Eva Ho — Founder of Fika Ventures — All Raise #WomanCrushWednesday

While April was our Artificial Intelligence month, in May we will focus on Enterprise SaaS and the brilliant investors and operators who bring their expertise to the industry. Our first feature this month is Eva Ho, co-Founder of Fika Ventures, a LA based firm that primarily focuses on enterprise companies with a long term thesis on data. All Raise’s ‘Women Crush Wednesdays’ (#WCW) is a series where we highlight genius women who are funding or founding tech companies. Please come back to the All Raise Medium blog every Wednesday to find a new profile of an awe-inspiring female VC or founder.

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Eva Ho’s mission as an investor and citizen is to build enduring solutions to solve deep systemic problems.

Before founding Fika Ventures, Eva co-founded Susa Ventures and helped build two successful venture-backed businesses, Applied Semantics and Factual, companies that emphasized the big data in applications within advertising and location services. With a longer term thesis on data in mind, Eva and her partner TX Zhuo co-founded Fika Ventures, which invests with a focus on data and AI-enabled technologies.

While widespread AI adoption promises to transform industries and VC investment in AI has skyrocketed, according to Adobe’s Digital Trends report, only 15% of technology enterprises are using AI as of today, but even the type of usage ranges from basic analytics to data-driven decision making. Eva invests in companies that utilize AI in a way that will solve immense problems that affect a large part of society. Fika portfolio companies are AI-focused, but transcend sectors. The portfolio includes real estate startup Bowery, a provider of real estate appraisals and fintech startup Papaya, which lets you pay any bill instantly. Her portfolio also offers a spectrum of business models from WeeCare, a marketplace for childcare providers, to Elementary Robotics, a full-stack robotics company tackling machine learning for robot hardware.

Fika Ventures is based in LA, where the venture ecosystem is still developing despite successes like Snap, Dollar Shave Club and Blackline. Eva has been involved in the tech community in LA for many years, having spent time as a Mentor at MuckerLabs and as an Entrepreneur in Residence for the city of Los Angeles. Eva has also brought her passion for mission-driven data use to All Raise, where she leads the data team.

We caught up with All Raise founding member Eva Ho to hear what drives her passion for AI and LA.

S: Can you tell me more about the support you give your entrepreneurs?

E: We’re a team of practitioners that really understand the journey of a founder. We are here to go to battle with them on a daily basis as they try to achieve what they’re trying to accomplish. We’re not the most well-known brand, we’re not the biggest one, we’ve only been around for a couple of years, but we go to bat for our founders because we’ve been on the other side. We’re very empathetic and we actually do the work.

S: Why did you want to focus on AI specifically?

E: I was lucky to be part of a couple of companies that were fairly deep tech from the late 90s. The first was Applied Semantics and I was eventually on the founding team of a company called Factual. We were recognizing the importance of exchanging and moving data across systems quickly to help various machines and humans make decisions. I’ve had such a long thesis on data and the importance of data for future applications in all parts of our life and all parts of our world, so I think it was a very easy transition to say “Hey, now I’m going to look for things in industries that I think can really use it.”

S: We continue to see headlines about different companies using AI, what are the current applications?

E: I would say true AI is still very rare. Very few departments or strategic teams in large Fortune 1000 companies are really using AI in any sort of deep or meaningful way today although they talk about it a lot and it’s a topic in boardrooms. I would venture to say less than 5% of employees are really using it in a way that is actually affecting decision and outcomes.

S: Given that we haven’t seen really effective applications as of yet, how should we think about most effectively utilizing this technology?

E: I think there are many ways of thinking about AI. There are non-sexy applications of AI where we are using it to automate and augment basic functions, workflows and decision support systems. For example, mapping out select delivery routes, thinking about which customers to target and predicting sales across different customer segments.

S: So you mentioned that you were looking specifically at themes like healthcare, Fintech and real estate. Is there anything about those three industries that make AI applications particularly useful?

E: It’s things that are helping you take more control of your own health from a consumer perspective by mining all the data collected by and for you. It’s about helping doctors and hospital systems be more effective and productive, as well as make fewer mistakes. Most doctors are overworked, underpaid, and they’re working with extremely asymmetric and imperfect information because they are required to see more patients with inadequate patient interaction time. There is simply too much information for them to process holistically. There is great opportunity to make the whole system more efficient and accountable, to achieve higher quality care at a lower cost. It’s an area that I have been passionate about for awhile and now starting to make more bets. Even in the area of insurance. I think insurance will become more contextualized and personalized, and every person will get custom, tailored plans based on their lifestyle choices and behaviors.

S: What about real estate?

E: I think there are ways to use technology to bring more quality and transparency to the system, as well as a greater affordability. For the average person, a home is one of the biggest but infrequent purchase decisions that they make. I worked a lot on homelessness issues in LA and I just really think that real estate and housing are very broken, and many parts of the stack, from lending to escrow, need to be reinvented. Technology that can be applied to better even the playing field and make the whole experience more accessible and delightful for end users.

S: Should we be concerned that widespread automation could negatively affect employment?

E: The assertion is that big scale AI is automating many of our jobs and eliminating entire roles across all industries. But I believe that the next generation of automation and AI-enabled tech will create new, more enriching roles — and that humans and machines can coexist in harmony. Maybe I am too idealistic, but think the role of human judgment and intuition will remain critical, and now will be applied in a way that is more nourishing and additive.

S: I know you’ve spent time as an entrepreneur-in-residence in LA. What made you want to pursue that opportunity?

E: I was part of the second term — guinea pigs I guess you want to call it. They choose one man and one woman every year from various sectors to represent and build bridges between that sector and the city. The first couple of years were around the tech community, because tech people in most cities tend to be extremely cynical of city and county governments and honestly often antagonistic. They feel that the DNA and culture of the government are completely orthogonal from tech. LA had a focus around how to better market and showcase our city as a tech hub (which I thought was important), but when I met with the mayor’s team, I said, “I also really like data and working on public service stuff, so give me something like that. Allow me to work on something more challenging and meaningful to me.”

S: What issues did you end up focusing on?

E: I chose to work on homelessness, which I also touch in my role as a board member of the California Community Foundation (CCF), a foundation that supports LA county. CCF has been integral in driving several of the recent big propositions and ballot measures around homelessness in LA, resulting in billions of dollars generated toward solving this. I also wanted to wear the other hat and get into the city and really understand, “Are there things that we can do to understand the data around homelessness to help us better make decisions and inform policies?”. Only when I got in there did I understand how complex and multi-dimensional it is and why I didn’t even make that much of a dent at all. I spent most of my time learning and listening, and understanding the triggers and levers. I was pretty hard on myself and thinking I didn’t actually do much because it took so much time to really grok all that is involved in looking at big societal challenges like homelessness. There are so many constituents at play, there’s so many avenues of funding. I came away with a renewed appreciation for all the civil servants who work tirelessly to find solutions.