Enterprise systems of record can defend the AI control plane through data, permissions, workflow authority and governance, but activity must convert into retained paid economics while human-seat value compresses.
CATCH-UP / MISSED PRIOR: Salesforce has a production-agent usage receipt, but only for survivors
Analysis by Frank Locascio and TheBRRR Research
What happened
Salesforce's Agentic Enterprise Index Second Edition reports that among businesses with Agentforce agents active in production every month from February 2025 through April 2026, average activated agents rose from 5 to 13, average unique skills per agent rose from 2 to 6, the action-to-output ratio grew at a reported 15% compound monthly rate, and Salesforce counted 734 million self-defined Agentic Work Units in April 2026. The primary methodology omits cohort size and excludes failed, paused and newly adopting organizations.
Why it earned coverage
Direct production telemetry on agents invoking business logic is stronger than a survey and directly tests whether an incumbent system of record can remain the action and governance plane for agents.
Investment transmission
Agents that update CRM records and invoke APIs increase the value of governed data, permissions and workflow ownership, allowing incumbents to defend the control plane even as human seats compress. A continuously active survivor cohort can scale while broader customers fail, and action counts can increase cost without improving outcomes. Durable value requires retained paid workflows, incremental revenue and successful-task economics above inference and implementation costs.
Affected exposures
Next observable receipt
Cohort denominator and inclusion counts, failed and paused deployments, Agentforce ARR and organic contribution, RPO and NRR, customer spend expansion, inference-adjusted gross margin, seats and pricing, task success, human escalation and independent customer references.
What would invalidate it
Aggregate customer data show high abandonment, low renewals, stagnant Agentforce revenue, rising inference or implementation cost, poor task success or AI-native competitors displacing the incumbent control plane.