Goldman Sachs Group Inc.’s use of artificial intelligence is enabling the bank to expand its operations without significantly increasing its workforce, according to President and Chief Operating Officer John Waldron.
Waldron’s Vision for AI Integration
“I often describe Goldman Sachs as a human assembly line,” Waldron said in a CNBC interview on Tuesday. “If you think about what’s happened in manufacturing, it’s become much more robotic, it’s become much more automated. The banks really haven’t been on that journey to the same extent.”
Back-office roles are increasingly being handled by machines at Goldman Sachs and across Wall Street, where executives are identifying additional areas where AI can improve efficiency and drive growth. This trend raises questions about potential job losses.
Digital Agents as the New Robots
“Our human assembly lines will become more digitized, digital agents will be our robots,” Waldron said. “I’m not sure dynamically how the overall headcount will change, but I think the firm is going to get much more resilient and much more scalable.”
Waldron, widely seen as the front-runner to succeed CEO David Solomon, launched a strategy called “OneGS 3.0” to implement efficiency savings generated by AI. Areas benefiting from these savings include client onboarding, lending processes, regulatory reporting, and vendor management.
Measuring Success of AI Deployment
At the bank’s RIA Professional Investor Forum on Tuesday, Waldron told attendees that the success of AI deployment is measured through productivity gains, cost savings, and forgone investments.
Waldron said it remains unclear how AI will change Goldman’s organizational structure. Some industry observers suggest the technology could reduce headcount at junior levels, narrowing the base of the traditional corporate pyramid.
Pyramid or Diamond?
“We don’t know yet whether it’s a diamond or a pyramid,” Waldron said.
Regarding the broader economy, Waldron noted that many reported layoffs are not yet due to generative AI deployment but rather firms correcting “hoarding of employees” after the Covid-19 pandemic. He predicted that savings from generative AI could start affecting organizational structures more broadly in 2027 and 2028.
