What is Agentic AI Governance?
Agentic AI governance refers to the comprehensive framework of policies, technical controls, and audit mechanisms that ensure autonomous AI agents operate within defined institutional boundaries while maintaining full accountability for their decisions.
Why Traditional AI Governance Falls Short
Traditional AI governance was designed for predictive models and chatbots - systems that respond to queries but don't take autonomous actions. Agentic AI is fundamentally different: these systems can plan, execute multi-step workflows, and make decisions that affect real-world outcomes.
The Three Pillars of Agentic AI Governance
**1. Intent Capture** Every autonomous decision must be traceable to its origin. This means capturing not just what the agent did, but the raw intent signals that prompted the action.
**2. Policy Enforcement** Institutional guardrails must be woven into the execution path, not bolted on as an afterthought. Agents must operate within policy boundaries from the first decision.
**3. Cryptographic Auditability** Every decision thread must be sealed with tamper-evident cryptographic proofs. SHA-256 hashing ensures that if any record is altered post-decision, the integrity violation is immediately detectable.
The Cost of Getting It Wrong
Foundation Capital estimates the agentic AI market at $4.6 trillion over the next five years. But enterprises that deploy autonomous agents without proper governance face:
- **Legal liability** for decisions made "in a black box"
- **Regulatory penalties** in industries like healthcare and finance
- **Reputational damage** from AI hallucinations or rogue behavior
How Mala.dev Approaches Agentic Governance
Mala.dev provides the Decision Substrate for the agentic era - a cryptographically sealed system of record that captures, contextualizes, and seals every autonomous decision with SHA-256 integrity proofs.