Jefferies analysts said certain US stocks may be undervalued despite concerns about AI-driven disruption, with the firm identifying 24 companies that they expect could emerge as long-term winners.
Jefferies’ list of 24 discounted stocks includes Airbnb Inc (NASDAQ:ABNB, XETRA:6Z1), Aon PLC (NYSE:AON), AppLovin Corp (NASDAQ:APP), Boston Properties Inc (NYSE:BXP), CBRE Group Inc (NYSE:CBRE), Capital One Financial Corp (NYSE:COF), CoStar Group Inc (NASDAQ:CSGP), DoorDash Inc (NYSE:DASH), Equitable Holdings Inc. (NYSE:EQH), KVH Industries, Leidos Holdings Inc (NYSE:LDOS), Lincoln National (NYSE:LNC), Meta Platforms Inc (NASDAQ:META, XETRA:FB2A, SIX:FB), Morgan Stanley (NYSE:MS), Microsoft Corp (NASDAQ:MSFT), ServiceNow Inc (NYSE:NOW, XETRA:4S0), Okta Inc (NASDAQ:OKTA), Palo Alto Networks Inc (NYSE:PANW, XETRA:5AP), Charles Schwab Corp (NYSE:SCHW), Sallie Mae, Snowflake Inc (NYSE:SNOW), Spotify Technology SA (NYSE:SPOT), SS&C Technologies, and Willis Towers Watson PLC (NASDAQ:WTW).
“While it remains early days in terms of AI development and deployments, and there will certainly be long-term casualties, we believe some stocks have been unjustly accused in the court of investor opinion,” the analysts wrote.
The report highlights that while US equity benchmarks remain near all-time highs, single-stock performance has diverged sharply. According to Jefferies, the one-month realized correlation among S&P 500 constituents has stayed near 15-year lows since late 2025, reflecting increasing dispersion beneath the surface.
Jefferies noted that over the past six months, sectors including REITs, software, professional services, diversified financials, and insurance, particularly brokers, have underperformed the broader index by 10% or more.
“While it remains too early in the adoption cycle to evaluate clear evidence of AI disintermediation, for many companies within these subsectors, investors have improperly shifted the burden of proof,” the analysts wrote.
The analysts emphasized that some companies may benefit from AI, citing factors such as proprietary data, regulatory or security moats, and scale advantages.
“These companies have strong moats and business models that suggest valuations are compelling,” the analysts wrote, adding that many could eventually be seen as AI beneficiaries despite recent underperformance.