The headline that caught my attention is straightforward: “Chip ETFs Beyond Nvidia: JPM Sees Opportunity In AI Software Underdogs”, reported by Benzinga, with HubSpot and Microsoft named in the framing. I think that framing matters more than it looks at first glance. For the last cycle, market attention has been dominated by the obvious winners in AI infrastructure, especially around chips. My read is that this story is signaling a second-order shift: once the compute layer becomes expected, execution at the software layer starts to separate operators from spectators.
I am watching this because founders and operators are now navigating a different constraint. Earlier, the core question was access to AI capability. Now, the harder question is conversion: who can turn AI capability into durable workflow value, repeatable outcomes, and measurable business lift. If institutional voices like JPM are highlighting “AI software underdogs,” that suggests the market is increasingly pricing operational leverage, not just hardware scarcity narratives.
What this means for builders and operators
I think this is a useful reset for company builders. A lot of teams still speak about AI in feature language, but markets and customers eventually reward system language: integration depth, time-to-value, adoption inside real business processes, and reliability under production pressure. That is where software companies either earn compounding advantage or become replaceable wrappers.
When HubSpot and Microsoft show up in the same headline context, I read that as a signal about platform gravity. Not because they are the same business, but because both sit close to daily operational workflows where AI can actually change behavior: sales cycles, marketing execution, productivity loops, and decision speed. I am less interested in AI demos and more interested in where AI reduces friction in revenue and operations every single day.
For founders, I think this creates a clear strategic lens: ownership of workflow beats novelty of model access. For operators, my read is that the winning posture is disciplined implementation over experimentation theater. The gap between “AI-enabled” and “AI-effective” is still wide, and that gap is where underdogs can outperform larger narratives.
My read on the timing
I think this moment reflects a maturing AI market. The first wave rewarded exposure. The next wave likely rewards execution quality inside software businesses that translate AI into practical outcomes. I am watching for companies that quietly improve throughput, decision quality, and customer conversion without relying on hype cycles to explain their value.
In short, this is not a move away from chips; it is a move toward where chip-driven capability gets monetized in the real economy. My read is that builders who understand that distinction early will make better product and operating bets.
Discussion
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