Datadog (DDOG) Q2 2025: AI Native Revenue Jumps to 11%, Broadening Platform Adoption

August 7, 2025 | By EarningsIQ Research

AI native customers now drive 11% of Datadog’s revenue, with usage growth outpacing expectations and platform adoption climbing across segments. Security ARR surpassed $100 million, and customer expansion signals Datadog’s unified observability model is deepening its enterprise foothold. Guidance embeds caution on AI cohort volatility, but management’s tone and product momentum suggest Datadog is positioning for durable, multi-segment growth as AI adoption spreads beyond early movers.

Summary

• AI Native Customer Surge: AI native cohort now represents a meaningful share of revenue, driving incremental growth.
• Multi-Product Expansion: Customers increasingly adopt four or more Datadog products, boosting platform stickiness and wallet share.
• Security and R&D Investment: Security suite crosses $100 million ARR, while R&D and go-to-market hiring fuel product velocity and global reach.

Performance Analysis

Datadog delivered robust top-line growth, outpacing guidance with 28% year-over-year revenue expansion and broad-based customer gains. The most notable driver was the surge in AI native customers, who contributed 11% of Q2 revenue, up from 8% last quarter and 4% a year ago. This cohort alone accounted for 10 points of total revenue growth, reflecting Datadog’s early capture of AI-driven observability workloads. Excluding the largest AI customer, revenue growth remained stable, underscoring a healthy core business.

Platform adoption continues to climb, with 52% of customers now using four or more products (up from 49% last year), and 14% using eight or more. Security ARR grew at a mid-40s percentage rate, now exceeding $100 million, as customers consolidate tools and expand coverage. Free cash flow margin held at 20%, while gross margin rebounded as Datadog’s own cloud cost optimization initiatives took effect. Notably, billings and RPO growth outpaced revenue, but management reiterated that revenue remains the best indicator of true business momentum, given contract and billing variability.

• AI Native Revenue Mix Shift: AI native customers now drive a double-digit share of revenue, accelerating Datadog’s aggregate growth.
• Security Suite Momentum: Security products surpassed $100 million ARR, with expansion opportunities in large enterprises and new AI-driven features.
• Operational Leverage from Cloud Efficiency: Gross margin improved as Datadog’s engineering teams optimized cloud usage, with further gains expected in the second half.

Customer wins highlight Datadog’s role as a strategic platform for large-scale cloud migration, AI observability, and security modernization, with marquee deals across banking, insurance, media, retail, and e-commerce verticals.

Executive Commentary

Strategic Positioning

1. AI Native Cohort as Growth Engine

AI native customers have become a major growth engine, now accounting for 11% of revenue and driving incremental expansion. Datadog is deeply embedded in the AI infrastructure stack, serving both inference and training workloads, and is monitoring applications where code is increasingly written by AI agents. Management views this cohort as a leading indicator for broader enterprise AI adoption, with hundreds of customers in this group, including eight of the top ten AI companies.

2. Platform Consolidation and Multi-Product Adoption

Datadog’s unified platform strategy continues to resonate, as customers consolidate observability and security tools. Over half now use four or more products, and large deals increasingly involve comprehensive product suites, including FlexLogs, which addresses economic and predictability concerns for log management. This cross-sell momentum is driving higher net retention and deepening customer relationships.

3. Security Suite Inflection and Expansion

Security ARR surpassed $100 million, with growth in the mid-40s percent, but management acknowledged the need to drive standardized, enterprise-wide adoption. The focus is shifting to top-down sales motions and further product expansion (both organic and through M&A), as AI-driven security threats and compliance needs intensify. Recent product launches, like Beats AI Security, aim to automate detection and response for emerging risks.

4. R&D and Go-to-Market Investment

Datadog’s aggressive hiring in R&D and sales is yielding tangible product and pipeline results, as evidenced by 125 new product and feature launches at the June Dash conference. The company is investing in AI research (e.g., Toto time series forecasting) and scaling autonomous agents for SRE, coding, and security. International expansion is accelerating, with higher investment intensity outside North America, particularly in Brazil, India, and APJ.

