When Algorithms Set Prices: Emerging Consumer Fairness Challenges in AI-Driven Dynamic Pricing

Artificial intelligence (AI) is turning dynamic pricing from a standardized management decision into an individual, algorithmic experience. Algorithmic pricing improves efficiency and personalization, but its opacity and individualized prices can leave consumers feeling treated unfairly and distrustful. This short communication draws on recent research on algorithmic pricing, price fairness, price transparency, and consumer trust to build a conceptual framework. It links four features of algorithmic pricing (real-time adaptation, personalization, individualized price differentiation, and limited explainability) to perceived price fairness, which in turn shapes consumer trust and acceptance or resistance. The paper argues that fairness is a strategic management problem, not only an ethical concern. Implications for pricing managers cover price explanations, responsible personalization, and governance, and empirical research directions are proposed.