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Orchestrating AI-based circular business models through platform ecosystems: Review, framework, and future directions
1School of Economics, Business Administration and Accounting, University of São Paulo, Av. Prof. Luciano Gualberto, 908, São Paulo, SP, 05508-010, Brazil.
Journal of Environmental Management
|July 4, 2026
Summary
Artificial intelligence (AI) integration reshapes circular business models (CBMs) by influencing value creation, governance, and coordination within platform ecosystems. This transition involves strategic shifts, dematerialization, and platformization, requiring ongoing alignment of capabilities and coordination.
Area of Science:
- Business and Management
- Information Systems
- Sustainability Science
Background:
- Existing research on artificial intelligence (AI) and circular business models (CBMs) is fragmented.
- Limited understanding exists on how AI influences circular value creation, governance, and coordination in platform ecosystems.
Purpose of the Study:
- To systematically review the literature on AI and CBMs.
- To develop an integrative, process-oriented framework for AI-CBM transitions.
- To identify key dimensions, tensions, and configurations of AI-CBM integration.
Main Methods:
- Systematic literature review of 88 peer-reviewed articles.
- Thematic analysis to develop an integrative framework.
- Analysis of socio-technical tensions and configurations.
Main Results:
- Identified three interdependent dimensions: strategic reframing, AI-driven dematerialization, and ecosystem platformization.
- Highlighted socio-technical tensions including barriers, ethical challenges, and strategic trade-offs.
- Developed a framework distinguishing AI's role from enabler to ecosystem infrastructure.
Conclusions:
- AI-CBM transitions involve recursive cycles of experimentation and recalibration.
- AI reorganizes circular value through data-driven routines and platform infrastructure.
- Practical heuristics and readiness conditions for AI-CBM transition are provided.
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