title: “Governance Implementation” description: “Establish the organizational governance foundation required to implement and operate the AIGO Framework.”
Governance Implementation
Governance implementation establishes the organizational foundation required to apply the AIGO Framework consistently. Before individual AI systems can be governed effectively, an organization should establish who has authority, what is in scope, how decisions are made, what records are maintained, and how governance activities are monitored and assured. AIGO therefore separates organizational governance from AI-system governance, while connecting the two through defined roles, processes, records, controls, and evidence.1. Establish governance ownership
The organization should assign clear ownership for the AIGO governance capability. Governance ownership should define: * who is accountable for AI governance * who has authority to make governance decisions * who operates governance processes * who owns individual AI systems * who owns AI-related risks * who implements controls * who performs independent or assurance activities * who approves exceptions and residual risk Governance responsibilities should be documented rather than relying on informal or assumed authority. See the Governance Roles documentation for the AIGO role model.2. Define the governance scope
The organization should establish the scope within which AIGO will operate. The scope may define: * organizational entities * business units * geographic jurisdictions * AI systems * AI-enabled products and services * development activities * acquisition and procurement * third-party AI services * internally developed models * deployed AI applications * supporting AI infrastructure * lifecycle stages covered by governance The scope should be sufficiently precise to determine which AI systems and activities are subject to AIGO governance. The scope should also identify exclusions and explain the basis for those exclusions where appropriate.3. Establish governance policies
Organizations should establish policies that define the organization’s expectations for responsible AI governance. Policies may address: * AI governance objectives * accountability * risk management * acceptable AI use * prohibited or restricted uses * human oversight * transparency * privacy and data governance * security * monitoring * incident management * change management * documentation * evidence retention * assurance * risk acceptance * retirement AIGO provides the framework structure for these governance activities, but organizations should adapt policies to their own legal, regulatory, contractual, operational, and risk environment.4. Define governance roles and decision authority
Roles should be mapped to actual organizational responsibilities. The organization should determine:
The exact organizational structure may vary.
AIGO does not require every organization to use the same job titles or reporting structure. What matters is that accountability, authority, responsibility, and independence are clearly established.
5. Establish the governance lifecycle
Governance implementation should connect organizational governance to the AI system lifecycle. At a high level, an organization should be able to move from: Governance scope → AI system registration → system profiling → classification → risk assessment → control selection → control assessment → approval → operation → monitoring → change and incident management → assurance → improvement → retirement Not every AI system will require identical activities or levels of rigor. The applicable governance activities should be determined according to the system’s characteristics, classification, risks, applicable requirements, and organizational policies. See the AI Governance Lifecycle documentation for the framework lifecycle model.6. Establish AI system registration
Organizations should maintain a controlled inventory of AI systems within the governance scope. Registration should provide enough information to identify and govern each system. Typical information includes: * system identity * system owner * organizational owner * purpose * business function * deployment status * lifecycle status * technology or model characteristics * relevant data * users and affected parties * suppliers or third parties * applicable jurisdictions * initial classification * governance status The AI system registration process provides the starting point for system-level governance. See AI System Registration for the operational implementation process.7. Establish classification
The organization should establish a consistent method for determining the governance treatment applicable to each AI system. Classification may consider factors such as: * intended purpose * affected persons * decision impact * autonomy * sensitivity of data * potential harm * regulatory obligations * operational criticality * human oversight * deployment context Classification should determine the level and type of governance activities required. See Classification for the corresponding implementation process.8. Establish risk management
The organization should establish an AI risk-management process that connects identified risks to owners, controls, evidence, decisions, and monitoring. A risk-management process should provide for: 1. risk identification 2. risk analysis 3. risk evaluation 4. risk treatment 5. control selection 6. residual-risk assessment 7. risk acceptance where required 8. ongoing monitoring 9. reassessment when circumstances change AI risk management should operate throughout the lifecycle rather than only during initial system approval. See Risk Assessment and AI Risk Management.9. Establish control governance
Controls should be selected and implemented in response to identified governance requirements and risks. Control governance should establish: * control ownership * control objectives * implementation responsibilities * applicability * implementation status * supporting evidence * assessment criteria * exceptions * remediation * reassessment frequency Controls should be traceable to the systems, risks, requirements, and evidence they address. See Controls and Control Assessment.10. Establish approval and decision mechanisms
