Artificial Intelligence Sector Overview – Q4 2017

As we previously noted, interest in AI has exploded. Its applications can be found in virtually every industry from marketing to healthcare to finance. On our AI research platform, we have classified the companies in the sector into functional categories. This blog post aims to examine these categories and how they compare with one another through a series of graphics.

Machine Learning Applications Is the Largest AI Category

Let’s start off by looking at the Logo Map for the AI sector. As of January 2018, we have classified 2,029 AI startups into 13 categories which collectively raised $27 billion in funding. The Logo Map highlights the number of companies in each category and a random sampling of these companies.

Artificial Intelligence Logo Map
Artificial Intelligence Logo Map

We have seen what the different categories in AI are and how many companies are within each category. What about their funding and maturity in relation to one another? Let’s look at our Innovation Quadrant to find out.

Most of the AI Categories Are Pioneers

Our Innovation Quadrant for the AI sector divides the categories within the sector into four different quadrants according to their average funding and average age. The Heavyweights are the categories with companies that have reached maturity with significant financing. The Established are those that have reached maturity with less financing. The Disruptors are less mature but with significant financing. The Pioneers are less mature and with earlier stages of financing.

Artificial Intelligence Innovation Quadrant
Artificial Intelligence Innovation Quadrant

We can see from our Innovation Quadrant above that most of the categories within AI belong in the Pioneers quadrant. The Smart Robots and Recommendation Engines categories have raised more funding and are in the Disruptor quadrant. Speech-to-Speech Translation and Speech Recognition are the most mature categories with significant funding.

We’ve now seen how the AI sector is categorized, and the relative stages of innovation for those categories. How do these categories stack up against one another in a holistic view? Let’s look at the Total Funding and Company Count Graph for AI.

Machine Learning Applications Category Dominates the Sector

The graph below shows the total amount of venture funding and company count in each AI category.

Artificial Intelligence Total Funding and Company Count by Category
Artificial Intelligence Total Funding and Company Count by Category

We can see from the graph above that the Machine Learning Applications category dominates all the other AI categories by far, with a total funding of $13 billion and 669 companies. This category is comprised of companies utilizing computer algorithms to automatically optimize some part of their operations. Some example companies in this category include CustomerMatrix, Ayasdi, Drive.ai, and Cylance.

Conclusion: The AI Sector is Thriving

The graphics above indicate that the Machine Learning Applications category stands out against other categories in terms of funding and maturity, while most other AI categories are pioneers and show huge potential for growth and development.

What are your thoughts on this? Let us know in the comments section below.

To learn more about our complete Artificial Intelligence report and research platform, visit us at www.venturescanner.com or contact us at info@venturescanner.com.

Age by Category in Artificial Intelligence – Q3 2017

The following graph shows average and median age in the Artificial Intelligence sector. The graphic includes data through July 2017.

Artificial Intelligence Age by Category
Artificial Intelligence Age by 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 13 years, followed by the Speech Recognition category with an average age of 9 years. The Speech Recognition category also has the highest median age at around 8.5 years. Machine Learning Applications is the youngest category with an average age of 5 years and a median age of 4.5 years.

We are currently tracking 1965 Artificial Intelligence companies in 13 categories across 70 countries, with a total of $23.7 Billion in funding. Click here to learn more about the full Artificial Intelligence market report.

Where in the World Are Artificial Intelligence Startups? – Q3 2017

The analyses below summarize where Artificial Intelligence (AI) innovations are occurring. The graphics includes data through July 2017.

Artificial Intelligence Company Count by Country
Artificial Intelligence Company Count by Country

The above map shows the number of AI companies located in different countries. The United States ranks as the top country with over 1000 companies.

Artificial Intelligence VC Funding by Country
Artificial Intelligence VC Funding by Country

The above map shows the amount of total AI startup venture capital funding in different countries. The United States has the most VC funding at around $10B.

We are currently tracking 1951 AI companies in 13 categories across 70 countries, with a total of $23.3B in funding. Click here to learn more about the full Artificial Intelligence market report.

Artificial Intelligence Companies Founded by Year – Q3 2017

The following graph shows the founding year distribution in the Artificial Intelligence sector. The graphic includes data through July 2017.

Artificial Intelligence Companies Founded by Year
Artificial Intelligence Companies Founded by Year

The above graph summarizes the number of Artificial Intelligence companies founded in a certain year. 2014 ranks at the top with around 259 companies founded in that year alone. 2013 is the runner-up with 244 companies founded in that year.

We are currently tracking 1942 Artificial Intelligence companies in 13 categories across 70 countries, with a total of $23 Billion in funding. Click here to learn more about the full Artificial Intelligence market report.

Artificial Intelligence Funding by Round – Q3 2017

The following two graphs summarize the rounds of funding going into the Artificial Intelligence (AI) space. Please note these graphics are made using data through July 2017.

Artificial Intelligence Funding Amount by Round
Artificial Intelligence Funding Amount by Round

The graph above shows the total amount of VC funding broken out by round. From 2006 to 2016, we saw a general increase in the overall sector funding, with the total amount peaking in 2016. Earlier stage funding rounds (Series A, B, and C) made up most of the funding amount.

Artificial Intelligence Funding Count by Round
Artificial Intelligence Funding Count by Round

The graph above shows the total count of funding events broken out by round. From 2006 to 2016 we’ve seen a general upward trend that peaked in 2014 and 2015, and then declined slightly in 2016. Earlier stage funding such as Seed, Series A, and Series B events make up the majority of funding event counts.

We are currently tracking 1917 Artificial Intelligence companies in 13 categories across 70 countries, with a total of $21.5 Billion in funding. Click here to learn more about the full Artificial Intelligence market report.

Artificial Intelligence Exits by Category and by Year – Q3 2017

The following graphs highlight the exit activity in the Artificial Intelligence sector. The graphics include data through July 2017.

Artificial Intelligence Exits by Category
Artificial Intelligence Exits by Category

The above graph summarizes the number of exits (acquisitions and IPOs) in each Artificial Intelligence category. The Machine Learning Applications category leads the sector with 4 IPOs and 43 acquisitions. The Natural Language Processing category is the runner-up with 4 IPOs and 29 acquisitions.

Artificial Intelligence Exits by Year
Artificial Intelligence Exits by Year

The above graph summarizes the number of exits (acquisitions and IPOs) in Artificial Intelligence by year. 2017 currently leads the sector with 1 IPO and 41 acquisitions, with 2016 following behind with 39 acquisitions.

We are currently tracking 1896 Artificial Intelligence companies in 13 categories across 70 countries, with a total of $19B in funding. Click here to learn more about the full Artificial Intelligence market report.

Average and Median Age by Artificial Intelligence Category – Q3 2017

The following graph shows average and median age in the Artificial Intelligence sector. The graphic includes data through April 2017.

Average/Median Age by AI Category
Average/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 13 years, followed by the Speech Recognition category with an average age of 9 years. The Speech Recognition category also has the highest median age at around 9 years.

We are currently tracking 1866 Artificial Intelligence companies in 13 categories across 70 countries, with a total of $17.6 Billion in funding. Click here to learn more about the full Artificial Intelligence market report.