The artificial intelligence (AI) industry has seen $50B in total all time funding. Let’s analyze the investors making bets into AI and identify the most active firms.
The graphic below shows AI investors based on their number of investments into the sector. If an investor participates in two investment rounds in the same company (such as a Series A and Series B), that would qualify as two investments for this graphic.
As the graphic demonstrates, Y Combinator has made the most bets in the AI sector with 75 investments. New Enterprise Associates follows in second place with 64 investments. Examples of companies Y Combinator invested in include Vicarious, Sift Science, Atomwise, and Standard Cognition. Let’s see which investors make their way onto this list in 2019!
Now that 2018 is complete, let’s see how exit activity for artificial intelligence (AI) compares to previous years. The graphic below shows the total annual AI exit events over time.
As the graphic demonstrates, 2018 saw a drop in AI exit activity compared to the previous year. The 58 exit events in 2018 represent a 22% decrease from the 74 exit events in 2017, which was the highest year on record for exit activity. However, AI exits are still on a general upward trend, with a 5-year CAGR of 24% from 2013 to 2018. Let’s see if the AI exit activity in 2019 will jump back up to the 2017 level.
With 2018 now behind us, let’s examine how artificial intelligence (AI) funding compares to previous years. The graphic below shows the total annual AI funding amounts over time.
As the graphic demonstrates, 2018 experienced the highest AI funding on record at $18B. It represents a 24% increase from the previous year’s funding. In addition, AI funding grew at a CAGR of 62% from 2013 to 2018. It’ll be interesting to observe if the funding growth will remain strong in the new year.
The following graphs highlight the exit activity in the Artificial Intelligence sector. The graphics include data through July 2017.
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.
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.
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 April 2017.
The graph above shows the total amount of VC funding broken out by round. 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.
The graph above shows the total count of funding events broken out by round. 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 1819 Artificial Intelligence companies in 13 categories across 70 countries, with a total of $16.1 Billion in funding. Click here to learn more about the full Artificial Intelligence market report.