"A non-EU cloud consuming energy produced outside the EU, in a datacenter beyond your control, with an opaque carbon footprint, is not just a sovereignty risk — it is also a CSRD risk."
AI model carbon footprint, environmental impact of cloud, measurement methodology, CSRD reporting, sovereign Green IT strategy.
CDO, CIO, CSR/CSRD officers, cloud architecture teams, senior management, sustainable procurement managers.
CSRD (2024-2026), EU Taxonomy, datacenter energy efficiency directive (EU EED), ISO 14001, GHG Protocol Scope 3.
Half day (3h30) — 2 sessions + 1 digital footprint measurement workshop.
Generative AI is a high-energy-intensity technology. Its carbon footprint directly depends on infrastructure choices — and therefore on sovereignty choices.
The most energy-intensive phase. Training a large model can consume as much as hundreds of transatlantic flights. This phase is beyond the reach of user organizations — unless they train their own models.
If performed on own infrastructure (on-premise or EU cloud), the footprint is measurable and traceable. If performed via external API, the footprint is opaque and cannot be accurately reported in the CSRD statement.
Every query to an external LLM generates a Scope 3 footprint. At the scale of a banking organization with thousands of AI tool users, the volume is significant and must be measured.
Large companies subject to CSRD must report their digital footprint including AI usage in non-financial reporting. Any consumption via a cloud provider whose energy data is opaque makes the reporting non-auditable — and exposes the organization to a non-compliant qualification by statutory auditors.
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