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Jocelyn Goldfein (LinkedIn, Twitter) is a true IT Visionary. Having worked at VMware and Facebook in the early days of both, and now as Managing Director at Zetta Venture Partners, Jocelyn has played a key role in the development of technology as we know it.
In part two of their interview, Jocelyn and Ian discuss whether A.I. is an industry in and of itself, what companies are worth investing in, how collaboration works between enterprises and start-ups, and much more.
Best Advice for a first-time C-Level Exec: “You have to learn how to manage up and manage down differently. And you have to learn how to communicate differently….Have a mentor in your back pocket who you can go to. You can wait to learn all these lessons through trial and error or through the school of hard knocks, but if you can have a buddy who is a couple of years ahead of you and can save you some of those mistakes, it’s a superpower.”
Key Takeaways:
A.I. as an industry — (1:15 & 5:50)
Jocelyn does not view A.I. as an industry. Rather, she believes it is a technology and a platform that can be used in every industry. In the same way that the internet can be considered a vertical — insofar as it does not describe the business a company is in and because there is no one company that provides the internet — A.I. can also be considered a vertical.
“Name a sector and I think with the adoption of A.I. — just like the adoption of technology, period — those in it will be able to be more efficient, more effective and more successful.”
“I’m not a fan of companies that are just selling A.I. frameworks or A.I. libraries and technologies.”
“For the most part, A.I. is not a product. And even the platforms that help you build A.I. solutions are going to frankly be free in open source or through the big cloud platform providers.”
“There is no one company that provides the internet. The internet is a global standard where a few service-oriented companies and products enable it to exist for everyone. I think A.I. will be similar.”
“A.I. for the sake of A.I. is not a solution. That’s a technology looking for a problem.”
What is getting funding right now? — (2:38 & 9:30)
Products and companies using A.I. to make things easier and cheaper are setting the pace right now in terms of funding. Improving IoT security is also a hot topic and industry. This is yet another area where A.I. is proving useful to some of the top CIOs and CISOs in the country.
What’s exciting now is how to transform data centers to perform more efficiently. There are immense gains to be had through using A.I. to search through systems and find the optimal way to use resources and achieve maximum output for minimum cost.
Healthcare also offers tremendous opportunities for A.I. but it needs to be approached with caution. There is still a lot of conservative thinking among those in the healthcare space who are not yet ready to adopt the risk of A.I. There are technologies out there using A.I. to make an impact and save lives, but it is a slower rollout because of how much is at risk in the healthcare field.
“What every CISO will tell you is that they don’t have enough people in their security operations team to respond to every threat. So how do we intelligently prioritize? That’s an area where A.I. can augment human activity.”
“The bread and butter of every CIO is trying to achieve as much quality at as low a cost as possible.”
“We have to think about not only what problems is the technology ready to solve, but also which markets are ready to adopt the technology.”
What does A.I. collaboration look like and how do you know when to build or buy? — (17:15)
Buying from the same vendor is a great way to share data in an anonymized way. The best example is Tractable, which uses dozens of customers to pool data and provide a more accurate service.
All CIOs should be thinking of A.I. as part of their mandate and that they need to adopt it. In terms of building or buying, it has to be a mixture of both, just like all other IT. There has to be in-house talent who can decide what you need, whether you have the resources and data to build or if it would be better to buy.
Working with start-ups has to be a bit different and there are different rules to play by. But there can also be a more intimate relationship that evolves where an enterprise works with a start-up to personalize an innovative solution.
“There’s a way to pool data to build a solution and solve a problem for an entire industry. That’s why I love the vertical applications of A.I. because that’s how you build a critical mass of data for a particular domain.”
“You should be investing in a strong team of data scientists regardless because you’re going to be able to apply them to a lot of problems.”
“You have to build up a core competency in A.I. Whether you end up building or buying, you need a core team to help you do both.”
“Innovation happens at the intersection of an innovative seller and an innovative buyer.”
Best practices for finding start-up partners — (32:25)
The people you want to meet are the people with problems to solve, that have a mandate and a budget to solve those problems. Partnerships have to start from a real business need. That’s what causes the alignment that allows you to streamline a process or spend money to take a risk. What motivates people to take a risk is if it’s even riskier to do nothing When that happens, you can find start-up partners to work with to innovate and solve problems.
“Where start-up meets with success is where they meet a buyer who is in terrible pain and who has big problems to solve.”
“Ultimately what powers innovation is risk-taking because if the answer were obvious it, by definition, would not be innovative.”
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