UsesLevel 4 of 6 occupation or activityOccupation or activity, level 4 of 6Calculated with 11 entries, levels 1 and 3Database structure 
6Territories
5Organisations
3Uses
2Machine operations
1Calculation factorsChatGPT Business or Enterprise licence, 1 year
One year of a ChatGPT Business or Enterprise licence for an office worker: about 11 deep research queries, 130 web searches with an AI, 770 questions to ChatGPT, and 7 other tasks. Projet Celsius estimate.
- Text and conversation account for 83% of emissions: "Deep research" weighs as much as 330 quick questions.
- About 1,500 requests to AI over the year, or 6.8 per working day.
- An estimate: the frequencies and the share done with AI are our assumptions.
Sentence to citeChatGPT Business or Enterprise licence, 1 year, Projet Celsius estimate: 1 kgCO2e per subscription and per year, for 2.2 kWh of electricity, servers worldwide (458 gCO2e/kWh).
Breakdown of emissions by item
1 kgCO2e in total: 2.2 kWh of electricity × 458 gCO2e/kWh (servers worldwide).
Inputs of the calculation
PUE of the data centre, Read 1,000 tokens, Write, with reasoning, Re-read from cache, Question to ChatGPT, Summarise 30 pages, Web search with an AI, Deep research
How the calculation is built
One year of a ChatGPT Business or Enterprise licence for an office worker: questions, emails, texts, documents, spreadsheets, web searches, a few deep research queries and images. OpenAI publishes the differences in use between the employees of its business customers but not the number of requests per employee, and the frequencies and uses are Projet Celsius assumptions.
Comparison with other occupations and activities
Characteristics
| Unit | 1 subscription, 1 year : 220 days |
|---|---|
| Default location | world, 458 gCO2e/kWh (Ember 2025, life cycle); 11 other locations to choose from |
| Counted | the tasks done with AI over a working year, including data centre cooling |
| Not counted | server manufacturing, model training, the person's device, the price of the licence and the agents that the company builds on the platform |
| Status | estimated |
All the characteristics
| Identifier | IA-0335, projetcelsius.com/en/ai/database/IA-0335/ |
|---|---|
| Version | 0.1 of 13 November 2026 |
| Category | Occupations and activities, one person, 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 |
Usage parameters
Advanced settings
Tasks and frequencies
Frequency and share done with AI, task by task · typical use
Adjust each task
| Task | Frequency | Share with AI | Per year | Electricity | Share |
|---|---|---|---|---|---|
| Question to ChatGPT | 770 | 260 Wh | 12 % | ||
| Write an email | 330 | 76 Wh | 3 % | ||
| Proofread a page | 110 | 66 Wh | 3 % | ||
| Write a page | 44 | 20 Wh | 1 % | ||
| Summarise 30 pages | 39.6 | 190 Wh | 9 % | ||
| Query a PDF | 26.4 | 120 Wh | 6 % | ||
| Analyse a spreadsheet | 26.4 | 73 Wh | 3 % | ||
| Web search with an AI | 132 | 360 Wh | 16 % | ||
| Deep research | 10.6 | 1 kWh | 47 % | ||
| Create an image | 6.6 | 21 Wh | 1 % | ||
| Coding agent hourdoes not apply with this tooling |
Result for the chosen case
220 days, servers worldwide: 1 kgCO2e, 2.2 kWh.
