- Emergence Capital’s first investment was in a pre-IPO Salesforce, and the firm has made smart bets since on companies like Zoom and Gusto. Now Jake Saper, partner at Emergence, is ready to make a new bet on the future of cloud software.
- Saper thinks the next set of cloud software companies will be what he calls “coaching networks” — basically software that uses artificial intelligence to gather information on how you perform your daily tasks and provide suggestions for improvement and efficiency.
- The key is that AI will be used to augment, rather than automate, the tasks that the software is helping users do, he said.
- “It’s a very different version or view of the way that AI will manifest in the enterprise than what is typically happening today,” Saper told Business Insider.
- Saper said that while he thinks some tasks will be automated by software, there’s a huge opportunity to use AI to help retrain workers and open up more job possibilities.
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Jake Saper’s first investment when he joined Emergence Capital was in Zoom, the video conferencing startup that rose to prominence this year when it went public in April. Zoom’s IPO valued the company at $9.2 billion — roughly 9 times its last private valuation.
But this wasn’t the first success story for Emergence. In fact, the firm’s first investment ever was a secondary round in Salesforce, ahead of its IPO. Since then, the firm has continually invested in a number of successful cloud-computing companies tackling the enterprise space, including Gusto, Box, and SucccessFactors.
Now, Saper and Emergence Capital at large are staking their bets that the next big thing in cloud software will be something he calls “coaching networks” — software that gathers data from your daily tasks and offers back suggestions and guidance to help you work more efficiently.
Saper said phase one of cloud was moving on premise software to the cloud, as we saw with Salesforce or Box. Phase two of cloud, which is happening now, is a trend towards industry-specific cloud software, which we’ve seen with the rise of apps like Emergence-backed Veeva, making software for the pharmaceutical industry.
Phase three, he said, will be these “coaching networks,” built using AI — not to automate, as we see in most modern uses of AI, but to assist.
“It’s a very different version or view of the way that AI will manifest in the enterprise than what is typically happening today,” Saper told Business Insider.
He gives the example of a customer service representative at a call center. While on a call, software running in the background could collect data about the customer and use it to guide the representative as they move to assist. That data would also be used to help other employees using the same software for the same tasks, he explained.
This is exactly the sort of thing that one of his firm’s portfolio companies, called Guru, is doing. “The idea is that it’s capturing all of those pieces of knowledge and then it’s surfacing them where the worker works. And so a really important element to this that you still layer on top of the current customer interaction,” Saper said.
The key is that artificial intelligence used to augment each individual task, rather than full-on automation. Saper thinks this kind of augmentation is the way in which AI will manifest itself in the software space going forward.
“Low level tasks, what we call static tasks, where the data you need to effectively complete the task is relatively static and bounded. We think those tasks will be automated,” Saper said. “The idea that we’re more excited about is all of the, what we call dynamic tasks that exist in the enterprise, these would be basically human to human tasks.”
AI will still change workers’ lives
Of course, that’s easy to say, but with AI comes the potential for job loss.
According to a report by the Brookings Institution earlier this year, roughly 36 million American jobs have a “high exposure” risk from automation, meaning that 70% of their job functions could be performed by machines. Some of the most at risk jobs are focused on manual labor tasks such as cooks, waiters, and clerical office workers.
Saper thinks that some of those kinds of jobs will go away, but that AI can also be used to retrain and reposition workers for the jobs that will remain.
“If I’ve got technology that I know can help augment those workers and get them much more quickly up the learning curve, then I can broaden the pool that I’m hiring from, which gives folks who may not have done the job before in the knowledge economy, the opportunity to do this knowledge economy job for the first time because they have a real time coach,” Saper said.
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