Many of this year’s hottest AI companies are taking the spotlight from last year’s darlings.
What’s new: CB Insights, which analyzes early-stage companies, published its annual list of the 100 “most promising” startups in AI.
Highlights: Startups in the AI 100 have raised $7.4 billion collectively. Most are headquartered in the U.S., but others are based in 13 countries including Canada, China, and the UK.
- Around 80 percent of the list is new this year. Entire categories turned over, including not only AI strongholds like Cybersecurity and Transportation but also Food & Agriculture, Media & Entertainment, and Retail & Warehousing.
- Several of the survivors are in the Healthcare sector, including Atomwise, Butterfly, Owking, Paige.ai, and Viz.ai.
- Healthcare has the largest number of companies, 13 in all. Retail is second with nine, which is roughly double last year’s tally.
- The list includes 10 unicorns, or companies valued at more than $1 billion, down from 15 last year.
- Among the most richly funded are U.S. autonomous vehicle developer Aurora ($693 million), UK AI-chip designer Graphcore ($536 million), and Lemonade, an American insurance company that uses AI to find fraudulent claims ($480 million).
- For the first time, the list highlights AI startups making products and services that address a variety of industries. Such “cross-industry tech” includes model development, computer vision, natural language processing, business intelligence, cybersecurity, and sales.
Methodology: CB Insights chooses the AI 100 based on a basket of metrics, some of them indirect or subjective, such as the “sentiment” of news coverage. It scores a company’s potential to succeed using a proprietary system based on funding, the overall health of its industry, and its “momentum.”
Why it matters: AI is a hot industry, but not yet a stable one.
We’re thinking: Don’t let the churn scare you. If you join a startup that doesn’t make it, as long as you keep learning, you’ll be in a better position to choose another that won’t repeat the same mistakes — or to start your own.