For a carbon footprint
| Item | purchases of services (GHG Protocol scope 3, category 1); regulatory BEGES, category 4 |
|---|---|
| Quantity | 1 subscription over a year |
| Factor | 1 kgCO2e per subscription over one year, IA-0335 version 0.1, based on the local grid (location-based), servers worldwide |
| Total | 1 kgCO2e · not counted: server manufacturing, model training, the person's device, the price of the licence and the agents that the company builds on the platform |
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 |
|---|---|---|---|---|---|
| Deep research | 11 times | 99 Wh | 1 kWh | 47 % | assumption |
| Web search with an AI | 130 times | 2.7 Wh | 360 Wh | 16 % | assumption |
| Question to ChatGPT | 770 times | 0.34 Wh | 260 Wh | 12 % | assumption |
| Summarise 30 pages | 40 times | 4.9 Wh | 190 Wh | 9 % | assumption |
| Query a PDF | 26 times | 4.7 Wh | 120 Wh | 6 % | assumption |
| Write an email | 330 times | 0.23 Wh | 76 Wh | 3 % | assumption |
| Analyse a spreadsheet | 26 times | 2.8 Wh | 73 Wh | 3 % | assumption |
| Proofread a page | 110 times | 0.6 Wh | 66 Wh | 3 % | assumption |
| Create an image | 6.6 times | 3.2 Wh | 21 Wh | 1 % | assumption |
| Write a page | 44 times | 0.45 Wh | 20 Wh | 1 % | assumption |
Entries that use it
No other entry in the database is calculated from this one.
Sources of the calculation
12 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.
Anthropic · June 2025
Role and limits : Anthropic
What the publication covers. an agent uses about 4 times the tokens of a conversation, a multi-agent system about 15 times
What it does not cover. electricity
Reading by the database. Publisher orders of magnitude, with no absolute value
Deep research → : Re-read from cache →
The context re-read from cache at each of the 40 steps, 40,000 tokens on average
Scope of the figure used. server, convention C4
Limit. The quantity and the share entrusted to AI are database assumptions, not a measured footprint.
Apec · June 2025
Role and limits : Apec
What the publication covers. frequency of generative AI use at work, 2,000 private-sector managers surveyed in March 2025
What it does not cover. non-managers and the number of requests
Reading by the database. Recent French survey on frequency of use at work; copy read on a specialist press site
Support for the "Typical use" setting
Scope of the figure used. The median user among those who use AI, end of 2026: they turn to it every working day for part of their questions, writing and reading, about 5 to 15 requests per day in an office job. In an organisation or a territory, it also sets the share of employees who use it (25%).
Limit. This setting remains an assumption of the database, not a measurement of the occupation.
EnronSent
Role and limits : EnronSent
Author. Will Styler
What the publication covers. 96,106 messages sent by Enron employees, 13,810,266 words
What it does not cover. the messages received
Reading by the database. Professional emails from 2000 and 2001: an order of magnitude, not a norm
Write an email → : Write, with reasoning →
The email written, 150 words
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.
Write an email → : Read 1,000 tokens →
Length convention: an email
Scope of the figure used. A typical email: the sent messages of the Enron corpus average about 144 words; figure read in an excerpt, notice not verified
Limit. This publication supports the quantity of text or content processed, not its carbon footprint.
Write an email → : Write, with reasoning →
Length convention: an email
Scope of the figure used. A typical email: the sent messages of the Enron corpus average about 144 words; figure read in an excerpt, notice not verified
Limit. This publication supports the quantity of text or content processed, not its carbon footprint.
Google · 2026
Role and limits : Google
What the publication covers. up to hundreds of sites browsed and pages processed per search
What it does not cover. electricity
Reading by the database. A presentation page: a ceiling, not an average
Deep research → : Read 1,000 tokens →
The web pages read, about a hundred by default: Google announces up to hundreds of sites
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.
OpenAI · December 2025
Role and limits : OpenAI
What the publication covers. actual use by ChatGPT enterprise customers and a survey of 9,000 employees
What it does not cover. the consumer plans and any absolute volume per employee
Reading by the database. Publisher report; the gaps between users are the useful data
ChatGPT Business, 1 year → : Question to ChatGPT →
About 10 occasions to ask a question per working day, assumption; at the intensive level, several times the typical level, like the most active employees, who send 6 times the messages of the median employee (OpenAI, 2025).
Scope of the figure used. not published
Limit. The quantity and the share entrusted to AI are database assumptions, not a measured footprint.
