Our Take
Levchin's stance highlights that AI productivity gains don't automatically require headcount reduction if companies already run lean operations.
Why it matters
The split approach among major fintechs signals that AI's workforce impact depends more on existing operational efficiency than the technology itself. Finance executives watching peer moves need clearer frameworks for AI ROI beyond simple labor substitution.
Do this week
Finance leaders: audit current operational efficiency metrics before announcing AI-driven workforce changes so you can justify decisions with data rather than industry trends.
Affirm CEO rules out AI layoffs despite automation gains
Affirm CEO Max Levchin told analysts Thursday that the buy-now-pay-later lender will not cut jobs due to AI adoption, even as the company increases its use of artificial intelligence for software engineering. "We are not planning AI-related layoffs, full stop," Levchin said during the company's fiscal third-quarter earnings call.
The statement comes as other major fintechs take the opposite approach. Block CEO Jack Dorsey highlighted AI-driven restructuring results on a separate earnings call Thursday, while Coinbase announced layoffs affecting 14% of staff this week, citing both crypto market conditions and AI capabilities.
Levchin explained Affirm's position by pointing to existing operational efficiency. "Long before AI tools came along, we had tooled ourselves up to be very efficient. These tools are giving us rocket boosters, wings, whatever metaphor you want, and we're very happy for it," he said. The company views AI as an accelerator for shipping more products rather than a replacement for human workers.
Divergent strategies reveal efficiency baselines matter more than AI capabilities
The contrasting approaches between Affirm and its peers illuminate a critical distinction in how companies deploy AI productivity gains. While the technology offers similar capabilities across organizations, the decision to reduce headcount appears driven more by pre-existing operational structure than by AI's inherent labor-saving potential.
Affirm's strong financial performance supports Levchin's approach. The company reported Q3 revenue of $1.04 billion (up 33% year-over-year) and net income of $102 million, beating analyst expectations of $60.6 million. Gross merchandise value grew 35% to $11.6 billion (per company reporting), marking the tenth consecutive quarter of 30%-plus growth.
The funding environment also remains favorable for Affirm despite broader private credit concerns. COO Michael Linford described the funding market as "exceptionally constructive," with asset-backed securities providing strong execution that keeps other investors competitive.
Different efficiency baselines require different AI strategies
Finance leaders should evaluate their current operational efficiency before following industry AI adoption patterns. Companies already running lean operations may find AI amplifies existing productivity without requiring workforce reduction, while those with operational slack may see clearer ROI from labor substitution.
The Affirm example suggests that AI's workforce impact is not predetermined by the technology itself. Organizations with established efficiency practices can deploy AI as a capability multiplier rather than a cost-cutting tool. This approach may preserve institutional knowledge and avoid the disruption costs associated with restructuring.
William Blair analysts noted that "the digital finance space will remain under pressure as the market worries about the consumer and private credit," making operational decisions even more consequential for long-term positioning.