Who Is Leading The AI Race?

Artificial Intelligence is becoming an extremely important function of the next evolution of technology. Therefore, I looked at every AI startup at the end of 2017. This was a collection of 1600+ startups globally. My goal was to understand the applications of AI/ML in every industry, the current fundraising environment and what countries are leading in AI development.

My summarised findings are below. You will see what countries are leading in the AI development and fundraising. In addition, I broke apart all 1600+ startups into 22 subcategories by function and application. This will help you understand where AI leads in development, funding and exits for each industry and application.

This report will give entrepreneurs, investors and companies a sense of where opportunities in AI exist and a benchmark for valuations.

For reference, I only looked at startups that have raised Angel-Series C funding. I combed through every company and applied my best judgement to keep startups if they actual apply a form of AI.


Countries Leading AI Development

The United States generated almost 1.5x the amount of startups than all other countries outside the US combined (International). It’s intriguing to see the United Kingdom as the leader of AI development outside the US, with Canada and Israel not too far behind.

Countries leading by total investment into AI startups paints a different picture. United States generated almost 2x the amount of investment than the entire international community received. However, China, Hong Kong and Japan have pushed a significant amount of investment into a smaller number of companies.

For both the US and all International companies, the average funding for AI startups hovers around $10M-$11M. However you’ll find that Hong Kong, China and Japan startup’s average raise is much higher. This could imply these startups are overvalued or AI startups in these markets are performing very well. Without these outliers, the average funding for International AI startups is closer to $5M.

It’s interesting to note the US as 3x as many more exits than the International community. Runner up is actually Israel, United Kingdom, Canada and China.


AI Startup Subcategories

After looking at over 1600 companies, I was able to come up with 2 main categories for AI startups, that further breaks into 22 subcategories. The two main categories are Horizontal AI and Vertical AI.

The Horizontal AI category are startups that are building AI tools, platforms or infrastructure that can be used across almost all industries. Think of this category as the hammer, wood or measuring tape of AI. This category breaks into 9 subcategories outlined below:

  • Analytics: AI built for analysing and pulling insights from large data sets
  • Assistant: Tools that are built to be forms of chat bots
  • Data: Startups that acquire, analyse and sell private data sets
  • Infrastructure: Startups building the physical or software infrastructure to empower AI tools
  • NLP: AI startups focused on understanding speech, voice or text (natural language processing)
  • Robotics: AI built for robots to perform any types of tasks, movements, etc
  • Security: Tools built to protect companies from security threats
  • Tool: Startups building general AI algorithms
  • Vision: Startups building image recognition tools

The Vertical AI category is applying AI tools to a particular industry to provide a service. Think of these as the plumber, construction worker or appraiser – they are simply using tools from Horizontal AI to provide unique services. This category is broken into 13 subcategories outlined below:

  • Agriculture: Startups building AI services to improve farming
  • Automotive: Startups building navigation, self-driving, maintenance, or any applications for vehicles
  • Commerce: AI companies built for different forms of commerce
  • Consumer: AI startups built for consumer lifestyle
  • CRM: AI startups focused on sales or managing customer questions
  • Education: AI startups focused on bettering education for students, teachers or schools
  • Enterprise: AI startups solely focused on improving operations in corporations, including accessing/sharing information, automating menial tasks, etc
  • Fintech: AI tools built for banking, investment, wealth management or efficient/safer ways to transact with one another
  • Gaming: Tools build for better gaming experiences, content or distribution
  • Healthcare: Any forms of managing, monitoring or servicing healthcare
  • IoT: Tools that collect, analyse or manage IoT device information
  • Marketing: Different forms of advertising or marketing activities
  • Recruiting: Tools built to source, analyse and track potential hires and or existing employees


Horizontal And Vertical Subcategory Break Down

Both the US and International community have built more Vertical AI startups than Horizontal AI startups.

However, the International community actually raises more funding for the Horizontal AI category than their Vertical AI category.


Horizontal AI Subcategory Statistics

In Horizontal AI, most US startups are created in the Analytics, Vision, Tool and Security subcategories. The International community differs slightly being that Vision, Analytics, Tool and NLP subcategories lead.

In the Horizontal AI Category, more funding is pushed into Tool, Analytics, Robotics and Vision subcategories for US startups. Whereas International startups it is Vision, Robotics, Infrastructure and Tool subcategories. This can be slightly skewed by the China, Hong Kong and Japan funding environments.

In the Horizontal AI category, you’ll notice most subcategories are at or above the average funding rate for all AI startups. You’ll also notice the Infrastructure subcategory gets a substantial amount of funding outside the US. This anomaly is from the China, Hong Kong and Japan funding environment.

It’s notable that the Analytics subcategory leads in the number of exits compared to all other subcategories in US and International.

Outside the US, the UK, Israel, China, Canada, and France are leading the development of Horizontal AI startup subcategory.


Vertical AI Subcategory Statistics

In the Vertical AI Category, most US startups are created in the Marketing, CRM, Enterprise and Healthcare subcategories. Whereas in International it is Fintech, Enterprise, Healthcare and Marketing subcategories.

In the Vertical AI category, more funding is pushed into Automotive, Healthcare, Fintech and Marketing subcategories. Whereas in International it is Healthcare, Fintech, Marketing and CRM subcategories.

In the Vertical AI category, you’ll notice US startups in Automotive and Agriculture receive a substantial amount of funding compared to the industry average. Outside the US you’ll find most subcategories raise below the average funding rate for AI startups.

Most exits in Vertical AI are within Marketing, CRM or Enterprise subcategories. However, it is surprising that the Consumer subcategory is one of the top exit subcategories both in US and International.

Outside the US, the UK, Canada, Israel, Germany and India are leading the development of Vertical AI startup subcategory.



There are many inferences you can pull from this data. I hope this helps puts the AI industry into perspective for many investors, entrepreneurs and corporations. It’s clear the United States outpaces all other countries in AI development and funding. Nonetheless, capital is flowing into this industry quickly and there are many opportunities to fill in each subcategory globally.

Of the 1600 AI startups, I believe about 360 will have big impact on their subcategory. Please connect or follow me as I will break down what companies to watch for in each subcategory in the future.