ChatGPT Business, 1 year → : Analyse a spreadsheet →
About 3 spreadsheets per week, assumption; 19% of monthly users have never run data analysis, against 3% of daily users (OpenAI, 2025).
Scope of the figure used. tokens read and written, data centre
Limit. The quantity and the share entrusted to AI are database assumptions, not a measured footprint.
ChatGPT Business, 1 year → : Web search with an AI →
About 3 web searches per day, assumption; 12% of monthly users have never run a search, against 1% of daily users (OpenAI, 2025).
Scope of the figure used. searches, pages read, response, data centre
Limit. The quantity and the share entrusted to AI are database assumptions, not a measured footprint.
The 2 other publications in this section
Projet Celsius · November 2026
Tokens per word, per line of code and per cell, measured with 7 public tokenisers
Role and limits
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
Proofread a page → : Read 1,000 tokens →
Length convention: one page
Scope of the figure used. A report page, headings and paragraphs included: between the 1,500-character sheet (250 words) and a full A4 page in single spacing (about 550 words, at 6.1 characters per word measured on our articles)
Limit. This publication supports the quantity of text or content processed, not its carbon footprint.
Proofread a page → : Write, with reasoning →
Length convention: one page
Scope of the figure used. A report page, headings and paragraphs included: between the 1,500-character sheet (250 words) and a full A4 page in single spacing (about 550 words, at 6.1 characters per word measured on our articles)
Limit. This publication supports the quantity of text or content processed, not its carbon footprint.
Write a page → : Write, with reasoning →
Length convention: one page
Scope of the figure used. A report page, headings and paragraphs included: between the 1,500-character sheet (250 words) and a full A4 page in single spacing (about 550 words, at 6.1 characters per word measured on our articles)
Limit. This publication supports the quantity of text or content processed, not its carbon footprint.
Summarise 30 pages → : Read 1,000 tokens →
Length convention: one page
Scope of the figure used. A report page, headings and paragraphs included: between the 1,500-character sheet (250 words) and a full A4 page in single spacing (about 550 words, at 6.1 characters per word measured on our articles)
Limit. This publication supports the quantity of text or content processed, not its carbon footprint.
Summarise 30 pages → : Write, with reasoning →
Length convention: one page
Scope of the figure used. A report page, headings and paragraphs included: between the 1,500-character sheet (250 words) and a full A4 page in single spacing (about 550 words, at 6.1 characters per word measured on our articles)
Limit. This publication supports the quantity of text or content processed, not its carbon footprint.
Query a PDF → : Read 1,000 tokens →
Length convention: one page
Scope of the figure used. A report page, headings and paragraphs included: between the 1,500-character sheet (250 words) and a full A4 page in single spacing (about 550 words, at 6.1 characters per word measured on our articles)
Limit. This publication supports the quantity of text or content processed, not its carbon footprint.
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.
Deep research → : Write 1,000 tokens →
Length convention: one page
Scope of the figure used. A report page, headings and paragraphs included: between the 1,500-character sheet (250 words) and a full A4 page in single spacing (about 550 words, at 6.1 characters per word measured on our articles)
Limit. This publication supports the quantity of text or content processed, not its carbon footprint.
Zhang and Nam · June 2026
HANSEL: Extracting Breadcrumbs from Web Agent Trajectories for Interactive Verification ↗ (new tab)
Role and limits
Author. Yujin Zhang and Daye Nam
What the publication covers. 45 web agent trajectories: 13.16 steps and 6.02 pages visited per task on average
What it does not cover. electricity
Reading by the database. A small sample, which gives the order of magnitude of an agent's steps
Web search with an AI → : Read 1,000 tokens →
The 5 pages found, read by the model, and the question: web agents visit 6 pages per task on average
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.
Energy and factors
The references of the selected values and of the entries used in this calculation.
