The exponential growth of digital data presents a significant environmental crisis, burdening the planet with energy consumption, resource depletion, and electronic waste. This document details the lifecycle footprint of data, highlighting the environmental costs associated with each stage from creation to disposal, particularly within the life science industry. Traditional data management’s focus on performance and cost has exacerbated these issues. However, Artificial Intelligence (AI) offers transformative solutions. By optimizing data capture, storage, processing, transmission, and disposal, AI can substantially reduce environmental impact. Case studies within this document illustrate both the challenges and the potential of AI-driven strategies to achieve sustainable data management practices.
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