Large companies are lagging on artificial intelligence and often spend heavily without a clear plan, futurist Amy Webb said Thursday at the Fortune AIQ Summit in a conversation with Fortune’s AI editor Jeremy Kahn.
“Let’s be fair, Fortune 500 companies are pretty late to the party on this,” said Webb, founder and CEO of the consulting firm Future Today Strategy Group. “Artificial intelligence didn’t just show up a couple of years ago.”
Webb said she sees “enormous amounts of capital” poured into pilots “with no strategy ahead of them.” She described projects that become orphaned after disputes with security teams, and executives who outsource building proprietary technology and then find themselves stuck. Frustrated employees, she added, sometimes build their own tools.
Webb compared many executives’ reliance on AI to driving a New York City taxi and being handed a phone to type in an address. After roughly two years of that pattern, she said, drivers are so dependent on navigation tools that there’s “a certain amount of learned helplessness,” which she sees mirrored in corporate leaders.
Her advice to companies is not to try to be “AI native” but to prioritize “being flexible” and to build mechanisms to enable that. She said she has not yet seen large companies implement such mechanisms, even though many CEOs are actively trying to understand AI.
Why gains don’t add up
Webb argued that individual productivity gains often don’t scale across organizations because firms define return on investment too narrowly, typically focusing on the bottom line. She contrasted that with Runway, an AI video company whose strategy she views as a clear vision that its tools help advance.
She recounted a story about a friend at a giant company who bypassed a chief technology officer to get a secure sandbox approved by going directly to the CEO, building an instance, accessing a supercomputer and assembling a team. Webb said the group plans to spend a couple hundred million dollars on AI tokens. She attributed such outcomes to a lack of “strong leadership and planning,” and to companies operating from “fear and FOMO.”
Runway’s counterpoint
Michelle Kwon, Runway’s chief operating officer, described a different approach. Runway, founded about nine years ago by three NYU graduates, uses AI “essentially every part of what we do,” and its entire staff writes code, she said.
Since earlier this year, employees have built about 215 apps for an internal app store, including contributions from teams outside engineering, and the company’s newest product emerged from that process. Runway announced a pilot for an autonomous ad agent the day before the panel. One employee built it in “a handful of weeks,” Kwon said, adding it raised ad output by more than 1,000% from a very small base and is now being released publicly.
Kwon said Runway still purchases systems that aren’t core to its business, such as payments or HR compliance software.
On productivity, Kwon said: “Just because you are using AI, that is not a proxy for your productivity or you doing a good job at work.” She argued AI should be a core part of how people work, provided it is “responsible” and “doesn’t create work for other people.”
“It’s not helpful if I receive a 100-slide deck,” Kwon said. “What is someone asking me to do with that?” She made the same point about chatbot output, which Runway sometimes receives: people “just copy and paste the output without having thought about: how do I synthesize this?” That, she said, “isn’t a productive use of anyone’s time.”
Peloton’s chief technology officer, Francis Shanahan, relayed a comment from the audience about the reverse problem: employees are “inundated now because they can literally build anything,” and he is seeing “burnout to be more and more of an issue.” Kwon said Runway intentionally “celebrates the wins” and recognizes employees. The company gives the whole staff the same day off not tied to a holiday to avoid tracking disparities in who takes time off. When Kahn joked that AI agents could keep working on those days, Kwon replied, “They can work tirelessly.”
Risk and liability
Matt Maher, founder of M7 Innovations and a consortium partner with the MIT Media Lab, asked who is liable when an AI agent breaches a contract or causes harm. Webb shared a personal story about a coding project she once deployed that spammed 1,000 people after a loop error put it in a live environment. She said such failures are ordinary human errors, not evidence of AI “waking up,” and urged executives to “stop anthropomorphizing” AI.
Webb added that security and risk officers should ask “tell me more” before saying no, and that leaders should give them some leeway. She warned that a wave of connected devices—glasses and charms that listen—will arrive over the next 18 months with little planning.
Asked about boards using AI, Webb said her firm has used it for a decade, but it is useless if directors don’t understand the data. She compared it to her own cycling sensors: “You can’t disassociate from what’s happening,” she said, “or you are liable.”
For this story, Fortune journalists used generative AI as a research tool. An editor verified the accuracy of the information before publishing.
This story was originally featured on Fortune.com.
Source: fortune.com
