What Is Artificial Intelligence Governance? Definition, the 6 Components, and What It Is Not
By Pedro Sonda, dooop
Artificial intelligence governance is the set of decisions, roles, rules, and controls that ensures a company uses AI aligned with its objectives, with known and acceptable risks, and with a person accountable for each use. It has six components: principles and risk appetite, roles and responsibilities, policies, inventory with risk classification, controls (such as human review and data access), and monitoring with incident handling. AI governance is not a document nor a committee: it is a management system that must operate daily, with intensity proportional to the risk of each use.
Updated in October 2026.
Why the Topic Has Gained Urgency
| Data | Source |
|---|---|
| 63% of organizations that suffered data breaches did not have an AI governance policy or were still developing one; only 37% have policies to manage AI or detect shadow AI (unauthorized use) | IBM, 2025 |
| Only 40% of employees say there is policy or guidance on generative AI at work; nearly half admit to using AI in ways that violate company rules | KPMG and University of Melbourne, 2025 |
| In Brazil, Bill 2338/2023, approved by the Senate in December 2024 and under consideration in the Chamber, proposes classification of systems by risk, with prohibition of excessive risk systems and additional obligations for high-risk ones | Chamber of Deputies |
Interpretation: AI use is already widespread, internal rules are not, and regulation is moving toward requiring proportional risk management. Governance has ceased to be optional for companies that use AI significantly.
dooop Framework: The 6 Components
| Component | Question It Answers | Typical Deliverable |
|---|---|---|
| 1. Principles and Risk Appetite | What does the company accept and not accept to do with AI? | Short principles; list of prohibited uses; risk limits approved by leadership |
| 2. Roles and Responsibilities | Who decides, who operates, who reviews, who supervises? | Governance lead; owners of each use; decision committee or forum |
| 3. Policies | What are the rules for employees, systems, and suppliers? | Corporate policy; one-page usage policy; supplier criteria |
| 4. Inventory and Risk Classification | What AI do we use, with what data, at what risk level? | Updated inventory; classification by levels |
| 5. Controls | What safeguards operate at each risk level? | Data access, human review, testing, logs, agent limits |
| 6. Monitoring and Incidents | How do we know it is working and what do we do when it fails? | Indicators, audits, incident channel and plan, periodic review |
What AI Governance Is Not
| Not | Why |
|---|---|
| A Document | A policy without accountability, inventory, and controls tends to remain on paper |
| Only Compliance | It also sets priorities and enables safe use, not just prohibits |
| Only Data Governance | It includes decisions, people, suppliers, and system behavior, beyond data |
| Responsibility Only of IT | It involves leadership, business areas, legal, risk, and HR |
| The Same for All Uses | A text summary and a credit decision require very different controls |
Recognized References
- NIST AI Risk Management Framework: organizes AI risk management into four functions (govern, map, measure, and manage).
- ISO/IEC 42001: AI management system standard with auditable requirements.
- LGPD: already applies to personal data used in AI; see AI and LGPD: what a company needs to assess.
These references help structure governance; the final design must fit the size and risk of each company.
Where to Start
- Appoint a responsible person; see Who should be responsible for artificial intelligence within the company?.
- Publish a minimal usage policy for employees.
- Build the inventory of current uses.
- Classify uses by risk level; see How to define risk levels for different AI uses.
- Apply proportional controls and review quarterly.
To assess existing governance, use the AI governance executive checklist.
What to Do Now
- Check which of the 6 components already exist in your company, with evidence.
- Choose the two most absent for the next 90 days.
- Involve leadership in defining principles and prohibited uses.
To structure AI governance proportionally and operably, explore dooop's AI Governance offering and see what an AI governance consultancy delivers.
Frequently Asked Questions
Does AI governance slow down innovation? Poorly designed, yes. Well designed, it accelerates: clear rules and quick approvals for low-risk uses free teams to experiment. See AI Governance without bureaucracy.
Do small and medium enterprises need AI governance? They need the six components in a simple version: one responsible person, a one-page rule set, an inventory spreadsheet, and controls on the few higher-risk uses.
What is the difference between AI governance and AI risk management? Risk management is part of governance. Governance also defines principles, priorities, roles, and how decisions are made.
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About dooop
dooop is a consultancy based in Caxias do Sul (RS) that prepares leaders and organizations to transform artificial intelligence into business capability through strategy, governance, and training.