What Is Green AI and Generative AI? — Virtual Session for a Leading Financial Organization

A snippet from a virtual presentation I delivered to a leading financial organization on Green AI and Generative AI — the recording is above.

What the session covered

Generative AI changes the sustainability equation. Earlier waves of software grew compute demand gradually; generative AI concentrates it. Model training and inference at enterprise scale carry a real footprint in energy, carbon, and cost — and for most organizations, that footprint arrives faster than the practices to manage it.

Green AI is the response. Green AI means integrating energy efficiency and carbon-emission reduction into every facet of AI development and deployment — from the data pipeline through model selection, training, inference, and monitoring. It is not a constraint bolted on after the fact; it is an engineering discipline that makes AI systems leaner, and leaner systems cost less to run.

Why it matters especially in financial services. Few industries combine this scale of AI ambition with this level of regulatory and ESG scrutiny. For a financial organization, the same practices that reduce AI’s environmental footprint also strengthen cost discipline and disclosure readiness — three outcomes from one set of engineering choices.

Sessions like this one are where the awareness starts: once teams see that efficiency, cost, and sustainability are the same conversation, the practices follow.