A Forerunner partner predicts what types of A.I. businesses will scale and succeed

·5 min read
Courtesy of Forerunner Ventures

In the middle of a banking crisis, OpenAI launched its latest and greatest A.I. system. And this week, Character.AI notched unicorn status. A.I. continues to be one of the hottest sectors of technology investing. Will it continue to be? Brian O’Malley, managing partner at the consumer-focused venture capital firm Forerunner, guest writes today's Term Sheet and weighs in.

It seems like everyone in the tech industry is marveling at the opportunity in A.I. Even though A.I. and machine learning have been implemented in tech for over a decade, the past year brought a level of practicality and a pace of innovation that has builders and investors paying close attention. And rightfully so: The A.I. technology has a magical quality to it, surprising even the most skeptical users, with the potential to reshape industries and jobs.

But this stage we’re at—one marked by effusive enthusiasm and a blistering pace of change—is also somewhat of a precarious one. The promise of the technology is undeniable, but the long-term, real-life utility is still unclear. Existing A.I. products, like Siri or Alexa, have failed to scale beyond simple use cases.

Humans are notoriously impatient with computers when they make a mistake. And, publicly traded A.I.-enhanced solutions, like StitchFix, which uses A.I. to make clothing recommendations, are valued very differently than private A.I. startups with nascent traction.

This stage we’re at isn’t dissimilar to when crypto rebranded as part of Web3 and gained enormous buzz in 2020. The promise of democratized finance was (and still could be) enormous, but somewhere along the way, the focus shifted from enduring applications to buzz fueled by coin speculation. The conversation shifted from early adopter utility to early adopter riches, with too many solutions searching for a problem. We’re seeing something similar now in A.I. with fewer questions around the factual quality of results versus the humanlike tone of the results.

As much as I find it fascinating to read that an A.I. chatbot would like to be alive (and in love), I hope the capital and talent moving into the ecosystem understands that mass adoption can only be achieved first through micro-utility.

To contextualize this, the evolution of mobile technology feels like a better analogy. Early mobile apps had a similar toylike quality where new capabilities sat at the forefront of the experience. The Lightsaber app was powered by the accelerometer; Bubbles took advantage of the touchscreen; and Shazam leveraged the microphone. But, once developers really honed in on the advances of GPS and the Camera, mobile startups started offering transformational services that had historically been out of reach for consumers. The camera was obviously essential to create the social products of today, but it also is critical for some serious operational use cases, like two-factor security and document scanning.

The accuracy of GPS chips ultimately gave way to some of the biggest businesses capitalizing on mobile as a platform: Uber, Doordash, Google Maps. What will be the equivalent in A.I. that helps this new technology go from a toy to an essential part of daily life?

When it comes to A.I., we at Forerunner—a venture capital firm focused on the consumer—believe the equivalent to GPS chips and quality cameras will be the computer’s ability to understand nuance in intent and emotion. As more consumers are turning to digital solutions for their daily needs, understanding these needs better will be a requirement. Just like Uber enabled everyone to have a private driver, something historically too expensive for most people, A.I. will be able to take human services (financial, travel, mental health, and coaching) and bring these to a broader population with accessible pricing. Some of the most interesting companies to us are the ones who are offering these services today at Uber Black-like prices but are uniquely positioned to ride the cost curve down to offer more UberX-like pricing. The open question is whether the service quality holds up in much more critical categories versus the quality of UberX, which has declined significantly over time in terms of reliability and accessibility of price.

Ultimately, the opportunity in A.I. lies in leveraging the technology to serve the customer versus being an "A.I. Company" as the end goal. The elephant in the room is that people don't want to talk with a computer when they need something done. Why? Because the magic of a computer understanding your intent doesn’t eclipse the frustration of it missing the point. That won't change anytime soon. We think some of the best A.I. companies will be the ones where the customers don’t even know A.I. is being leveraged. This is already happening in the crypto world, where real businesses are leveraging blockchain technology where needed…and, dare I say, not even talking about it!

Our industry has a tendency to indulge the highs and the lows, so it’s worth recognizing the less glamorous necessities: The builders who are working through the data quality issues, integration challenges, and the unique domain knowledge requirements to make A.I. experiences reliable and repeatable. These are the folks who will end up building enduring, strong businesses—ones where A.I. is a means to an end versus the end point itself.

Changes won’t come overnight, but sectors core to society’s quality of life, like transportation or travel, or essential to equality, like health care or our legal system, have the opportunity to dramatically change.

Technology has removed so much humanity out of experiences. It is somewhat ironic that A.I., and its ability to interpret people’s intent and underlying feelings, might be the answer to bringing some of it back.

Jackson Fordyce curated the deals section of today’s newsletter.

This story was originally featured on Fortune.com

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