Author argues that AI-disruption uncertainty is far harder to assess in software names than in non-software businesses like EXPD, LSTR, CBRE, SCHW and AJG, which are down ~20% and offer ~25% recovery upside with easier analysis.
EXPD — LONG The author argues that AI agents and startups are unlikely to displace the complex work of insuring and moving containers through customs across borders, making EXPD's business model more AI-resistant than software names. He notes such non-software companies are down around 20%, implying roughly 25% upside on recovery, and that this thesis can be assessed with more confidence and in far less time than a software name. The main stated risk is that the AI-disruption impact is genuinely hard to be confident about, though he judges it easier here than in software.
if startups with shiny new AI agents will be able to insure and move containers from Vietnam through customs to Germany (EXPD)
LSTR — LONG The author contends that AI agents will struggle to replicate the contracting with shippers and operators needed to truck loads from Florida to Denver and handle last-mile delivery, making LSTR less vulnerable to AI disruption than software. He frames these non-software names as down about 20% with roughly 25% recovery upside, and easier to underwrite than software. The stated risk is uncertainty about how much AI actually threatens these operations.
contract with shippers and operators to truck loads from Florida to Denver then the last mile to destination (LSTR)
CBRE — LONG The author argues that financing and negotiating a $50MM commercial real estate deal and then managing the property is work AI agents are unlikely to take over, making CBRE a more assessable AI-disruption play than software. He notes these non-software companies are down around 20%, offering roughly 25% upside on recovery, with far less research time required. The main risk he acknowledges is the difficulty of being confident about AI's real impact.
finance and negotiate a $50MM commercial real estate deal then manage the property (CBRE)
SCHW — LONG The author argues that custodying trillions of dollars and executing trillions of trades for millions of clients is a business AI startups are unlikely to disrupt, making SCHW a more confident bet than bombed-out software. He frames the opportunity as non-software names down about 20% with roughly 25% recovery upside, analyzable in a fraction of the time. The stated risk is uncertainty over AI's actual impact on these businesses.
custody trillions of dollars and execute trillions of trades for millions of clients (SCHW)
AJG — LONG The author argues that placing and managing layers of global insurance and reinsurance is work AI agents will not easily replace, making AJG a more assessable AI-disruption play than software names. He notes these non-software companies are down around 20%, implying roughly 25% upside on recovery, with much less research effort needed. The main stated risk is the difficulty of being confident about AI's impact.
place and manage layers of global insurance and reinsurance (AJG)