Data

Global investment in generative AI

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What you should know about this indicator

  • One-time events like large acquisitions can skew yearly figures, and broader economic factors like interest rates or market sentiment can also affect AI investment trends independently of AI-specific developments.
  • The dataset’s methodology doesn’t specify which types of AI investments are included, so it may overlook important areas of AI investment, such as those from public companies (e.g., NVIDIA, TSMC), corporate internal R&D, government funding, public sector initiatives, data center infrastructure, hardware production, semiconductor manufacturing, and expenses for research and talent.
  • The dataset likely underestimates the total global AI investment, as it only captures certain types of private equity transactions, excluding other significant channels and categories of AI-related spending.
Global investment in generative AI
Generative AI refers to AI systems that can create new content, such as images, text, or music, based on patterns learned from existing data.
Source
Quid via AI Index (2024); U.S. Bureau of Labor Statistics (2024) – with major processing by Our World in Data
Last updated
June 28, 2024
Next expected update
June 2025
Date range
2019–2023
Unit
constant 2021 US$

Sources and processing

This data is based on the following sources

The AI Index Report tracks, collates, distills, and visualizes data related to artificial intelligence (AI). The mission is to provide unbiased, rigorously vetted, broadly sourced data to enable policymakers, researchers, executives, journalists, and the general public to develop a more thorough and nuanced understanding of the complex field of AI.

Retrieved on
June 28, 2024
Citation
This is the citation of the original data obtained from the source, prior to any processing or adaptation by Our World in Data. To cite data downloaded from this page, please use the suggested citation given in Reuse This Work below.
Nestor Maslej, Loredana Fattorini, Raymond Perrault, Vanessa Parli, Anka Reuel, Erik Brynjolfsson, John Etchemendy, Katrina Ligett, Terah Lyons, James Manyika, Juan Carlos Niebles, Yoav Shoham, Russell Wald, and Jack Clark, “The AI Index 2024 Annual Report,” AI Index Steering Committee, Institute for Human-Centered AI, Stanford University, Stanford, CA, April 2024.

The Bureau of Labor Statistics reports the monthly Consumer Price Index (CPI) of individual goods and services for urban consumers at the national, city, and state levels. CPI is presented on an annual basis, which we have derived as the average of the monthly CPIs in a given year.

Retrieved on
May 16, 2024
Citation
This is the citation of the original data obtained from the source, prior to any processing or adaptation by Our World in Data. To cite data downloaded from this page, please use the suggested citation given in Reuse This Work below.
U.S. Bureau of Labor Statistics

How we process data at Our World in Data

All data and visualizations on Our World in Data rely on data sourced from one or several original data providers. Preparing this original data involves several processing steps. Depending on the data, this can include standardizing country names and world region definitions, converting units, calculating derived indicators such as per capita measures, as well as adding or adapting metadata such as the name or the description given to an indicator.

At the link below you can find a detailed description of the structure of our data pipeline, including links to all the code used to prepare data across Our World in Data.

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Notes on our processing step for this indicator
  • Reporting a time series of AI investments in nominal prices (i.e., without adjusting for inflation) means it makes little sense to compare observations across time; it is therefore not very useful. To make comparisons across time possible, one has to take into account that prices change (e.g., there is inflation).
  • It is not obvious how to adjust this time series for inflation, and we debated it at some length within our team.
  • It would be straightforward to adjust the time series for price changes if we knew the prices of the specific goods and services that these investments purchased. This would make it possible to calculate a volume measure of AI investments, and it would tell us how much these investments bought. But such a metric is not available. While a comprehensive price index is not available, we know that the cost for some crucial AI technology has fallen rapidly in price.
  • In the absence of a comprehensive price index that captures the price of AI-specific goods and services, one has to rely on one of the available metrics for the price of a bundle of goods and services. In the end we decided to use the US Consumer Price Index (CPI).
  • The US CPI does not provide us with a volume measure of AI goods and services, but it does capture the opportunity costs of these investments. The inflation adjustment of this time series of AI investments therefore lets us understand the size of these investments relative to whatever else these sums of money could have purchased.

Reuse this work

  • All data produced by third-party providers and made available by Our World in Data are subject to the license terms from the original providers. Our work would not be possible without the data providers we rely on, so we ask you to always cite them appropriately (see below). This is crucial to allow data providers to continue doing their work, enhancing, maintaining and updating valuable data.
  • All data, visualizations, and code produced by Our World in Data are completely open access under the Creative Commons BY license. You have the permission to use, distribute, and reproduce these in any medium, provided the source and authors are credited.

Citations

How to cite this page

To cite this page overall, including any descriptions, FAQs or explanations of the data authored by Our World in Data, please use the following citation:

“Data Page: Global investment in generative AI”, part of the following publication: Charlie Giattino, Edouard Mathieu, Veronika Samborska and Max Roser (2023) - “Artificial Intelligence”. Data adapted from Quid via AI Index, U.S. Bureau of Labor Statistics. Retrieved from https://ourworldindata.org/grapher/global-investment-in-generative-ai [online resource]
How to cite this data

In-line citationIf you have limited space (e.g. in data visualizations), you can use this abbreviated in-line citation:

Quid via AI Index (2024); U.S. Bureau of Labor Statistics (2024) – with major processing by Our World in Data

Full citation

Quid via AI Index (2024); U.S. Bureau of Labor Statistics (2024) – with major processing by Our World in Data. “Global investment in generative AI” [dataset]. Quid via AI Index, “AI Index Report”; U.S. Bureau of Labor Statistics, “US consumer prices” [original data]. Retrieved November 18, 2024 from https://ourworldindata.org/grapher/global-investment-in-generative-ai