AI-Driven Dynamic Pricing and Energy Justice: Introducing the AI-Powered Pricing Justice Index (APJI) to Address Social Inequality

Artificial intelligence (AI) is increasingly integrated into decentralized energy markets through dynamic pricing systems that aim to optimize consumption, stabilize power grids and encourage behavioral changes. While such systems are often celebrated for their technical efficiency, their growing autonomy raises important concerns regarding fairness, transparency and accountability. This study explores the multifaceted role of AI in energy pricing by addressing four interrelated research questions: (1) how AI adapts to peer-to-peer (P2P) energy trading environments; (2) how machine learning enables self-regulating pricing systems; (3) what regulatory and ethical challenges arise in the absence of centralized oversight; and (4) how fairness and inclusion in AI-based pricing can be systematically evaluated. In response to these questions, the study introduces the AI-powered Pricing Justice Index (APJI), a conceptual framework designed to assess pricing systems across six dimensions: transparency, equity, accessibility, behavioral fairness, data ethics and sustainability alignment. Methodologically, the research employs a qualitative conceptual approach grounded in literature synthesis, normative critique and framework development. Although not based on empirical data, the APJI offers a novel and scalable tool for guiding the ethical design and regulation of AI in energy systems. The study contributes to ongoing discussions on algorithmic governance by reframing energy pricing as not only a technical or economic process but also a site of justice. It concludes with a call for interdisciplinary collaboration to operationalize the APJI and ensure that energy transitions are both intelligent and equitable.