The Changing Venture Capital Investment Climate For AI

Original article was published by on AI Magazine


The venture capital (VC) world often follows the general trends of the markets. When social media is the in-thing, investors will flock to all manner of social media startups. The same goes for any area of investing from mobile apps to live-work-play co-working places and everything in between. So too is the investor perspective on artificial intelligence. When it became clear less than a decade ago that AI was the latest, hottest place to build companies that could grow from tiny startups to huge public market exits of acquisitions, the VC community got all in. 

In the past few years, it seemed that just the mere mention of AI in your product was attractive enough to raise substantial funding rounds. As a result, startups of all sorts played into this trend adding AI and ML jargon and buzzwords into business plans or marketing material and raising more money than ever. Yet, are these companies actually building solutions that the market is looking for and pusing AI forward, or are they simply “AI-washing” their otherwise unintelligent offerings?

Waves of Investment in AI

We’ve been here before. In fact, this latest wave of AI is the third major wave of AI research, development, and investment, with the first two waves coming roaring in and crashing down in what became known as the AI Winters. Much has been talked about whether this latest AI summer will be permanently here to stay, but we can look at the investor climate as an early warning to see if attention, interest, and resources continue to be strong for AI or we’re already starting to see signs of an impending chill in the market.

During the first wave of AI starting in the 1950’s initial funding was largely supplied by governments. Governments funded R&D efforts around artificial intelligence but as governments lost interest funding dried up and AI projects basically did as well. During the second wave of AI in the 1980’s the market also saw the rise of venture capitalism. This opened up entire new avenues for funding resulting in increased research, projects, and more diverse projects.

This current third wave of AI is being pushed forward by different factors. In addition to government and corporate investment, big data and computing power leveraged by the huge cloud-based technology combined with the emergence of data-hungry deep learning neural network algorithms are powering the latest renaissance in AI. Startups in the AI space are raising significant funds from VC firms all over the world. 

However, things are a bit different with AI. Whereas in the past Silicon Valley was by far the overwhelming investor location of choice for technology-focused startups, the AI market is decidedly more global. Chinese-based firms have raised eye-watering sums of money and “unicorn” startups are being founded everywhere from Bucharest to Bangalore. While Silicon Valley has still not been unseated as the top investor location, other locations inside the US as well as overseas are definitely posing significant challenges to that leadership. 

Venture funding in AI companies had reached a mind-blowing $61 billion from 2010 through the first quarter of 2020. The majority of these investment dollars are to companies based in the USA or China. Is this investment sustainable? Some would say not. Venture capitalists are mostly driven by finding that unicorn needle in the startup haystack, driving outsized returns to their investors that offset the expected losses in the rest of their investments. As such, the only way so much money would be pumped into this industry is if the market believes that AI is a “transformational” technology that will revolutionize entire industries and markets, in much the same way that mobile, social, cloud, and other technologie have similarly disrupted their markets. Disruption means change. Change means opportunity. And where there’s opportunity, there’s venture capital.

Perspectives from a Venture Capitalist

VC firms still seem committed to the long-haul in their AI-focused investing. On an AI Today podcast, John Frankel of ffVC shared his insights into why like cloud and mobile, AI is here to stay. John founded ff Venture Capital (ffVC) with partner Alex Katz in 2008.  The primary interest of the company are emerging technology companies that focus on artificial intelligence, drones, robotics, and cybersecurity.

John Frankel, ffVC

John Frankel, ffVC

One cornerstone to their strategy is a partnership with New York University (NYU), with an incubator set up to assist startup companies to accelerate their AI efforts. Part of the reason why New York has had such a strength in AI companies is because of its unique combination of financial strength, research and academic strength, and the location of major corporations that can apply technology. AI is proving its value in many industries and as such being in close proximity to hubs of finance, advertising, insurance, and other markets provides a larger scope of immediate access to markets than possible even in Silicon Valley.

Indeed, VC firms are starting to move beyond the sci-fi aspects of AI to the more mundane applications in industry. Indeed, VCs are investing less in AI “concept” companies and more in applying machine learning and AI to transform existing markets from retail to real estate. According to John Frankel, the big shift he is seeing is the vertical application of AI in which startups are taking technologies that already exist such as image or voice recognition and building industry- and enterprise-specific applications. 

John offers a bit of advice when it comes to investors or companies jumping into the AI waves. He says that it’s a bit late at this point to invest in the underlying, infrastructural technology unless there’s a major revolution in the fundamental technology of that company. The large incumbents have significant resources that they are applying to bear in the markets. He points out that AI should be seen as a way to improve or build upon what we had rather than a replacement strategy for things that are not working. While there will be a major shift in some areas such as the type of workers that are needed or products that are being sold, ultimately the technology is going to be used to enrich the experiences of day-to-day customers and citizens and not necessarily just line the pockets of a few well-timed and well-placed investors.