From left: Vivek Ladsariya, managing director at Pioneer Square Labs; Heather Redman, co-founder and managing partner at Flying Fish; Anoop Gupta, CEO at SeekOut; and Vikram Chalana, CEO at Pictory. (GeekWire Photo / Taylor Soper)

AI startups accounted for 40% of total venture funding in May. So it may seem strategic for startups to include AI as part of their pitches to investors.

But founders and CEOs should tread carefully when talking about their company’s use of the trendy tech, according to two Seattle-area venture capitalists who spoke at the PAN-IIT Seattle 2024 Conference event in Bellevue, Wash., earlier this month.

Over-branding in AI “shows you as an unserious company and unserious people,” said Vivek Ladsariya, who recently joined Pioneer Square Labs as a managing director.

“Serious investors — and more importantly serious customers — will really see through that,” he said. “That’s not the brand you want to build.”

AI has “sort of become table stakes” and should be part of a company’s strategy, but not overstating its role is crucial, said Heather Redman, co-founder and managing partner at Flying Fish.

“You can really lose a lot of credibility,” she said.

Vikram Chalana, CEO of Seattle startup, joked that he went against the advice shared by the investors since his 4-year-old company literally has AI in its domain name.

AI is core to Pictory’s product, which automates video creation.

“At the end of the day, it has to be about a customer problem,” Chalana said.

Ladsariya echoed that sentiment.

“If you’re speaking to customers, it’s really important to talk about what you can do, rather than a general technology,” he said.

AI has been a core thesis at Flying Fish since it launched eight years ago. Redman said the firm specifically targets founders and teams with AI backgrounds.

“We are generally looking for a PhD on the team,” she said. “It’s not a must-have, but certainly a nice-to-have.”

But Anoop Gupta, CEO of SeekOut, said companies don’t necessarily need “AI experts” to take advantage of generative AI.

“If you’re building AI infrastructure, then having a lot of deep experience is necessary,” he said. “But my sense is that a smart engineer, a computer scientist — they can learn a lot about [AI]. Their sense of conceptualization and problem definition and how to experiment can take you a long way. You don’t need a machine learning specialist.”

Chalana agreed, noting that he’s seen people with advanced AI experience and education struggle with adopting generative AI. He said the best generative AI engineer on his team is a 26-year-old software developer.

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