Tier 1 · Model 3 of 4 · v0.6

AI Environmental Impact Model

An indicative disclosure scale for communicating the relative energy intensity of AI use. Applicable to any piece of work, any output type and any level of AI activity.

Three axes produce one grade. Task type and model category set the base grade in the grid below, and usage intensity moves it by one step in either direction.

Axes
3
Grades
A to E
Output
indicative grade
Intensity
± one grade

Published March 2026. Where a session involved multiple task types, score based on the highest-intensity task used.

EM v0.6 · Published · March 2026

This model is a disclosure tool, not a sustainability certification.

It communicates the relative energy intensity of different AI tasks rather than making verified carbon claims. Grade A does not mean zero impact; it means the indicative impact is negligible at the current state of measurement. Scores will be tightened at v1.0 as first-party provider data becomes available under EU AI Act requirements from August 2026.

The grid · v0.6

Select a base grade, then an intensity

Model category →

On-device or lightweight

Standard cloud

Frontier or large

Text

Extended reasoning or agentic

Image generation

Video generation

↑ Task type

Cell value = base grade before intensity

Usage intensity

Indicative grade · Extended reasoning or agentic · Standard cloud · Moderate

C, Moderate energy intensity

Moderate energy use. Disclose in deliverable transparency notes.

Grade C held at moderate intensity

01.

How scoring works

As AI use becomes routine in professional and creative work, its environmental footprint is a growing area of public and regulatory interest. Verified per-model energy figures are not yet available for most AI systems at the level of detail needed for precise accounting, and the methodologies providers do publish use incompatible approaches that make comparison difficult.

This model takes a practical approach to that challenge. Rather than claiming a precision the data cannot support, it uses task type, model category and usage intensity to produce an indicative A to E grade that any organisation can apply and disclose. The grade sits alongside the AI Transparency grade on the Report Card and can be included in deliverable footers as a standard transparency measure.

Every assessment combines three factors. Where a session involved multiple task types, score based on the highest-intensity task used.

Axis 1

Task type

Text

Writing, researching, editing, analysing, translating or generating code

Extended reasoning or agentic

Using an AI tool's advanced research or reasoning mode, or running multi-step automated workflows

Image generation

Creating images or visual assets using AI

Video generation

Creating video content using AI

Axis 2

Model category

On-device or lightweight

A lightweight or on-device tool

Standard cloud

ChatGPT, Claude, Gemini or similar used for everyday tasks

Frontier or large

An advanced or specialist tool, or a general assistant in its most powerful mode

Axis 3

Usage intensity

Light

Under ~30 minutes, single task

Move one grade down (minimum A)

Moderate

~1 to 2 hours, several tasks

No change. Base grade applies.

Heavy or continuous

Throughout a working day or project

Move one grade up (maximum E)