Average and Median Age by Artificial Intelligence Category – Q1 2017

The following graph shows average and median age in the Artificial Intelligence sector. The graphic includes data through October 2016.

Average and Median Age by AI Category
Average and Median Age by AI Category
The above graph summarizes the average and median age of companies in each Artificial Intelligence category. The Speech to Speech Translation category has the highest average age at around 14 years, and the Speech Recognition category has the highest median age at around 10 years.

We are currently tracking 1539 Artificial Intelligence companies in 13 categories across 71 countries, with a total of $9.9 Billion in funding. Click here to learn more about the full AI landscape report and database.

Artificial Intelligence Funding by Type – Q4 2016

The following two graphs summarize the types of funding going into the Artificial Intelligence (AI) space.

Artificial Intelligence Funding Type  - Amount
Artificial Intelligence Funding Type  –  Amount

The graph above shows the total amount of VC funding broken out by type. In recent years, we’ve seen a general increase in the amount of funding across the board, with growth in the amount of practically all funding stages.

Artificial Intelligence Funding Type  -  Count
Artificial Intelligence Funding Type  –  Count

The graph above shows the total count of funding events broken out by type. Similar to the earlier graph, we’ve seen a general upward trend over these past few years. Earlier stage deals (Seed, Series A) make up a larger share of the total count.

We are currently tracking 1,522 Artificial Intelligence companies in 13 categories across 73 countries, with a total of $9.8 Billion in funding. Click here to learn more about the full AI landscape report and database.

Artificial Intelligence Companies Founded by Year – Q4 2016

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Artificial Intelligence Companies Founded by Year
The above graph summarizes the number of Artificial Intelligence companies founded in a certain year. 2013 ranks at the top with around 188 companies founded in that year alone. 2014 is the runner-up with 173 companies founded in that year.

We are currently tracking 1503 Artificial Intelligence companies in 13 categories across 73 countries, with a total of $9.3 Billion in funding. Click here to learn more about the full Artificial Intelligence landscape report and database.

Artificial Intelligence Startup Landscape Trends and Insights – Q4 2016

A report providing an overview of the Artificial Intelligence startup landscape, graphical trends and insights, and recent funding and exit events. Click here to see this entire deck on our new blog.

We are currently tracking 1500 Artificial Intelligence companies in 13 categories across 73 countries, with a total of $9.1 Billion in funding. Click here to learn more about the full Artificial Intelligence landscape report and database.

Artificial Intelligence Category Innovation Quadrant – Q4

Artificial Intelligence Category Innovation Quadrant
Artificial Intelligence Category Innovation Quadrant
Our Innovation Quadrant provides a snapshot of the average funding and average age for the different Artificial Intelligence categories and how they compare with one another.

  • Heavyweights: Categories with high average funding and high average age. These categories are comprised of companies that have reached maturity with significant financing.
  • Established: Categories with low average funding and high average age. These categories are comprised of companies that have reached maturity with less financing.
  • Disruptors: Categories with high average funding and low average age. These categories are comprised of companies that are less mature with significant financing.
  • Pioneers: Categories with low average funding and low average age. These categories are comprised of companies that are less mature with earlier stages of financing.
The definitions of the Artificial Intelligence categories represented in the above Innovation Quadrant are as follows:

Deep Learning/Machine Learning (Platforms): 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: 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.

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 (Platforms): 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 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.

Personalized Recommendation Engines: 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.

We are currently tracking 1498 Artificial Intelligence companies in 13 categories across 73 countries, with a total of $9 Billion in funding. Click here to learn more about the full Artificial Intelligence landscape report and database.

Artificial Intelligence Activity by Selected Investors – Q4 2016

Artificial Intelligence Activity by Selected Investors

The above analysis summarizes the total number of investment rounds Artificial Intelligence investors participated in, and the number of unique AI companies funded by selected investors. 500 Startups and Y Combinator take the lead in both categories, both making the highest number of investments and backing the most AI companies.

We are currently tracking 1,494 Artificial Intelligence companies in 13 categories across 73 countries, with a total of $9 Billion in funding. Click here to learn more about the full Artificial Intelligence landscape report and database.

Average Funding by Artificial Intelligence Category – Q4 2016

Artificial Intelligence Average Funding

The above analysis summarizes the average company funding in each Artificial Intelligence category. The Smart Robots category leads the sector with $22M in average funding per company, followed by the Gesture Control category with around $18M in average funding per company.

We are currently tracking 1,481 Artificial Intelligence companies in 13 categories across 73 countries, with a total of $8.8 Billion in funding. Click here to learn more about the full Artificial Intelligence landscape report and database.