Investment in artificial intelligence startups is on a tear as venture capitalists and corporate investors scramble to stake out a leadership position in what could be the driving trend in technology for decades to come.
The financial interest in AI, machine learning and related technologies is hardly new. CB Insights has tracked some $18.4 billion invested in 2,541 AI-related startups since 2012.
But the trend is only accelerating. In the latest MoneyTree report from PricewaterhouseCoopers LLP and CB Insights, which showed otherwise mostly stagnant startup funding, AI and machine learning companies shined, reaching an eight-quarter high of $820 million invested in 90 companies.
A flurry of significant investments in a number of AI-related companies this past week underscored the point. On Wednesday alone, for instance, AI-powered analytics software provider CognitiveScale Inc. raised a $15 million round, voice AI startup Snips raised $13 million and, to top it off, machine learning consultancy Element AI Inc. got an unusually large $102 million early-stage investment just eight months after the company was launched. Then on Thursday and Friday, two other AI-powered companies, Conviva Inc. and Codota Dot Com Ltd., announced fundings too.
“You get these spikes around waves of technology, and people are realizing that AI and machine learning are one of those cresting technologies,” said Matt Murphy, a managing director at the venture capital firm Menlo Ventures. “The science has moved far enough along that it’s now ready for practitioner mode.”
‘The new electricity’ In a sense, the term AI has become almost meaningless by now, because nearly all software, cloud and Internet services and apps depend on AI in some way to make their products smarter. “AI is the new electricity,” said former Baidu Inc. Chief Scientist and machine learning guru Andrew Ng.
Some of the pile-on is opportunistic, too. Companies have noticed that the terms themselves are getting more attention in the press, so suddenly there are a lot of “AI-powered” companies. Five years ago, companies that did business intelligence relabeled themselves as “big data” companies, and now big data companies are refashioning themselves as AI companies. “VCs invest in packs,” said Stuart Frankel, chief executive of Narrative Science Inc., a seven-year-old company that raised $11 million in April for its natural language generation services. “There are activities being recharacterized to take advantage of the market opportunity.”
In turn, the investment amounts are getting bigger as competition for deals and a continuing scarcity of talent extracts a premium. That’s not necessarily a good thing, because many of the companies have proven neither the technology nor a specific market opportunity. Only in a few years, when those companies look for later-stage financing, will it be apparent whether they have a viable business.
Still, there’s no denying that direct investment in AI companies continues to accelerate. It’s all driven in turn by the hunger by consumers for smarter devices and apps and by enterprises looking to upgrade their internal operations and create new opportunities to extract value from their data. Although the advances in AI and machine learning are most obvious in services such as image recognition in photo and social media apps and in smartphone voice recognition, enterprises are fully on board too.
According to Gartner Inc., about 40 percent of new enterprise applications implemented by information technology service providers will include AI technologies by 2021. For its part, International Data Corp. expects global spending on “cognitive/AI systems” to rise from $8 billion in last year to $46 billion in 2020.
In particular, said Menlo’s Murphy, there’s a huge opportunity in making enterprise applications and their users smarter. His firm has invested, for instance, in Veriflow Systems Inc., which uses machine learning to map out networks to track performance and find vulnerabilities more easily, and Clarifai, which raised $30 million in October for its technology to help software and app developers tag visual images more easily.
Cascading benefits These investments could have cascading benefits on the rest of the technology industry as well, particularly back-office enterprise tech. “With all this data, there’s a need for a new data platform,” Jim McHugh, a vice president and general manager at Nvidia Corp., said this week at the DataWorks Summit in San Jose, California, a conference dedicated to technologies for managing the huge amounts of data needed for machine learning. Just about every other industry, from advertising to manufacturing to financial services, stands to benefit from all this investment as well, as they leverage these new technologies to improve everything from targeting ads to ferreting out fraud or finding the most lucrative new customers.
It’s not just venture capitalists putting up big bucks for AI companies. Companies are investing heavily too. Google Inc., which CEO Sundar Pichai has been calling an “AI-first” company since at least last year, is launching an AI-focused venture investing operation, according to one report last month. On Wednesday, Intel Corp. announced it had just invested in three AI-related companies, and they’re far from the first for the giant chip maker, which has been redesigning some of its iconic processors for machine learning. For its part, Microsoft Corp. announced last week that it also was an investor in both Element AI and CognitiveScale, following two others in May, Bonsai AI Inc. and Agolo Inc.
The entry of tech giants into AI-related startup investing worries some observers, since they’ve already acquired so much AI talent either through acquisitions or hiring them with their seemingly bottomless coffers of cash. “There’s a huge talent shortage,” said Murphy. But he still thinks the opportunity is so immense across so many industries that “there’s no way the big tech companies can dominate the field.”
Not surprisingly, investment in AI has gone global as well, particularly in China. Indeed, it’s a sign of how fast AI investment has accelerated that the U.S. government has taken notice. Now the U.S. is looking at restricting the ability of Chinese companies to invest in domestic technologies such as AI and machine learning.
Whether or not that works, investment in AI, machine learning and data science is likely to keep rising for the next few years. “We are really at the dawn of a renaissance of data science,” said Rob Thomas, vice president and general manager of IBM Analytics. “It will do for 21st century what Industrial Revolution did for the 20th century.” That’s an opportunity investors can’t resist.