“Change is the only constant” in the world of AI, and the line-up of AI unicorns are exemplifying this today by showcasing transformational solutions that essentially offer benefits to all industries. The demonstrated continuous innovation of these AI unicorns are quite impressive. With many diverse applications, tools, and platforms, customers are better poised to embark on their own successful AI journey confidently and seamlessly.

According to Gartner, 66% of organizations have increased AI investments since the onset of the COVID-19 pandemic. The most promising AI startups are grabbing the attention of corporate investors worldwide. This is a cue for private startups to up their AI game and create strategic business plans that embrace the new AI trends.

What is a Unicorn Company?

A unicorn company is a private organization with a valuation of over $1 billion. Some of the former unicorns that became immensely popular include Airbnb, Google, Netflix, Facebook, and more.

The top 2021 global AI unicorns (Source: CB INSIGHTS) that have successfully attracted sufficient attention to drive their valuations to the unicorn levels are showcased below. Let’s assess what they’ve been focused on and see if we can discern any emerging AI tech trends.

What does the landscape tell us?

Although AI has been described as one of the critical technologies that will fuel innovation in the current decade, the global unicorn market and financial metrics indicate a moderate status. Of the 2021 global unicorn companies cited in the CB INSIGHTS report, only 8% are categorized as AI startups. One reason may be the criteria by which a startup is classified as AI. Moving forward, we can foresee this ratio increasing well beyond the current 8%. What’s interesting as well is that valuation-wise, these AI unicorns amount to 11% of the total unicorn valuations. There are slightly higher average valuations on AI unicorns than the rest. Of course, one single AI unicorn MVP (ByteDance, $140B valuations) contributes significantly to this higher AI unicorn valuation average. The average valuation for AI unicorns drops when removing this outlier and results in only 6% of the total unicorn valuation. In other words, expect to see some additional growth in the coming year with more AI startups achieving unicorn status. One example I just ran across recently is Morning Consult, achieving a meteoric rise to a $1B valuation as it closed its $60M Series B round.

What has the focus been on for the top 10 AI Unicorns?

AI unicorns have been tackling many application areas by applying automation of advanced algorithmic decision making, machine learning methods, natural language and image processing, and deriving new insights in real-time from data and user interactions. A few examples from our top 10 list include:

Broader Applications

Content and Data Focus:

  • ByteDance provides AI and machine learning that can personalize social media and content platforms with innovative recommendation engines.
  • Scale AI Inc. uses AI to create high-quality, better-annotated datasets for different types of AI applications like autonomous vehicles, Virtual Reality, robotics, and more.
  • SenseTime has broad AI technology research utilizing deep learning in applications spanning health, education, smart cities, automotive and more.

Automation and Scaling:

  • SambaNova Systems is focused on AI/ML and big data analytics at scale and over distributed environments.
  • UiPath provides streamlined SaaS Robotic Process Automation (RPA) solutions.
  • Automation Anywhere offers cloud-native automation and RPA solutions.

Focused Applications

Autonomous Vehicles:

  • Pony.ai focuses on autonomous vehicle technology solutions.


  • Feedzai Inc. applies AI to fraud detection and financial crime solutions.
  • HighRadius provides automation in the AI-Fintech domain.

Harvesting Public Data:

  • Dataminr utilizes AI to analyze data across various public databases to predict unforeseen events for the public limited companies.

Improved categorization of AI startups

AI is a vast space, and at times the ‘label’ in and of itself doesn’t honestly explain the depth and breadth of innovation that an AI startup/unicorn offers. With an improved classification of AI startups, investors and analysts alike will be better poised in providing more tangible comparisons and trends of current AI innovation areas, and at the same time be able to discern more succinctly gaps in technology and the resulting need for emerging innovative AI trends. Below are a few suggested classification categories. Although not an exhaustive list, it provides a starting point to create a more comprehensive model when classifying AI startups:

Focus Areas:

  • Broad or universal solutions that span applications and domains.
  • Targeted solutions that address specific industries, applications, or data sets.

Technology Offering:

  • An extensive platform can address an entire AI value chain or a specific tool that addresses a targeted need.
  • Automation and distributed infrastructure focus that enables real-time processing of streaming data sets and embodies cloud, edge computing, data centers, etc.
  • Data engineering and data management focus on support of quality data consumed by AI systems and address the ongoing operations ‘data quality of machine learning and deep learning systems.

Parting Words

AI is still poised for continued growth in 2022 and beyond. As more AI startup solutions become available, investors and customers alike will have to assess each offered innovation and identify where it fits into the AI-driven value chain. The AI ecosystem is complex, so offering solutions that are easy to deploy and that produce immediate benefit in a seamless and trustworthy fashion will be clear winners regardless of the application domain or technology focus that new AI startups will offer. Given the growth with large and continuous data volumes being generated across all sectors globally, adopting AI solutions en masse will become a necessity for all.