After an exciting boom in the development of AI industries, the field has gradually entered the disillusionment phase of the hype cycle. Correspondingly, as year 2019 has just passed, many AI startups went down with it (as a matter of fact, you may find some of them very familiar, such as Anki, the company behind the elfish little robot, Cozmo.
The following is a list of AI-related startups who have closed down in 2019. We'll also mention some of our advices to an AI startup in the last part of this article, so be sure to stay with us till the end.
The Death List
Roadstar.ai (Died in Series A financing)
Founded in: 2017
Raised Funds: $ 128 M USD
Main Product: Autonomous driving technology
Major Reason for Its Downfall: Internal conflict among the 3 founders.
Jibo (Died in Series B financing)
Founded in: 2012
Raised Funds: $ 72.7 M USD
Main Product: Smart family robot - Jibo
Major Reason for Its Downfall: Lose the competition with other smart assistants such as Alexa.
Aria Insights (Died in Series B financing)
Founded in: 2008
Raised Funds: $ 39 M USD
Main Product: Drone
Major Reason for Its Downfall: Capital chain rupture
Seven Dreamers (Died in Series B financing)
Founded in: 2014
Raised Funds: $ 95 M USD
Main Product: Automatic clothes folding robot - Laundroid
Major Reason for Its Downfall: Capital chain rupture
Anki (Died in Series D financing)
Founded in: 2010
Raised Funds: $ 182 M USD
Main Product: AI robot toy - Cozmo
Major Reason for Its Downfall: Capital chain rupture
Drive.ai (Died in Series B financing)
Founded in: 2010
Raised Funds: $ 77 M USD
Main Product: Autonomous driving technology
Major Reason for Its Downfall: The executive was too greedy
Reach Robotics (Died in Series A financing)
Founded in: 2013
Raised Funds: $ 7.8 M USD
Main Product: The gaming robot with AR feature - MekaMon
Major Reason for Its Downfall: Lose the competition with other gaming robots
So, What Do We Learn from Them?
As one can see, the major reasons for these startups to fail are three: lack of funds, competitions in the market, and internal problems relevant to the members of the team or management.
The first reason usually results from the fact that most AI startups are focusing on making technical improvement instead of reasonable product (by the word “reasonable” I mean the products that people will continue to buy so that you can build a sustainable business model around them). And it’s exactly because of that, these startups are usually not competitive enough in the market. As for the third, since the major concern of these startups is in R&D, management, marketing and product design become their weak links.
All the above three reasons can actually be summarized into one single message: Making technical breakthrough in AI technology is no longer the point for a company or startup. The point now is to focus on making AI a successful product. Thus, instead of technical people, the AI startups today actually require more expertise from the fields of product, marketing and management.
To sum up, for a startup (especially those who does not have a lot of funds), technical innovation should not be your top priority since it burns money fast, and you will only have a little chance to compete against big tech companies, such as Amazon and Google, who are rich in both money and data. Instead, one should put their creativity and innovation power in answering the following three questions: (1) How and where to apply the current AI techniques? (2) How is our product different from others’? And (3) How do we persuade potential customers to make a purchase? If you and your team can find a sustainable niche market for your products and at the same time knowing how to sell them, then your startup will have a much better chance to survive!
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