The original title is "AI Agent Audit Trails: Manual Logging vs. AgentLedger"

Short summary

AI teams must choose between manual logging with existing observability tools versus AgentLedger, a purpose-built decision-tracing framework, based on compliance requirements. Manual logging works for low-stakes internal automation but fails regulatory audits; AgentLedger captures decision reasoning, policies, and review thresholds. Start with manual logging for 30 days; if you cannot reconstruct specific decisions, migrate to AgentLedger.

• •72% of organizations use AI in business functions but lack audit trails for agent decisions
• •Manual logging (Datadog, Grafana) sufficient for internal automation; fails compliance when decisions affect external stakeholders
• •AgentLedger required for regulated decisions in finance, healthcare, legal systems—captures reasoning and policy trails auditors demand
• •Recommendation: manual logging first, migrate to AgentLedger when the 30-day reconstruction test fails

Generated with AI, which can make mistakes.