At the recent Financial Times Future of Asset Management conference, industry leaders came together for a deep-dive session entitled “From AI Pilots to Secure Scale: Rebuilding Operations Around Client Value,” featuring:
- Gary Hoberman (Founder & CEO, Unqork)
- Jon Couture (Financial Services Operations Executive, Vanguard)
- Per Roman (Chairman & Managing Partner, Bullhound Capital)
- Kelly Wagman (Head of AI Strategy, Crescent)
Watch the full session and find key takeaways below.
Stop Counting Pilots, Start Measuring Production
For years, the industry has been enamored with AI prototypes. Gary Hoberman challenged this mindset directly: “We should stop counting pilots. You only get credit for production.”
Hoberman cautioned against the current trend of using AI simply to generate raw code, which creates massive, long-term technical debt.
“If you allow an agent to write code, it’s like hiring developers, putting them into production, and giving them access to write code in runtimes you have no control over,” Hoberman warned.
Instead, firms must rely on governed architecture and deterministic workflows to solve business problems safely.
The Shift from Labor Value to Data Value
Per Roman highlighted how AI is fundamentally changing where venture capitalists and asset managers derive alpha. With AI models rapidly commoditizing, the competitive advantage is shifting.
“The value is turning onto data,” Roman explained. “It’s the data the humans can collect when they are sitting at a dinner, at a lunch, at a golf course… generating human-to-human unique information.”
Roman noted that while AI dramatically flattens the technology landscape, firms will ultimately compete on the quality of their proprietary data, not just operational headcount.
Shifting the Culture and Rethinking Workflows
Deploying AI at scale demands a fundamental shift in corporate culture and employee mindsets.
Jon Couture emphasized that for a scaled, highly regulated organization like Vanguard, AI adoption is driven by a relentless pursuit of client value. This requires seeking out new employee skill sets. Couture noted the rising need for “a higher tolerance for ambiguity” and an “entrepreneurial orientation,” as foundational knowledge becomes commoditized.
Kelly Wagman echoed this, detailing how Crescent approaches AI as a holistic architectural shift. Moving beyond individual experimentation requires a dedicated strategy. “As we start to think about workflows that touch multiple people… you have to have a concerted effort to say, okay, we’re gonna standardize this workflow and set up the technology so that it reaches multiple people,” Wagman explained.
Rewarding Output Over Headcount
A profound structural change is on the horizon for management. Traditionally, Wall Street has rewarded leaders based on the sheer number of people they manage. Hoberman argued that in the AI era, this compensation model must flip.
“It has to be what you get done with as few resources as possible,” Hoberman argued, whether that involves agents, people, or a combination of both. “That’s what you’re rewarded for achieving. And without that, the companies won’t change.”
The Window for Action is Narrowing
The timeline for AI transformation is accelerating rapidly. As Hoberman predicted, drastic industry shifts will occur within the next six to twelve months. To stay competitive, asset managers must act urgently to rebuild their operations around secure, governed AI, ensuring every technological leap ultimately translates into unmatched client value.