Art by Charter · Photo by iStock melpomenem

“In a way, we’re all startups again,” declared A.Team founder and CEO Raphael Ouzan at the AI x Future of Work Summit the company hosted this past week. The acceleration of generative AI has forced even the most established companies to experiment and rapidly transform their existing business models. “The homepage on Google generates hundreds of billions of dollars—you don’t want to mess with that,” said Ouzan. “And yet they are messing with that, and they’re putting a component of generative AI right on that homepage that literally says, ‘This is experimental. Watch out for the results.’”

Embracing a startup mindset around AI is one of several pieces of advice for organizations that we heard at two separate AI events this week. At both A.Team’s summit and the Evident AI Symposium, we listened to insights from leaders—including a chief people officer at an automotive tech supplier and multiple data and analytic executives at banks—about how AI is changing their ways of doing business.

Here are some takeaways from those events:

  • Continually remind employees to apply their judgment over the long term. Vahe Andonians, chief technology officer and chief product officer of Cognaize, said that we need humans to apply their judgment to AI outputs even when we no longer need to be checking its facts. “I’m going to steal from Nietzsche,” he said, “It should be humans because we are the only ones that can suffer. AI is not going to suffer…so the judgment layer should be us.” George Lee, co-head of the office of applied innovation at Goldman Sachs, added that one thing his team has been focused on is how to encourage employees to keep a sharp eye, even when the AI system is performing well: “After the 10th experience of it looking just great, are you going to pay attention?” (A recent study on BCG consultants, covered by Charter, illustrated the danger of employees ‘switching off their brains’ when working with impressive AI systems.)
  • Just do something. That was the advice of Jeff McMillan, head of analytics, data, and innovation at Morgan Stanley Wealth Management, who led the effort to create a tool, built on OpenAI’s GPT-4, for the firm’s wealth advisors. “We went from driving horse-drawn carriages around the streets of New York City and then someone gave me a BMW,” he said. McMillan noted that prioritizing speed led to a less-than-smooth rollout—”We piloted for nine months. We had…20,000 pieces of feedback because the day we went live with this thing, it was not producing high quality”—but that the experience enabled his team to learn a lot, quickly, about how to move forward. His advice is to “get the smartest people you have in the room, engage with these tools in a controlled playground, and invent.” What you shouldn’t do, said McMillan, is spend too much time deciding which model you’re going to go with. “Honestly, they’re all BMWs.”

Charter Pro members can read here more insights from these two events, including predictions from bank leaders about what organizations should prioritize in their AI adoption. Sign up for a discounted Charter Pro membership here to access this coverage.

Correction: This story has been updated to reflect Lee’s title. He is the co-head of the office of applied innovation at Goldman Sachs, not the co-head of applied innovation.

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