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Annual professional service robots installed globally, by application area

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Artificial Intelligence

What you should know about this indicator

  • Agriculture category includes robots used for tasks such as plowing, seeding, harvesting, weeding, fertilizing, and pesticide spraying—both indoors (e.g. greenhouses) and outdoors (e.g. fields and vineyards). It also covers robots for milking, as well as those used in other livestock activities like feeding and barn cleaning.
  • Professional cleaning category includes robots designed to clean floors, windows, walls, tanks, pipes, and vehicle hulls in professional environments. This category also includes disinfection robots and others used for specialized or large-scale cleaning tasks.
  • Transportation and logistics category includes robots that transport goods and manage inventory in both indoor and outdoor environments. These robots are used in places such as warehouses, hospitals, hotels, and public streets, and they support activities like deliveries, stock counting, and restocking.
  • Medical and healthcare category includes robots used in clinical and care settings for diagnostics, surgery, rehabilitation, and non-invasive therapy. It also includes hospital support robots, wearable exoskeletons, and telepresence robots used specifically in healthcare.
  • Hospitality category includes robots that prepare and serve food or drinks, as well as those that provide information, guidance, or remote presence in customer-facing environments like hotels, restaurants, and museums.
Annual professional service robots installed globally, by application area
Professional service robots perform useful tasks outside of industrial manufacturing, such as surgery, logistics, or agriculture. Consumer service robots, such as robotic vacuum cleaners, are not included.
Source
International Federation of Robotics via AI Index Report (2026) – with minor processing by Our World in Data
Last updated
April 20, 2026
Next expected update
April 2027
Date range
2021–2024
Unit
robots

Sources and processing

This data is based on the following sources

AI Index Report

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
April 20, 2026
Retrieved from
https://hai.stanford.edu/assets/files/ai_index_report_2026.pdf
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.
Sha Sajadieh, Loredana Fattorini, Raymond Perrault, Yolanda Gil, Vanessa Parli, Lapo Santarlasci, Juan Pava, Nestor Maslej, Russ Altman, Erik Brynjolfsson, Carla Brodley, Jack Clark, Virginia Dignum, Vipin Kumar, James Landay, Terah Lyons, James Manyika, Juan Carlos Niebles, Yoav Shoham, Elham Tabassi, Russell Wald, Toby Walsh, Dan Weld. “The AI Index 2026 Annual Report,” AI Index Steering Committee, Institute for Human-Centered AI, Stanford University, Stanford, CA, April 2026.

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
April 20, 2026
Retrieved from
https://hai.stanford.edu/assets/files/ai_index_report_2026.pdf
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.
Sha Sajadieh, Loredana Fattorini, Raymond Perrault, Yolanda Gil, Vanessa Parli, Lapo Santarlasci, Juan Pava, Nestor Maslej, Russ Altman, Erik Brynjolfsson, Carla Brodley, Jack Clark, Virginia Dignum, Vipin Kumar, James Landay, Terah Lyons, James Manyika, Juan Carlos Niebles, Yoav Shoham, Elham Tabassi, Russell Wald, Toby Walsh, Dan Weld. “The AI Index 2026 Annual Report,” AI Index Steering Committee, Institute for Human-Centered AI, Stanford University, Stanford, CA, April 2026.

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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 professional service robots installed globally, by application area”, part of the following publication: Charlie Giattino, Edouard Mathieu, Veronika Samborska, and Max Roser (2023) - “Artificial Intelligence”. Data adapted from AI Index Report. Retrieved from https://auto-epoch.owid.pages.dev:8789/20260424-104218/grapher/annual-professional-service-robots-installed-by-area.html [online resource] (archived on April 24, 2026).

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:

International Federation of Robotics via AI Index Report (2026) – with minor processing by Our World in Data

Full citation

International Federation of Robotics via AI Index Report (2026) – with minor processing by Our World in Data. “Annual professional service robots installed globally, by application area” [dataset]. AI Index Report, “AI Index Report” [original data]. Retrieved May 8, 2026 from https://auto-epoch.owid.pages.dev:8789/20260424-104218/grapher/annual-professional-service-robots-installed-by-area.html (archived on April 24, 2026).

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Use these URLs to programmatically access this chart's data and configure your requests with the options below. Our documentation provides more information on how to use the API, and you can find a few code examples below.

Data URL (CSV format)
https://auto-epoch.owid.pages.dev/grapher/annual-professional-service-robots-installed-by-area.csv?v=1&csvType=full&useColumnShortNames=false
Metadata URL (JSON format)
https://auto-epoch.owid.pages.dev/grapher/annual-professional-service-robots-installed-by-area.metadata.json?v=1&csvType=full&useColumnShortNames=false

Code examples

Examples of how to load this data into different data analysis tools.

Excel / Google Sheets
=IMPORTDATA("https://auto-epoch.owid.pages.dev/grapher/annual-professional-service-robots-installed-by-area.csv?v=1&csvType=full&useColumnShortNames=false")
Python with Pandas
import pandas as pd
import requests

# Fetch the data.
df = pd.read_csv("https://auto-epoch.owid.pages.dev/grapher/annual-professional-service-robots-installed-by-area.csv?v=1&csvType=full&useColumnShortNames=false", storage_options = {'User-Agent': 'Our World In Data data fetch/1.0'})

# Fetch the metadata
metadata = requests.get("https://auto-epoch.owid.pages.dev/grapher/annual-professional-service-robots-installed-by-area.metadata.json?v=1&csvType=full&useColumnShortNames=false").json()
R
library(jsonlite)

# Fetch the data
df <- read.csv("https://auto-epoch.owid.pages.dev/grapher/annual-professional-service-robots-installed-by-area.csv?v=1&csvType=full&useColumnShortNames=false")

# Fetch the metadata
metadata <- fromJSON("https://auto-epoch.owid.pages.dev/grapher/annual-professional-service-robots-installed-by-area.metadata.json?v=1&csvType=full&useColumnShortNames=false")
Stata
import delimited "https://auto-epoch.owid.pages.dev/grapher/annual-professional-service-robots-installed-by-area.csv?v=1&csvType=full&useColumnShortNames=false", encoding("utf-8") clear