5. Cloud Cost Management and Margin Discipline

Internal cloud efficiency initiatives are directly improving gross margin, with Datadog “dogfooding” its own cost management and profiling products. This not only supports near-term margin improvement but also provides a proof point for customers, reinforcing Datadog’s value proposition as both a technology and economic partner in cloud transformation.

Key Considerations

This quarter underscores Datadog’s ability to capture new AI-driven workloads while expanding its platform footprint in traditional enterprise segments. The company’s approach to product innovation, customer expansion, and operational discipline positions it to benefit from secular trends in cloud migration, digital transformation, and AI adoption, but also introduces new sources of volatility and competitive intensity.

Key Considerations:

• AI Native Growth Concentration: AI native customers now drive a significant share of growth, but management warns of potential usage and contract volatility as this cohort matures.
• Security as a Growth Vector: Security suite is gaining traction, but enterprise-wide standardization and further product development are needed to fully realize its potential.
• Sales and R&D Productivity: Accelerated hiring is translating to new logo wins and faster product delivery, but ongoing investment is required to sustain momentum in a competitive market.
• Cloud Cost Optimization: Efficiency gains are boosting margins and serving as a differentiator for customers seeking predictable observability economics.
• International Expansion: Higher investment outside North America is driving above-average growth in emerging markets, broadening Datadog’s addressable opportunity.

Risks

Datadog’s increasing reliance on AI native customers introduces revenue concentration and volatility risk, particularly as large contracts are renegotiated and usage patterns evolve. Competitive pressure remains intense, especially from open-source and point solutions, and Datadog must execute on both product innovation and enterprise go-to-market to maintain its leadership. Currency fluctuations and international expansion add further complexity to margin and growth management.

Forward Outlook

For Q3 2025, Datadog guided to:

• Revenue of $847 to $851 million (23% YoY growth)
• Non-GAAP operating income of $176 to $180 million (21% margin)

For full-year 2025, management maintained guidance:

• Revenue of $3.312 to $3.322 billion (23% to 24% YoY growth)
• Non-GAAP operating income of $684 to $694 million (21% margin)

Management highlighted:

• Guidance incorporates conservative assumptions for AI native cohort volatility, despite no current signs of slowdown.
• Ongoing margin improvement expected from continued cloud efficiency and cost management initiatives.

Takeaways

Datadog’s Q2 results reinforce its position as a leading observability and security platform, capturing secular tailwinds from cloud and AI adoption while balancing growth investment with operational discipline.

• AI-Driven Expansion: The AI native cohort is now a material revenue contributor, but also a source of potential volatility as Datadog navigates customer optimization cycles and contract renewals.
• Multi-Product and Security Growth: Cross-sell momentum and security suite traction are driving higher retention and wallet share, but enterprise-wide adoption remains a key execution priority.
• Margin and Platform Leverage: Internal cost optimization is supporting margins and serving as a customer proof point as economic scrutiny of observability spend intensifies.

Conclusion

Datadog’s accelerating AI native revenue and broad platform adoption signal durable growth potential, but the company must manage new sources of volatility and execute on both product and go-to-market fronts to sustain its competitive edge. Investors should watch for signs of AI cohort normalization, security suite expansion, and continued leverage from cloud cost management in the coming quarters.

Industry Read-Through

Datadog’s results highlight the rapid shift of observability workloads to cloud and AI-driven applications, with AI native customers now setting the pace for broader enterprise adoption. The platform consolidation trend is intensifying, as customers seek unified solutions for observability, security, and cost management. Security and automation are emerging as critical battlegrounds, with integrated suites and autonomous agents gaining traction. Competitors in observability, security, and cloud infrastructure should expect continued pressure to innovate and consolidate, as customers demand both technical breadth and economic predictability in their tooling.

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