Elastic (ESTC) Morgan Stanley Technology, Media & Telecom Conference 2026 summary

Business performance and growth trends

• Sales-led subscription revenue growth accelerated to 19%, with strong operating income and a record number of million-dollar deals.

• Segmentation of sales teams into hunting and farming territories has improved strategic deal signings.

• AI adoption is growing, with nearly a quarter of $100K+ customers using AI-related solutions.

• Self-managed deployments are increasing, especially in regulated industries, government, and Europe, due to data sovereignty and security needs.

• Guidance for Q4 reflects risk adjustments and fewer days in the quarter, but underlying business trends remain strong.

AI strategy and platform differentiation

• The platform enables real-time, relevant data context for large language models, supporting AI use cases at scale.

• Differentiation comes from the ability to run both in cloud and self-managed environments, offering flexibility and security.

• AI workloads drive higher consumption, with AI users showing a 6% average uplift in platform usage.

• The platform's defensible moat is its data store and context/relevance capabilities, making it integral to AI and agentic workflows.

• Recent innovations include Jina models, Agent Builder, workflow automation, LLM observability, and Elastic Inference Service.

Market positioning and competitive landscape

• The platform is positioned as a core data retrieval and context engine for enterprise AI, security, and observability.

• AI adoption is a structural tailwind, expected to steadily increase revenue growth through 2029.

• The company is ahead in security with early AI features like Attack Discovery, winning transformative deals such as with CISA.

• Observability growth aligns with the log industry, with new metrics data store launching mid-year to enhance competitiveness.

• Continuous efficiency improvements in the platform create short-term revenue headwinds but support long-term market share gains.