Bank of America Securities is betting that the artificial intelligence boom will be a bigger tailwind for the companies that build the plumbing of the digital world than for those selling the flashier AI applications. The bank raised its price targets on four infrastructure software names—Datadog, Dynatrace, Elastic, and Atlassian—while cutting its target on UiPath, a maker of automation software, as competition in enterprise AI intensifies.
What is infrastructure software?
Infrastructure software is the behind-the-scenes technology that companies use to run, monitor, and manage their applications. Think of it as the control room for a company's digital operations: it tracks performance, stores and searches data, and helps teams collaborate. These tools don't always grab headlines, but they are essential—and increasingly, they are benefiting from the AI wave.
BofA's argument is straightforward: as companies roll out more AI features, they generate more system activity. More data to store and search, more services to keep running, and more things that can break. That activity translates into higher usage of monitoring, search, and workflow tools—especially when vendors charge based on usage, meaning customers pay more as they process more data or run more queries.
Target changes: winners and losers
BofA raised its price target on Datadog to $335 from $305, Dynatrace to $78 from $65, Elastic to $114 from $108, and Atlassian to $252 from $210. These are the "picks-and-shovels" names that stand to benefit mechanically from AI adoption.
But the bank drew a clear line between these infrastructure players and enterprise AI applications. It warned that UiPath and C3.ai face the highest risk of analysts cutting forward forecasts as competition heats up, and it lowered UiPath's target to $12 from $15.
Why infrastructure benefits from AI
The logic behind BofA's optimism is that AI doesn't just create new applications—it creates new demands on the underlying systems. Every AI feature added to a product means more logs, metrics, and traces (the digital breadcrumbs of what systems are doing), plus more search and collaboration activity. With usage-based pricing, that extra load can translate directly into revenue without a company having to dominate a single headline-grabbing AI category.
For example, when a company deploys an AI chatbot, it needs to monitor the performance of that chatbot, store the data it generates, and search through that data for insights. Infrastructure software providers are the ones that get paid for that activity, often on a per-use basis. That's a more predictable revenue stream than selling a one-time software license.
The risk in enterprise AI apps
Enterprise AI applications—like UiPath's robotic process automation tools or C3.ai's AI-based analytics—face a different dynamic. When many vendors offer similar productivity tools, customers can shop around, weakening pricing power. That makes earnings estimates easier to revise down, which is the risk BofA highlighted heading into the Q3 earnings season.
UiPath, in particular, has been under pressure as competitors like Microsoft and other tech giants push into automation. The bank's cut to its price target reflects a belief that the company may struggle to maintain its growth rate in a crowded market.
What it means for investors
For everyday investors, this is a reminder that "AI winners" in software aren't all competing in the same way. Infrastructure software often benefits mechanically from AI adoption, while enterprise AI apps face more competitive headwinds. That distinction matters when evaluating which companies might see their earnings estimates rise or fall.
BofA's move also highlights the importance of usage-based pricing models. Companies that charge by the amount of data processed or queries run can see revenue grow in lockstep with AI-driven activity, without needing to win a single dominant application category.
Investors should watch how these companies report usage metrics in upcoming earnings calls. A pickup in consumption could validate BofA's thesis, while a slowdown might suggest the AI tailwind is less powerful than hoped.
For context, the broader market has been closely watching how AI spending translates into revenue. US business growth has cooled, but price pressures persist, which could complicate the Federal Reserve's path. That macro backdrop matters for software stocks, which are sensitive to interest rates and economic growth.
Also worth noting: RingCentral shares jumped 14% after a Q3 beat, showing that software companies with strong execution can still reward investors. But the contrast with UiPath's cut underscores that not all software stories are equal.
The bottom line
BofA's target changes are a signal that the AI trade is becoming more nuanced. Infrastructure software looks like a safer bet as AI adoption grows, while enterprise AI apps face tougher competition. For investors, the takeaway is to look beyond the "AI" label and understand how a company actually makes money from AI—whether through usage-based infrastructure or through applications that must fight for customers.
As always, price targets are just one analyst's view, and the market will ultimately decide. But the direction of BofA's moves—up for infrastructure, down for UiPath—offers a useful lens on where the AI opportunity may be shifting.
