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AI Disruption: What VCs Are Betting On

This article is more than 2 years old.

According to data from PitchBook, the funding for AI deals has continued its furious pace. In the latest quarter, the amount invested came to a record $31.6 billion. Note that there were 11 deals the closed more than $500 million.

Granted, plenty of these startups will fade away or even go bust. But of course, some will ultimately disrupt industries and change the landscape of the global economy.

“To be disrupted, you have to believe the AI is going to make 10x better recommendations than what’s available today,” said Eric Vishria, who is a General Partner at Benchmark. “I think that is likely to happen in really complex, high dimensional spaces, where there are so many intermingled factors at play that finding correlations via standard analytical techniques is really difficult.”

So then what are some of the industries that are vulnerable to AI disruption? Well, let’s see where some of the top VCs are investing today:

Software Development: There have been advances in DevOps and IDEs. Yet software development remains labor intensive. And it does not help that its extremely difficult to recruit qualified developers.

But AI can make a big difference. “Advancements in state-of-the-art natural language processing algorithms could revolutionize software development, initially by significantly reducing the ‘boilerplate’ code that software developers write today and in the long-run by writing entire applications with little assistance from humans,” said Nnamdi Iregbulem, who is a Partner at Lightspeed Venture Partners.

Consider the use of GPT-3, which is a neural network that trains models to create content. “Products like GitHub Copilot, which are also based on GPT-3, will also disrupt software development,” said Jai Das, who is the President and Partner at Sapphire Ventures.

Cybersecurity: This is one of the biggest software markets. But the technologies really need retooling. After all, there continues to be more and more breaches and hacks. 

“Cybersecurity is likely to turn into an AI-vs-AI game very soon,” said Deepak Jeevankumar, who is a Managing Director at Dell Technologies Capital. “Sophisticated attackers are already using AI and bots to get over defenses.”

Construction: This is a massive industry and will continue to grow, as the global population continues to increase. Yet construction has seen relatively small amounts of IT investment. But AI could be a game changer.

“An incremental 1% increase in efficiency can mean millions of dollars in cost savings,” said Shawn Carolan, who is a Managing Partner at Menlo Ventures. “There are many companies, like Openspace.ai, doing transformative work using AI in the construction space. Openspace leverages AI and machine vision to essentially become a photographic memory for job sites. It automatically uploads and stitches together images of a job site so that customers can do a virtual walk-through and monitor the project at any time.”

Talent Management: HR has generally lagged with innovation. The fact is that many of the processes are manual and inefficient.

But AI can certainly be a solution. In fact, AI startups like Eightfold.ai have been able to post substantial growth in the HR category. In June, the company announced funding of $220 million, which was led by the SoftBank Vision Fund 2. 

“Every single company is talking about talent as a key priority, and the companies that embrace AI to find better candidates faster, cheaper, at scale, they have a true competitive advantage,” said Kirthiga Reddy, who is a Partner at SoftBank. “Understanding how to use AI to amplify the interactions in the talent lifecycle is a differentiator and advantage for these businesses."

Drug Discovery:  The development of the Covid-19 vaccines—from companies like Pfizer, Moderna and BioNTech—has highlighted the power of innovation in the healthcare industry. But despite this, there is still much be done. The fact is that drug development is costly and time-consuming. 

“It's becoming impossible to process these large datasets without using the latest AI/ML technologies,” said Dusan Perovic, who is a partner at Two Sigma Ventures. “Companies that are early adopters of these data science tools and thereby are able to analyze larger datasets are going to make faster progress than companies that rely on older data analytics tools.”

Tom (@ttaulli) is an advisor/board member to startups and the author of Artificial Intelligence Basics: A Non-Technical Introduction, The Robotic Process Automation Handbook: A Guide to Implementing RPA Systems and Implementing AI Systems: Transform Your Business in 6 Steps. He also has developed various online courses, such as for the COBOL.

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