Google · January 2009
Role and limits : Google
What the publication covers. a search, data centre
Reading by the database. Never remeasured
Reference of the selected value
Scope of the figure used. A search, data centre included
Limit. Never publicly remeasured; Google's AI answers are not published
Luccioni et al. · October 2024
Role and limits : Luccioni et al.
Author. Luccioni, Jernite and Strubell
What the publication covers. GPU, processor, memory
What it does not cover. data centre
Reading by the database. Open models only
Create an image → : Generate an image →
One image, of the chosen size: standard by default
Scope of the figure used. GPU, processor, memory; excluding the data centre
Limit. This figure covers part of the calculation; it does not measure the whole entry.
Reference for the variant "Standard image, from 512 to 1,024 pixels per side"
Scope of the figure used. Average of the open models tested, 1,000 images; median 1.35 Wh, maximum 11.49 Wh
Limit. Open models only; closed generators publish nothing
OpenAI · June 2025
Role and limits : OpenAI
Author. Sam Altman, OpenAI
What the publication covers. an average query
What it does not cover. method, scope
Reading by the database. One sentence, no method
Reference of the selected value
Scope of the figure used. "An average query", with no published method
Limit. Record R-0004, attached to the ChatGPT block
Watershed · Aug. 2026
Estimating GHG Emissions from AI Use: Framework for Corporate-Level Measurement ↗ (new tab)
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
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
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
Write an email → : 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.
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
Proofread a page → : 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.
Write a page → : 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.
Summarise 30 pages → : 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.
Query a PDF → : 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.
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.
Web search with an AI → : 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.
Deep research → : 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.
Create an image → : 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.
Conversion into carbon
The source of the electricity factor of the selected location.
Worldwide: 458 gCO2e/kWh, life cycle.
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
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
- Projet Celsius assumptions 100 %
Usage assumptions
Frequency, share done with AI according to adoption, source of each assumption
Question to ChatGPT : 10 per day, 35% with AI in typical use
About 10 occasions to ask a question per working day, assumption; at the intensive level, several times the typical level, like the most active employees, who send 6 times the messages of the median employee (OpenAI, 2025).
Write an email : 15 per day, 10% with AI in typical use
About 15 emails per day; without integration with the mail client, a small share is written or reworked in the assistant, assumption.
Proofread a page : 2 per day, 25% with AI in typical use
About 2 texts to rework per day, assumption.
Write a page : 1 per day, 20% with AI in typical use
About 1 page to write per day, assumption.
Summarise 30 pages : 3 per week, 30% with AI in typical use
About 3 long documents or threads to summarise per week, assumption.
Query a PDF : 2 per week, 30% with AI in typical use
About 2 long documents to query per week, assumption.
Analyse a spreadsheet : 3 per week, 20% with AI in typical use
About 3 spreadsheets per week, assumption; 19% of monthly users have never run data analysis, against 3% of daily users (OpenAI, 2025).
Web search with an AI : 3 per day, 20% with AI in typical use
About 3 web searches per day, assumption; 12% of monthly users have never run a search, against 1% of daily users (OpenAI, 2025).
Deep research : 88 per year, 12% with AI in typical use
About 2 in-depth questions per week, as for the Microsoft 365 Copilot licence; at the typical level about 1 deep research per month, plan cap not reviewed.
Create an image : 1 per week, 15% with AI in typical use
About 1 image need per week for a presentation or document, assumption.
Coding agent hour : 5 per week, 20% with AI in typical use
About 5 hours per week during which a coding agent can work, for those who code, assumption; the coding agent uses more credits than the other functions (OpenAI, 2025).
Methodology conventions
With their alternatives
| The working day and year | A working year counts 220 days and 44 weeks, a personal year 365 days; the task lists of occupations give, as a median, about 2 requests to AI per working day at low adoption, 6 at standard adoption, 21 at intensive adoption, excluding code suggestions |
|---|---|
| The default location | Without other information, the servers are in the world, at the world average electricity |
| 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 |
| 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 13 November 2026, in the database in version 0.4
- 13 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).
