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SaaS Industry Structure in the AI Era
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SaaS Industry Structure in the AI Era

Per-seat collapse, usage-based transition, data moat formation — how AI is restructuring the SaaS industry itself.

May 20, 2026

The SaaS industry faces a fundamental revenue model inflection point driven by AI agent proliferation. As per-seat models weaken and usage/outcome-based pricing emerges, the bifurcation between data-moat platforms and feature-selling tools is accelerating.

Market Size

Global SaaS market: ~$320B in 2025 → projected $820B by 2030 (CAGR ~20%)

Key Trends

Per-seat → Usage/Outcome Shift

Share of companies using outcome-based pricing jumped from 2% to 18% in 2Q25. 37% plan to change their pricing model within a year.

AI Agent Execution Layer Demand

As AI agents scale, structural demand grows for platforms (ServiceNow, Salesforce) that handle execution on legacy systems.

Data Accumulation Platform Bifurcation

Platforms where customer data accumulates become AI substrates; feature-only tools get eaten by AI startups. Gartner projects 35% of point-product SaaS to be replaced by AI by 2030.

Stock-Earnings Divergence

During the 2025 SaaS stock crash, RPO, NRR, and ARR were actually rising. Market fear outran actual fundamentals.

Key Players

ServiceNowAI agent execution layer monopoly
SalesforceData moat + outcome-based transition leader
SnowflakeTextbook usage-based data platform
DatadogStructural AI infrastructure monitoring beneficiary
MongoDBDefault data layer for AI app developers
Microsoft 365Competitive pressure across SaaS via Copilot