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Tuesday's Bonus Story SaaS Apocoplyse Survivor? Why Datadog Could Be a Real AI WinnerSubmitted by Leo Miller. Originally Published: 3/26/2026. 
Key Points - The so-called "SaaS Apocalypse" has resulted in somewhat indiscriminate, leading to opportunities and value traps.
- As AI proliferates, Datadog could be a big beneficiary, yet shares remain down almost 40% from their highs.
- Despite the stock’s year-to-date decline, analysts see DDOG rising well above the current share price.
- Special Report: Elon Musk: This Could Turn $100 into $100,000
Over the past few months, many investors have likely encountered the phenomenon known as the “SaaS Apocalypse.” This describes a trend of software-as-a-service (SaaS) stocks seeing their share prices fall amid the rise of new artificial intelligence (AI) tools. To some extent, markets appear to be selling off any stock with even a SaaS-adjacent business model. But the impact of AI disruption will not be uniform across all SaaS companies. That divergence can create opportunities in certain SaaS names poised to benefit from AI adoption rather than being replaced by it. One tech stock that may fit this description is Datadog (NASDAQ: DDOG). While shares have recovered from recent lows, the stock is still down about 10% in 2026 and nearly 40% from its 52-week high. Some investors believe the market may be misreading what Datadog's role could look like in an AI-heavy enterprise environment. Understanding the Drivers Behind the "SaaS Apocalypse" One of AI's big promises is that AI agents will be able to act autonomously across enterprise workloads. The theory is that deploying agents will allow companies to significantly reduce costs by having agents perform tasks that previously required expensive SaaS products. That potential cost-savings is a major reason incumbent SaaS companies have seen their shares fall. Some also argue that a single highly competent employee equipped with AI agents could do the work of several people, leading to lower headcount and reduced costs. This is a key value proposition from AI developers such as OpenAI, Anthropic, and Google's parent company Alphabet (NASDAQ: GOOGL). Their pitch: pay us to deploy your AI agents, and you'll need fewer employees. However, AI is far from perfect and can make mistakes. That becomes apparent with consumer-facing chatbots and can erode trust in AI models. Inside an organization, errors can have larger consequences—customer impact, revenue leakage, and operational disruption. Therefore, businesses are unlikely to adopt AI agents at scale without first building trust over time and being able to diagnose failures quickly. This is one area where observability vendors argue they can help. Outsourcing Thinking: AI Agents Increase the Need for Observability Datadog sells observability software that collects data from companies' applications—both internal and customer-facing—so organizations can detect problems, identify root causes, and resolve incidents. A key part of the bull case for Datadog is that while AI agents may reduce headcount, they also introduce complexity and generate far more data. A video on Datadog's AI Agent Monitoring tool illustrates this well. In the demo, the speaker describes a fictional personal finance app called Budget Guru, where a user asks the AI agents to perform a simple task: buy $500 of a stock and remind them about an overdraft fee. A human could complete that task in a few clicks and perform the necessary thinking internally. Budget Guru, however, coordinates five separate AI agents to execute the same task—essentially outsourcing the thinking a human would have done. In the process, those agents generate a large volume of observable data about how they reached their conclusion. AI agents produce logs, traces, and events that wouldn't exist if a human had performed the task. As the number of moving parts grows, so do potential failure points. In that framework, AI agents don't eliminate the need for monitoring; they raise the bar for it. That dynamic should increase demand for observability platforms like Datadog, turning dispersion risk into an opportunity. Datadog: Impressive Growth, Profitability, and Analyst Support In its latest quarter, Datadog's revenues grew 29% year over year to $953 million. The company also generated free cash flow (FCF) of $291 million, yielding an FCF margin of roughly 31%. The Rule of 40 combines revenue growth and profit margins to evaluate how well a SaaS company balances growth and profitability. With a score above 40 seen as healthy, Datadog comes in well-positioned at about 60. Notably, Wall Street analysts see considerable potential in Datadog. The MarketBeat consensus price target sits near $180, implying more than 40% upside. Price targets updated after the company's latest earnings report show a slightly lower average, near $174. Overall, with strong growth, solid profitability, analyst backing, and potential AI-agent tailwinds, there are reasons to believe DDOG could defy the "SaaS Apocalypse." | 
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