Julie Biel

"I would not be bullish on buying writ large because I do think there is some real existential risk to software. The type used for pure optimization is fertile ground for any type of AI disruption. You need to have some proprietary data sets and regulatory variables." Generative AI will commoditize basic optimization and workflow software. However, enterprise software companies that own massive, proprietary data moats and operate in complex regulatory environments will be insulated from AI disruption and can actually monetize AI features effectively. Long high-quality enterprise software companies with deep proprietary data moats, while avoiding speculative, narrative-driven tech. A broader macroeconomic slowdown could cause enterprise IT budgets to contract, hurting even high-quality software vendors.

"I would not be bullish on buying writ large because I do think there is some real existential risk to software. The type used for pure optimization is fertile ground for any type of AI disruption. You need to have some proprietary data sets and regulatory variables." Generative AI will commoditize basic optimization and workflow software. However, enterprise software companies that own massive, proprietary data moats and operate in complex regulatory environments will be insulated from AI disruption and can actually monetize AI features effectively. Long high-quality enterprise software companies with deep proprietary data moats, while avoiding speculative, narrative-driven tech. A broader macroeconomic slowdown could cause enterprise IT budgets to contract, hurting even high-quality software vendors.

"I would not be bullish on buying writ large because I do think there is some real existential risk to software. The type used for pure optimization is fertile ground for any type of AI disruption. You need to have some proprietary data sets and regulatory variables." Generative AI will commoditize basic optimization and workflow software. However, enterprise software companies that own massive, proprietary data moats and operate in complex regulatory environments will be insulated from AI disruption and can actually monetize AI features effectively. Long high-quality enterprise software companies with deep proprietary data moats, while avoiding speculative, narrative-driven tech. A broader macroeconomic slowdown could cause enterprise IT budgets to contract, hurting even high-quality software vendors.

Biel notes that regional banks did not participate in the rally last year but now have an opportunity to improve due to "deregulation" and the ability to "do more with the balance sheets." If regulatory pressure eases and consolidation occurs (which Biel expects), regional banks can regain profitability and market share, trading at attractive multiples compared to large caps. Long Regional Banks as a deregulation/catch-up trade. Continued commercial real estate exposure and high interest rates.

Biel states investors have "gotten a bit burned by long-standing software names" and are recognizing they "want to own hard assets, companies that make stuff." There is a capital rotation occurring away from digital/software assets (due to AI disruption fears) toward cyclical upswings in the real economy and "tools providers" in healthcare that are insulated from binary regulatory risks. Long "Hard Assets" and non-binary Healthcare. Economic slowdown dampening cyclical demand.

Biel states investors have "gotten a bit burned by long-standing software names" and are recognizing they "want to own hard assets, companies that make stuff." There is a capital rotation occurring away from digital/software assets (due to AI disruption fears) toward cyclical upswings in the real economy and "tools providers" in healthcare that are insulated from binary regulatory risks. Long "Hard Assets" and non-binary Healthcare. Economic slowdown dampening cyclical demand.