AI & Agentic AI Governance: From principles to operating controls



Agentic AI Leadership - "Agentic AI introduces autonomous action. Governance has to evolve from ethics statements to enforceable controls, metrics, and continuous assurance." 


SGA Praxis helps you build the operating model: council/decision rights, stage-gates, AI inventory & risk registry, scorecards, and automation-enabled monitoring to ensure scale is ethically implemented.

Ancient Inca Fortress Foundation Wall

AI Governance Council & Decision Rights

Establish a cross-functional governance council with a clear charter, defined decision rights (RACI), escalation paths, and a predictable cadence so approvals are fast, consistent, and enforceable.

Agentic Use-Case Stage-Gates

Implement risk-based stage-gates that require the right evidence before launch and define “human-on-the-loop” checkpoints to ensure autonomous actions stay within approved boundaries.

Vendor + Contract Governance for AI

Standardize third-party assessments and contract requirements (auditability, incident notification, data handling, control evidence) so vendor-powered AI meets your governance expectations beyond a compliance checklist.

AI Inventory & Risk Registry

Create a single source of truth for every AI/agent system, its owner, autonomy level, dependencies, and risks, so leaders can prioritize, control exposure, and govern what actually exists.

Controls for Trust

Embed practical controls, identity/attribution, logging and monitoring, fail-safes, and ongoing evaluation, so agent behavior is traceable, auditable, and safe in production.



Knowledge Base

Leverage our relationships with large established AI leaders as well as agility and speed focused companies.

How Boards and PMOs Work Together to Govern Agentic AI

Agentic AI changes the governance equation because the system doesn’t just recommend, they act and re-act. That means “AI governance” only works when it connects enterprise direction (Board/C‑suite) to repeatable delivery controls (PMO/TMO) and day‑to‑day operational ownership (Tech + Operations). This section is the shared blueprint: who decides what, how it gets implemented, and how assurance is sustained after go‑live.


AI Governance Accountability Model

Tier

Group

Core Responsibilities

Tier 1: Strategy & Oversight

Board / Audit

Sets overall risk appetite and approves the organizational operating model.

Tier 2: Decision Rights

Exec Sponsors

Defines accountability, manages funding, and ensures cross-functional governance.

Tier 3: Operationalization

AI Council

Manages intake, assigns risk tiers, and collects audit-ready evidence.

Tier 4: Execution & Assurance

Tech / Ops

Builds, deploys, and monitors agentic systems.

The Continuous Feedback Loop

The framework is not a one-way path; it is reinforced by a data-driven cycle: 


  • Input: Metrics and audit results from Execution (Tier 4).


  • Action: Used by the AI Council (Tier 3) to update controls and prioritize initiatives.



  • Outcome: Ensures alignment with the Strategy (Tier 1) while maintaining safety. 



Key Structural Elements

  • Board-Level Responsibility: Effective governance starts at the top, where boards must understand who "owns" the AI strategy and ensure a consistent accountability model.
  • Cross-Functional AI Council: This central body is critical for aligning AI strategy with corporate vision and identifying potential risks.
  • Operational Focus: For agentic systems, governance moves beyond high-level principles to include concrete practices like upfront risk assessment, technical controls, and continuous monitoring.
  • Human-in-the-Loop: High-risk agentic systems require human oversight to manage decisions that have significant probability or severity of harm.

Strategic Alignment

This hierarchical approach transforms abstract ethical principles into everyday practices. By assigning clear ownership at every level, from executive sponsors to technical teams, organizations can avoid fragmented accountability and move faster without increasing unmanaged risk.