Can Artificial Intelligence (Ai) Based Pricing Achieve Sustainability? A Systematic Review from Business, Customer & Policymaking Perspectives

Abstract

AI-driven pricing mechanisms have emerged as transformative tools for modern economies, offering dynamic adaptability to market conditions while posing unique challenges for sustainability. This systematic review synthesizes insights from 48 academic and industry sources, focusing on the economic, social, and environmental dimensions of AI pricing. Utilizing the PRISMA framework, the study identifies critical drivers and barriers to adopting AI-based pricing models, particularly in achieving sustainability goals. The research highlights the future trajectory of AI pricing systems, forecasting their potential to revolutionize industries like energy, transportation, and e-commerce etc. by optimizing resource utilization and aligning pricing with real-time demand. Global disparities in adoption rates are examined, revealing how developed economies capitalize on advanced infrastructure while emerging markets face regulatory and infrastructural challenges. Ethical and policy considerations, such as algorithmic transparency, bias mitigation, and consumer trust, are also explored, underscoring the need for robust governance frameworks. The study proposes a qualitative sustainability assessment framework that evaluates AI pricing's impact across economic, social, and environmental domains, offering actionable insights for policymakers and business leaders. By addressing critical research gaps and envisioning future scenarios, this paper contributes to the discourse on the role of AI pricing in fostering sustainable market systems globally.

Keywords: AI-based pricing, sustainability, Dynamic pricing, Systematic Review, Ethical considerations, Policy implications