We at Venture Scanner are tracking 1104 Artificial Intelligence companies across 13 categories, with a combined funding amount of $6.27 Billion. The 15 visuals below summarize the current state of Artificial Intelligence.
1. Artificial Intelligence Market Overview
We organize Artificial Intelligence into the 13 categories listed below:
Deep Learning/Machine Learning (General): Companies that build computer algorithms that operate based on their learnings from existing data. Examples include predictive data models and software platforms that analyze behavioral data.
Deep Learning/Machine Learning (Applications): Companies that utilize computer algorithms that operate based on existing data in vertically specific use cases. Examples include using machine learning technology to detect banking fraud or to identify the top retail leads.
Natural Language Processing (General): Companies that build algorithms that process human language input and convert it into understandable representations. Examples include automated narrative generation and mining text into data.
Natural Language Processing (Speech Recognition): Companies that process sound clips of human speech, identify the exact words, and derive meaning from them. Examples include software that detects voice commands and translates them into actionable data.
Computer Vision/Image Recognition (General): Companies that build technology that process and analyze images to derive information and recognize objects from them. Examples include visual search platforms and image tagging APIs for developers.
Computer Vision/Image Recognition (Applications): Companies that utilize technology that process images in vertically specific use cases. Examples include software that recognizes faces or enables one to search for a retail item by taking a picture.
Gesture Control: Companies that enable one to interact and communicate with computers through their gestures. Examples include software that enables one to control video game avatars through body motion, or to operate computers and television through hand gestures alone.
Virtual Personal Assistants: Software agents that perform everyday tasks and services for an individual based on feedback and commands. Examples include customer service agents on websites and personal assistant apps that help one with managing calendar events, etc.
Smart Robots: Robots that can learn from their experience and act autonomously based on the conditions of their environment. Examples include home robots that could react to people’s emotions in their interactions and retail robots that help customers find items in stores.
Recommendation Engines and Collaborative Filtering: Software that predicts the preferences and interests of users for items such as movies or restaurants, and delivers personalized recommendations to them. Examples include music recommendation apps and restaurant recommendation websites that deliver their recommendations based on one’s past selections.
Context Aware Computing: Software that automatically becomes aware of its environment and its context of use, such as location, orientation, lighting, and adapts its behavior accordingly. Examples include apps that light up when detecting darkness in the environment.
Speech to Speech Translation: Software which recognizes and translates human speech in one language into another language automatically and instantly. Examples include software that translates video chats and webinars into multiple languages automatically and in real-time.
Video Automatic Content Recognition: Software that compares a sampling of video content with a source content file to identify the content through its unique characteristics. Examples include software that detects copyrighted material in user-uploaded videos by comparing them against copyrighted material.
2. Company Count by Artificial Intelligence Category
The above graph summarizes the number of companies in each Artificial Intelligence category to show which categories are dominating the current market. The Machine Learning (Applications) category is leading the way with 263 companies, followed by the Natural Language Processing category with 154 companies.
3. Funding by Artificial Intelligence Category
The above graph summarizes the total amount of funding in each Artificial Intelligence category. The Machine Learning (Applications) category is leading the market with over $2B in total funding, which is 3X the total funding of the second highest category, Natural Language Processing with $662M.
4. Venture Investing in Artificial Intelligence
The above graph compares the total venture funding in each Artificial Intelligence category to the number of companies in the category. The Machine Learning (Applications) category is leading in both stats with over $2B in funding and 263 companies. Natural Language Processing is the runner-up in both stats with $662M in funding and 154 companies.
5. Artificial Intelligence Total Funding by Year
The above graph summarizes the total funding raised by Artificial Intelligence companies each year. 2015 was the best year in Artificial Intelligence funding with almost $1.2B raised, with 2014 in the second place with a total of $1B raised.
6. Average Funding by Artificial Intelligence Category
The above graph summarizes the average company funding in each Artificial Intelligence category. The Machine Learning (Applications) category leads the market with $17M in funding per company, followed by the Smart Robots and Gesture Control categories each with about $14M in funding per company.
7. Average Age by Artificial Intelligence Category
The above graph summarizes the average age of companies in each Artificial Intelligence category. Speech to Speech Translation ranks as the most mature Artificial Intelligence category with an average age of 13 years per company, which is more than 1.5X the average age of the three runner-up categories (Gesture Control, Video Content Recognition, and Speech Recognition, each with an average age of about 8 years per company).
8. Median Age by Artificial Intelligence Category
The above graph summarizes the median age of companies in each Artificial Intelligence category. Video Content Recognition ranks as the most mature Artificial Intelligence category with a median age of 7.8 years per company, followed by Speech to Speech Translation with a median age of 7.2 years per company.
9. Artificial Intelligence Company Count by Country
The above map shows the number of Artificial Intelligence companies located in different countries. The United States ranks as the top country with 499 Artificial Intelligence companies.
10. Artificial Intelligence VC Funding by Country
The above map shows the amount of Artificial Intelligence venture capital funding in different countries. The United States has the most Artificial Intelligence VC funding at $4.2B.
11. Artificial Intelligence Companies Founded by Year
The above graph summarizes the number of Artificial Intelligence companies founded in a certain year. 2013 ranks as the top year with 118 Artificial Intelligence companies founded, followed by 2012 with 103 companies founded.
12. Artificial Intelligence Funding by Vintage Year
The above graph summarizes the total amount of funding raised by the Artificial Intelligence companies founded in a certain year. Artificial Intelligence companies founded in 2010 have raised the most funding at $566M, with those founded in 2012 at a close second with $556M.
13. Artificial Intelligence Headcount Distribution
The above graph summarizes the percentage of Artificial Intelligence companies with a certain employee headcount range. Companies with 1–50 employees make up almost 90% of the market.
14. Number of Artificial Intelligence Investments by Selected Investors
The above graph summarizes the total number of investment rounds Artificial Intelligence investors participated in. Accel outperformed all of its peers, having made 23 investments into Artificial Intelligence companies. New Enterprise Associates is the runner-up with 18 investments.
15. Number of Artificial Intelligence Companies Backed by Selected Investors
The above graph summarizes the number of unique Artificial Intelligence companies funded by selected investors. Accel takes the top spot by having invested in a total of 20 unique Artificial Intelligence companies, which is almost 1.5X the number of companies invested by the runner-up, Intel Capital (14 companies).
Venture Scanner is your analyst and technology powered startup research firm. If you would like access to the full Artificial Intelligence landscape and dataset, visit www.venturescanner.com/artificial-intelligence or reach out to [email protected].