two-dimensional “product-geography” definition toward a multidimensional “scenario-time-ecosystem” structure. Third, the relationship between AI investment and competition intensity follows an inverted U-shaped pattern, with the inflection point determined by the relative dynamics between the intensity of data-driven positive feedback and user multi-homing costs. Further analysis reveals that supply-side R&D transformation barriers and demand-side financing constraints constitute dual dilemmas that may accelerate market concentration toward leading platforms. The theoretical contribution of this paper lies in incorporating the competitive effects of AI investment into an inverted U-shaped dynamic framework while explicitly distinguishing supply-side capability mechanisms from demand-side structural mechanisms. These conclusions provide theoretical foundations and decision-making references for product market competition governance, digital antitrust policy formulation, and corporate AI investment strategies in the AI era.