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Have AI Investments Reached A Tipping Point?聽

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Investment in artificial intelligence startups hit a record high of $59 billion in 2021, up from $28 billion in 2020, according to data.

Venture investment in AI startups will only continue to rise in the next five years. That鈥檚 because AI has finally reached a tipping point where it is powerful and affordable enough to make a real economic impact on diverse industries.

AI is a broad category, but generally encompasses all 鈥渋ntelligent鈥 software that can learn from itself in some capacity. This can include machine-learning platforms and the software used by robots, and self-driving vehicles to interpret the environments around them.

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For decades, AI has been developed and used by computer scientists to train all kinds of autonomous systems. But what鈥檚 changed today is that AI is no longer stuck in the lab; it鈥檚 the backbone of fast-growing startups with the potential to become multibillion-dollar businesses.

Today, companies in industries as diverse as finance, retail, health care, food production, manufacturing, logistics and transportation are deploying AI to improve everyday business processes, automate their workflows and, sometimes, to introduce autonomous robots.

Kevin Dunlap of Calibrate Ventures
Kevin Dunlap of Calibrate Ventures

I estimate that at least $500 billion will be spent in the next five years on AI implementation worldwide. Just one company, chicken producer , announced late last year it will invest to automate its plants over the next three years. While AI has been around in the lab for decades, today it is delivering real economic value for customers, creating immense opportunity for AI startups.

So what types of AI startups stand to gain the most investment in the years to come? As an investor who has backed AI software companies such as , , 听补苍诲 , as well as AI-powered robotics companies such as , 听补苍诲 , I see three especially high-growth areas.

The first is synthetic data, which is essentially AI software that can create data sets used to build ML models. Synthetic data is used to train computers to understand and respond to millions or billions of situations. It could be used to train self-driving cars, financial software to stop potential fraud, or health care systems to spot trends without compromising patient confidentiality, for example.

The second is AI software that powers autonomous mobile robots. Coupled with computer vision, LIDAR and sensors, AI software is the robot 鈥渂rain.鈥

AI startups are retrofitting all types of vehicles and devices with software 鈥渂rains鈥 to turn them into autonomous robots that can understand the world around them and make human-like decisions. , recently acquired by , does this for tractors, while . retrofits floor-cleaning machines and delivery carts, and 鈥 software turns earth-moving equipment into autonomous robots.

The third is AI software to automate manufacturing, logistics and warehousing. These interrelated sectors have seen tremendous pressure in the last two years due to the pandemic鈥攁 surge in e-commerce, labor shortages, supply-chain issues and more. Already having embraced automation to some degree, these industries are now the leading adopters of AI, looking to add 鈥渕achine intelligence鈥 to existing assembly lines and warehouse and logistics facilities. They are also deploying AI software to do demand forecasting, improve shipping, reduce waste and other crucial functions.

As an AI investor, I鈥檝e never been more excited to invest in this space and expect AI software to be commonplace in every industry within the next five to 10 years.


is co-founder and managing partner at . Prior to co-founding Calibrate Ventures, Dunlap was a managing director at , where he backed companies including , and . He currently sits on the boards of , and .听

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