Artificial Intelligence Average Funding Event Size Shows Steady Growth

For this quarter’s funding analysis, let’s examine how average funding event sizes in the artificial intelligence (AI) sector are evolving. The graphic below shows the AI average funding event size over time by quarter.

Artificial Intelligence Average Funding Event Size
Artificial Intelligence Average Funding Event Size

As the graphic demonstrates, AI average funding event size in Q1 2019 was at $35M. This is an increase of 75% from the $20M in Q1 2018. The average funding size has been on a robust upward trend, with the average funding size last quarter around 3 times larger than it was 5 years ago. The top three funding events in Q1 2019 include a $940M round from Nuro, a $600M round from Horizon Robotics, and a $530M round from Aurora.

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Artificial Intelligence Report Highlights  – Q1 2019

Here is our Q1 2019 summary report on the artificial intelligence startup sector. The following report includes a sector overview and recent activity.

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AI Investors With the Most Activity

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.

Artificial Intelligence Investors with Most Investments
Artificial Intelligence Investors with Most Investments

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!

To learn more about our complete artificial intelligence dynamic report, visit us at www.venturescanner.com or contact us at info@venturescanner.com.

AI Exit Activity Slowed in 2018

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.

Artificial Intelligence Exits Over Time
Artificial Intelligence Exits 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.

To learn more about our complete artificial intelligence dynamic report, visit us at www.venturescanner.com or contact us at info@venturescanner.com.

Artificial Intelligence Report Highlights  – Q4 2018

Here is our Q4 2018 summary report on the artificial intelligence startup sector. The following report includes a sector overview and recent activity.

To learn more about our complete artificial intelligence dynamic report, visit us at www.venturescanner.com or contact us at info@venturescanner.com.

AI Funding Reaches Record Year in 2018

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.

AI Annual Funding Over Time
AI Annual Funding 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.

To learn more about our complete artificial intelligence dynamic report, visit us at www.venturescanner.com or contact us at info@venturescanner.com.

Machine Learning-Related Categories Lead Artificial Intelligence Funding

We’ve previously highlighted that artificial intelligence (AI) funding has seen explosive growth in recent years. When we take a closer look at the funding trends for each category within AI, we notice two key takeaways:

  • The Machine Learning Platforms category leads the sector in Q3 funding
  • The Machine Learning Applications category leads the sector in all-time funding

We’ll highlight these takeaways with some graphics and discussions below.

The Machine Learning Platforms Category Leads AI In Q3 Funding

To start off, let’s review the amount of funding raised this quarter by each category within artificial intelligence.

Artificial Intelligence Latest Quarter Category Funding
Artificial Intelligence Latest Quarter Category Funding

The above graphic highlights that the Machine Learning Platforms category leads the sector in Q3 funding with $1.9B. The Computer Vision Platforms category follows in second place with $1.6B in Q3 funding.

Machine Learning Platform companies build self-learning algorithms that operate based on existing data. They include predictive data models and software platforms that analyze behavioral data. Some example companies include C3 IoT, DataRobot, Sentient, and AYASDI.

Let’s now investigate how the AI categories’ funding compare with each other historically.

The Machine Learning Applications Category Leads the Sector in All-Time Funding

The graph below shows the all-time funding for the various artificial intelligence categories. The Q3 funding and growth rates of these categories are also highlighted.

Artificial Intelligence Total Category Funding
Artificial Intelligence Total Category Funding

As the bar graph indicates, the Machine Learning Applications category leads AI in total funding at $19B. This is more than twice the funding of the next category, Machine Learning Platforms at almost $9B.

Machine Learning Application companies utilize self-learning algorithms to optimize vertically-specific business operations. Examples include using machine learning to detect banking fraud or to identify relevant sales leads. Some example companies are Sift Science, SparkCognition, Sumo Logic, and BenevolentAI.

In summary, the two machine learning-related categories are leading the AI sector in funding. Let’s see how the the rest of 2018 shapes up for artificial intelligence!

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.