Dynatrace shares got a boost this week after UBS analysts highlighted the company's recent acquisition of Arize AI as a potential catalyst for a new growth category: AI observability. The investment bank believes that as enterprises deploy more artificial intelligence models, the tools used to monitor those models will become a significant part of the broader observability market.
Observability software, in plain terms, helps companies keep an eye on their applications and IT infrastructure. It tracks performance, detects errors, and helps teams pinpoint the root cause of problems before they affect users. Think of it as a health monitor for software systems.
Now, with AI models becoming a bigger part of business operations, a new layer of monitoring is emerging. AI observability focuses on tracking the behavior of machine learning models in production—watching for issues like poor outputs, data drift, or outright failures after the model has been deployed. UBS argues this niche is about to take off.
What UBS is saying
Based on industry checks, UBS projects that AI observability could grow to represent 20% to 25% of all observability spending over the next few years. That's a substantial shift in a market that has traditionally been dominated by application performance monitoring and infrastructure monitoring.
For Dynatrace, the firm estimates this could add 3 to 4 percentage points to its revenue growth. That's a meaningful bump for a company that, like many software vendors, has seen growth moderate as customers tighten IT budgets.
The Arize acquisition, which Dynatrace completed earlier this year, is central to this thesis. Arize brings specialized tools for monitoring AI models, including capabilities for detecting bias, tracking model performance, and explaining predictions. By folding Arize into its platform, Dynatrace is positioning itself to capture spending from enterprises that are scaling AI initiatives.
Why AI observability matters
As companies rush to integrate AI into their products and operations, they're discovering that AI models behave differently than traditional software. Models can degrade over time as the data they were trained on becomes less representative of real-world conditions. They can also produce biased or harmful outputs, which creates regulatory and reputational risks.
That's where AI observability comes in. It gives teams visibility into how models are performing in the wild, alerting them to anomalies and helping them retrain or adjust models before problems escalate. For businesses, this is becoming a necessity rather than a nice-to-have.
UBS's view is that this need will translate into real spending. As enterprise AI budgets scale, a portion of that money will flow to vendors that can help manage and monitor AI systems. Dynatrace and its rival Datadog are seen as the two main beneficiaries in the observability space.
What it means for investors
For everyday investors, the key takeaway is that AI is not just about the companies building the models—it's also about the infrastructure and tools that support them. Observability is a classic example of a pick-and-shovel play: even if specific AI applications succeed or fail, the companies that provide the underlying monitoring and management software stand to benefit from the overall trend.
That said, UBS's projections are just that—projections. The pace at which AI observability becomes a mainstream spending category will depend on how quickly enterprises deploy AI in production and how much they're willing to pay for specialized monitoring. There's also competition to consider; Datadog and other players are investing heavily in similar capabilities.
For Dynatrace, the Arize deal is a bet that AI observability will be a meaningful growth driver over the next few years. If UBS is right, the company could see a noticeable acceleration in revenue growth. If not, the acquisition may simply add to a crowded product portfolio.
Investors should also keep an eye on the broader software spending environment. AI is a priority for many companies, but budgets are still finite. The wild cards for tech spending remain interest rates and the pace of AI adoption. And while the US economy has shown resilience, any slowdown could push enterprises to delay non-essential IT projects.
Ultimately, the AI observability story is one to watch. It's a reminder that the AI boom has many layers, and the companies that help manage the chaos of AI deployment could be quiet winners.
