AI-native SaaS is software-as-a-service built around AI workloads rather than simple human logins. Instead of charging mainly by seat, it often bills by tokens, credits, workflow runs, or completed outcomes. In this model, the product’s core resource is compute and model output, not just access.
For cyber security, this matters because usage telemetry becomes sensitive control data. Attackers may abuse prompts, agents, or API keys to generate excessive inference costs, replay usage events, or skew billing and renewal metrics. Defenders need strong authentication, rate limits, audit logs, and reconciliation checks to spot runaway agents, duplicate metering, or tampered records. In AI-native SaaS, protecting the meter is part of protecting the service.