AI is widely promoted as a driver of innovation and efficiency. Yet, its growing environmental footprint introduces tensions that challenge dominant narratives of technological progress. Training and deploying large-scale AI models demand substantial energy, water, and computational resources, generating environmental impacts that remain largely invisible to most consumers. Within this context, consumption becomes a sociotechnical practice shaped not only by product attributes, but also by the s…
Read moreAI is widely promoted as a driver of innovation and efficiency. Yet, its growing environmental footprint introduces tensions that challenge dominant narratives of technological progress. Training and deploying large-scale AI models demand substantial energy, water, and computational resources, generating environmental impacts that remain largely invisible to most consumers. Within this context, consumption becomes a sociotechnical practice shaped not only by product attributes, but also by the symbolic, ethical, and ecological meanings ascribed to organizational behavior. Drawing on perspectives from sustainability research, signaling theory, consumer studies, and sociotechnical systems, this theoretical essay examines how environmental responsibility, technological opacity, and symbolic value intersect in consumer interpretations of AI-mediated products and digitally generated content. Rather than proposing causal relationships, the essay reflects on how the integration of AI complicates long-standing assumptions about transparency, trust, and green consumption. By mapping these tensions, the work contributes to ongoing debates in AI and Society about the ecological and ethical implications of embedding computationally intensive technologies into everyday life.
