Datadog (DDOG) Chief Financial Officer David spoke at the Goldman Sachs Communacopia + Technology Conference on Thursday, Sept. 10, detailing the observability platform maker's strategy to monetize artificial intelligence and accelerate its shift toward large enterprise customers.
Datadog reported 31.5% revenue growth over the last twelve months, with gross profit margins nearing 80%. Gross customer retention sits in the upper 90s—higher still among large enterprise clients—and net retention is expanding. Thirty-five analysts have revised earnings upward for the upcoming reporting period. Shares have risen 62% over the past year and 83% over the past six months, and the stock closed at $221.72 on a subsequent date.
David said the company is pursuing a dual path in AI: improving its core monitoring product with faster, more accurate real-time signals that could eventually enable auto-remediation, and directly monetizing AI workloads through its existing infrastructure. "The vision here is to produce more accurate and quicker real-time signals which can improve the functionality of the platform and go on the continuum to allow for auto-remediation or close to it," David said. He added that one monetization route is simply extending Datadog's existing coverage to AI environments—"Datadog's monitoring CPUs, Datadog's monitoring databases."
To support that effort, Datadog acquired Adaptive ML, a reinforcement-learning specialist for IT management and observability, and established a dedicated research lab investing in GPUs, inference systems, and proprietary models including its early AI offering Toto. The company also highlighted products such as Bits, Agent Observability, Infinite Cardinality Metrics, Flex Logs, Frozen Logs, and Federated Logs.
On sales strategy, David described a move away from purely bottom-up adoption toward a structured enterprise model. Key-account teams have been reshaped to cover one or two accounts each instead of roughly ten, allowing deeper engagement on large transformation projects. Target verticals include banking, insurance, automotive, manufacturing, and airlines.
R&D spending runs approximately 30% of revenue—more than $1 billion annually. David emphasized that curation matters as much as scale: "What we have been, I think, much smarter at is understanding how the client is using the product… That is good for the customer because they get more value in their metrics. That is also good for us because it does not help us to have metrics or even logs that flow in and are costly to us."
Looking at the broader market, David estimated only 20% to 30% of applications currently reside in the cloud, leaving ample room for growth. He characterized the sector's dynamic as a recurring tension between expansion and optimization but stressed that the balance still favors growth.
Guidance for the period was described as de-risked, with the company incorporating only committed revenue from larger contracts rather than relying on usage upside beyond contract minimums.
