When we first began exploring the environmental cost of large-scale AI systems, we were struck by a simple realization: our models are becoming smarter, but our infrastructure is becoming heavier. Every model training run, inference endpoint and data pipeline contributes to an expanding carbon footprint.
For most organizations, sustainability is still treated as a corporate initiative rather than a design constraint. However, by 2025, that approach is no longer sustainable, either literally or strategically. Green AI isn’t just an ethical obligation; it’s an operational advantage. It helps us build systems that do more with less (less energy, less waste and less cost) while strengthening brand equity and resilience.
What if you could have a practical, end-to-end framework for implementing green AI across your enterprise IT? This is for CIOs, CTOs and technical leaders seeking a blueprint for turning sustainability from aspiration into action.
