Analyse des données avec l'IA, 1 an

Name: Data analysis with AI, 1 year
Creator: Projet Celsius
License: https://creativecommons.org/licenses/by/4.0/

Projet Celsius

Database entryUsesLevel 5 of 6 organisationOrganisation, level 5 of 6Calculated with 2 entries, levels 1 and 3Database structure

Data analysis with AI, 1 year

25 analysts who each give AI one spreadsheet a week to analyse and turn into charts, 44 weeks a year. Projet Celsius estimate.

The calculation covers the analysis of spreadsheets by AI, data centre included.
100% of the calculation rests on database assumptions; it does not measure actual use.
Out of scope: the organisation's data warehouses and analysis software, server manufacturing and model training.

Compare

Calculated with

Breakdown of emissions by item

The pathAnalyse a spreadsheet × 1,100Data analysis

1.4 kgCO2e in total: 3.1 kWh of electricity × 458 gCO2e/kWh (servers worldwide).

Inputs of the calculation 4

PUE of the data centre, Read 1,000 tokens, Write, with reasoning, Analyse a spreadsheet

How the calculation is built

Calculated from the analysis of one spreadsheet.

Comparison with other organisations

See the full list

Very small business (5)480 gCO2e

Website translation690 gCO2e

Data analysisthis entry1.4 kgCO2e

Process automation5.5 kgCO2e

Training with an AI tutor6.5 kgCO2e

Team of 12, 1 year7.1 kgCO2e

SME of 50 people12 kgCO2e

Content production16 kgCO2e

Automated customer service28 kgCO2e

Document assistant34 kgCO2e

Logarithmic axis: each tick is 10 times the previous one.

Characteristics

Unit	1 service, 1 year
Default location	world, 458 gCO2e/kWh (Ember 2025, life cycle); 11 other locations to choose from
Counted	the analysis of spreadsheets by AI, data centre included
Not counted	the organisation's data warehouses and analysis software, server manufacturing and model training
Status	estimated

All the characteristics identifier, version, rule for the value, sources, licence

Identifier	IA-0410, projetcelsius.com/en/ai/database/IA-0410/
Version	0.1 of 2 November 2026
Category	Organisations, one organisation, one year
Choice of the selected value	database calculation from the entries this one is made of, at the quantities of the unit
Sources	calculation of the database
Licence	CC BY 4.0

Emissions by server location

Emissions associated with electricity (CO2e)

Poland1.8 kgCO2e
World1.4 kgCO2e
United States1.2 kgCO2e
European Union640 gCO2e
France130 gCO2e

× 14 between Poland and France, for the same electricity

Ember 2025, over the life cycle. The same use consumes 3.1 kWh in each location.

Data analysis with AI, 1 year · result per service per year · estimated · one server location per line.Counted: the analysis of spreadsheets by AI, data centre included. Out of scope: the organisation's data warehouses and analysis software, server manufacturing and model trainingFind this case: projetcelsius.com/en/ai/database/organisations/data-analysis-with-ai/Calculation by Projet Celsius, AI Impact Database, version 0.4 of 13 November 2026 · IA-0410, entry in version 0.1 · engine 0.3.1 · CC BY 4.0.

Usage parameters

Advanced settings model class, reasoning, calibration, duration

Model classReasoningCalibrationDuration

Result for the chosen case

Location of the servers

For a carbon footprint

The row for a carbon footprint

Item	purchases of services (GHG Protocol scope 3, category 1); regulatory BEGES, category 4
Quantity	1 department over one year
Factor	1.4 kgCO2e per service over one year, IA-0410 version 0.1, based on the local grid (location-based), servers worldwide
Total	1.4 kgCO2e · not counted: the organisation's data warehouses and analysis software, server manufacturing and model training

Breakdown by item

Quantity, unit value, contribution and nature of the data for each item

Item	Quantity	Unit value	Contribution	Share	Nature of the data
Analyse a spreadsheet	× 1,100	2.8 Wh	3.1 kWh	100 %	assumption

Entries that use it

No other entry in the database is calculated from this one.

Sources of the calculation

3 publications, for this entry and those used to calculate it, with the chosen parameters.

The result is calculated by Projet Celsius. The sources below support its uses, its factors and its conversion; they do not all measure this total.

Uses and assumptions

These publications shed light on AI tasks and uses. They do not measure the carbon footprint of the case calculated.

Projet Celsius · November 2026
Tokens per word, per line of code and per cell, measured with 7 public tokenisers
Read 1,000 tokens
Role and limits : Projet Celsius
What the publication covers. 479,888 words from 196 blog articles and their English translation, code from the site and the Python library, a table of measurements; tokenisers of GPT-4o, GPT-4, Llama 3, Gemini (via Gemma 3), Mistral, DeepSeek and Qwen
What it does not cover. the Claude tokeniser, not public
Reading by the database. A measurement on technical texts, figures included; to be repeated if publishers change their tokeniser
Projet Celsius measurement, repeated on request with the public tokenisers
- Analyse a spreadsheet → : Read 1,000 tokens →
  The spreadsheet, 200 rows and 10 columns, and the question
  Scope of the figure used. server, excluding the data centre
  Limit. The quantity and the share entrusted to AI are database assumptions, not a measured footprint.
- Analyse a spreadsheet → : Read 1,000 tokens →
  Length convention: a spreadsheet of 200 rows
  Scope of the figure used. A table of 200 rows and 10 columns of numbers and short labels: 4.7 tokens per cell, measured on a real table
  Limit. This publication supports the quantity of text or content processed, not its carbon footprint.

