Data
Annual global corporate investment in artificial intelligence, by type
What you should know about this indicator
- A merger is a corporate strategy involving two companies joining together to form a new company. An acquisition is a corporate strategy involving one company buying another company.
- Private investment in AI companies in each year that received an investment of more than $1.5 million (not adjusted for inflation).
- A public offering is the sale of equity shares or other financial instruments to the public in order to raise capital.
- A minority stake is an ownership interest of less than 50% of the total shares of a company.
- The categories shown suggest a focus on traditional corporate finance deals, but without a detailed methodology, we can't be certain about what's included or excluded. This means it may not fully capture important areas of AI investment, such as those from public companies (e.g., NVIDIA, TSMC), corporate internal R&D, government funding, public sector initiatives, data center infrastructure, hardware production, semiconductor manufacturing, and expenses for research and talent.
- One-time events like large acquisitions can skew yearly figures, and broader economic factors like interest rates or market sentiment can also affect AI investment trends independently of AI-specific developments.
- The dataset likely underestimates the total global AI investment, as it only captures certain types of private equity transactions, excluding other significant channels and categories of AI-related spending.
Annual global corporate investment in artificial intelligence, by type
This data is expressed in US dollars, adjusted for inflation.
Source
Quid via AI Index (2024); U.S. Bureau of Labor Statistics (2024) – with major processing by Our World in Data
Last updated
June 28, 2024
Next expected update
June 2025
Date range
2013–2023
Unit
constant 2021 US$
Sources and processing
This data is based on the following sources
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.
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.
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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: Annual global corporate investment in artificial intelligence, by type”, 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/corporate-investment-in-artificial-intelligence-by-type [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 DataFull citation
Quid via AI Index (2024); U.S. Bureau of Labor Statistics (2024) – with major processing by Our World in Data. “Annual global corporate investment in artificial intelligence, by type” [dataset]. Quid via AI Index, “AI Index Report”; U.S. Bureau of Labor Statistics, “US consumer prices” [original data]. Retrieved November 24, 2024 from https://ourworldindata.org/grapher/corporate-investment-in-artificial-intelligence-by-type