Energy and factors

The references of the selected values and of the entries used in this calculation.

Watershed · Aug. 2026
Estimating GHG Emissions from AI Use: Framework for Corporate-Level Measurement ↗ (new tab)
Read 1,000 tokens · Write 1,000 tokens · Data centre PUE
Role and limits : Watershed
Author. Bistline, Ulissi, Davis, Glidden, Joyce, Li, Mohsenin and Suh (Watershed)
What the publication covers. factors per 1,000 tokens read and written at the server before PUE (host and standby machines included), PUE separate (1.10 for a large operator, 1.56 for an unknown operator)
What it does not cover. clean measurements, the model and the hardware
Reading by the database. Default factors proposed for review (public data as of June 2026); for a large operator, taken from Google's measurement published in 2025 (Elsworth et al.), which already contains the data centre overhead; constant per token, they underestimate long contexts and agents according to the authors
- Read 1,000 tokens →
  Reference for the variant "Medium model, Watershed default factor"
  Scope of the figure used. Default factor for 1,000 tokens read, medium model, large operator, at the server before PUE (Watershed table 2, public data as of June 2026)
  Limit. A default value that Watershed derives from Google's measurement (0.24 Wh for the median text query of the Gemini app), with about 500 tokens per query and a written token costing 3 times a read token; Watershed does not give the split between read and written tokens. The 0.24 Wh already include the overhead of Google's data centre (0.02 Wh, 8%): with 375 tokens read and 125 written, the simplest reading, the factor contains it, and the PUE of 1.10 applied afterwards counts it a second time (about 9%). Values proposed for review, final at the next version of the framework
- Write 1,000 tokens →
  Reference for the variant "Medium model, Watershed default factor"
  Scope of the figure used. Default factor for 1,000 tokens written, medium model, large operator, at the server before PUE (Watershed table 2, public data as of June 2026)
  Limit. 3 times the reading factor, based on the ratio between writing and reading selected by Watershed (Patel et al., Splitwise, 2024). Same derivation and same caveat as for reading: Google's 0.24 Wh already include about 8% of data centre. Values proposed for review, final at the next version of the framework
- Analyse a spreadsheet → : Data centre PUE →
  The data centre, convention C3
  Scope of the figure used. building cooling and losses
  Limit. This figure covers part of the calculation; it does not measure the whole entry.
- Data centre PUE →
  Reference of the selected value
  Scope of the figure used. Default factor for a large operator, from the server to the data centre; 1.56 for an unknown operator
  Limit. A default value, not a measurement

Conversion into carbon

The source of the electricity factor of the selected location.

Worldwide: 458 gCO2e/kWh, life cycle.

Ember · 2026
Global Electricity Review 2026, and Our World in Data based on Ember ↗ (new tab)
Grid electricity
Role and limits : Ember
Author. Ember, Our World in Data
What the publication covers. electricity generation over the life cycle, by country
What it does not cover. guarantees of origin
Reading by the database. The same source for all countries
- Grid electricity →
  Conversion of electricity into carbon: worldwide
  Scope of the figure used. the production of electricity over the life cycle, including power plant construction and fuels
  Limit. An average for the chosen country, not the electricity contract or the data centre of a specific service.

Nature of the data

Published readings, conventions, assumptions

What this figure rests on

Projet Celsius assumptions 100 %

A share counts as an assumption as soon as a quantity set by Projet Celsius (a frequency, a share done with AI, a headcount) enters its calculation, even if the rest rests on published measurements.

Calculation assumptions

Quantities, nature and source of each assumption

Analyse a spreadsheet : × 1,100
One spreadsheet analysis per week per analyst, 44 weeks
assumption · Analyse a spreadsheet

Methodology conventions

With their alternatives

The full methodology

The data centre	Server electricity is multiplied by 1.10 for the data centre · alternatives: × 1.72 from chips to the full service at Google, never to be combined
The default location	Without other information, the servers are in the world, at the world average electricity · alternatives: the United States, where most of the large assistants run
Electricity, location-based, on a life cycle basis	The kilowatt-hour is that of the servers' country, on a life cycle basis, from a single source for all countries · alternatives: market-based, with purchase contracts, shown alongside when published
Two significant figures	A calculated value is rounded to two significant figures, a published value is reproduced with the precision of its source; the calculation keeps full precision
The formula	the sum of what makes up the entry, then CO2e: electricity (Wh) multiplied by the carbon intensity of the server location (gCO2e/kWh), divided by 1,000
Calculate a case without an entry	The formula, the default values and a step-by-step example

History

Entry in version 0.1 of 2 November 2026, in the database in version 0.4

The changelog

2 November 2026Version 0.1 of the entry, as of the date of its current value.
31 October 2026Creation of the database, in its first version (0.1).

Citation

Projet Celsius, AI Impact Database, version 0.4 of 13 November 2026, "Data analysis with AI, 1 year", IA-0410 (entry in version 0.1 of 2 November 2026), projetcelsius.com/en/ai/database/IA-0410/ · CC BY 4.0.

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