The organization should define how AI systems receive governance approval. Approval mechanisms should establish: * approval criteria * required evidence * approval authority * decision outcomes * conditions of approval * exceptions * residual-risk decisions * approval records * review and expiry conditions where applicable Approval should be based on documented governance information rather than an informal decision alone. See Approval.11. Establish evidence and records management
AIGO implementation should produce auditable governance records. Evidence may include: * system registrations * system profiles * classifications * risk assessments * control assessments * approval decisions * monitoring results * incident records * change records * assurance records * management reviews * improvement records * retirement records Records should be attributable to the relevant AI system, governance activity, owner, and lifecycle stage. The AIGO schemas provide machine-readable structures for many of these governance records. See Schemas for the structured representation of governance information.12. Establish monitoring and operational oversight
Governance should continue after an AI system has been approved. Organizations should define how they monitor: * system performance * relevant risk indicators * control effectiveness * incidents * changes * emerging risks * compliance or governance obligations * evidence status * approval conditions Monitoring results should feed back into risk management, assurance, and continuous improvement. See Monitoring.13. Establish change and incident management
AI systems should remain subject to governance when circumstances change. The organization should define processes for: * material system changes * model changes * data changes * changes in intended purpose * changes in deployment context * changes in applicable requirements * significant incidents * control failures * emerging risks Changes or incidents may require reassessment, additional controls, renewed approval, escalation, or other governance action. See Change Management and Incident Management.14. Establish assurance
The organization should establish assurance mechanisms to determine whether governance arrangements are operating as intended. Assurance may examine: * governance implementation * system-level governance * risk-management effectiveness * control implementation * evidence completeness * monitoring * approval conditions * incident handling * change management * ongoing conformity with organizational requirements Assurance should provide information to governance decision makers and support continual improvement. See Assurance.15. Establish risk acceptance
Where residual risk remains after treatment, the organization should define who may accept that risk and under what conditions. Risk acceptance should be: * explicitly authorized * documented * linked to the relevant risk * supported by an assessment * time-bounded where appropriate * subject to review * reassessed when circumstances change Risk acceptance should not be treated as a substitute for reasonable risk treatment. See Risk Acceptance.16. Establish continual improvement
AIGO governance should operate as a continual-improvement capability. Organizations should periodically review: * governance effectiveness * AI system inventory * risk trends * control performance * incidents * assurance findings * regulatory or contractual changes * lessons learned * emerging AI risks * stakeholder feedback Improvement actions should be documented, assigned, tracked, and evaluated. See Continuous Improvement.17. Connect organizational governance to AI systems
The most important implementation principle is that organizational governance should remain connected to individual AI systems. A practical traceability chain is: Organization → Governance → AI System → Classification → Risk → Control → Evidence → Assessment → Approval → Monitoring → Assurance → Improvement This allows an organization to answer questions such as: * Which AI systems are governed? * Who owns each system? * Why was a system classified in a particular way? * Which risks were identified? * Which controls address those risks? * What evidence demonstrates implementation? * Who assessed the controls? * Who approved the system? * What is being monitored? * What incidents or changes have occurred? * What assurance has been performed? * What improvements are required? The machine-readable AIGO architecture is intended to support these relationships in a structured form.18. Recommended implementation sequence
Organizations implementing AIGO for the first time can use the following sequence: 1. Establish governance ownership. 2. Define organizational scope. 3. Establish AI governance policies. 4. Assign governance roles and decision authority. 5. Establish the AI governance lifecycle. 6. Create the AI system inventory. 7. Register AI systems. 8. Create AI system profiles. 9. Classify AI systems. 10. Assess AI risks. 11. Determine applicable controls. 12. Implement controls. 13. Assess control effectiveness. 14. Collect and maintain evidence. 15. Obtain governance approval. 16. Operate and monitor AI systems. 17. Manage incidents and changes. 18. Perform assurance. 19. Manage residual-risk acceptance where applicable. 20. Conduct management review and continual improvement. 21. Retire AI systems when appropriate. This sequence is a recommended implementation path rather than a requirement that every organization follow exactly the same order.19. Implementation artifacts
A practical AIGO implementation should produce a connected set of governance artifacts. At minimum, organizations should consider establishing: * AI governance record * AI system registration * AI system profile * AI classification record * AI risk assessment * control assessment * approval record * evidence records * monitoring records * incident records * change-management records * assurance records * risk-acceptance records where applicable * management-review records * continuous-improvement records * retirement records The corresponding AIGO templates and schemas can be used as starting points for implementing these records.20. Using AIGO with existing governance systems
AIGO does not require an organization to replace its existing governance, risk, compliance, security, privacy, quality, or enterprise-risk processes. Instead, organizations can integrate AIGO into existing operating models. For example: * enterprise risk management can provide risk governance * information security can provide security controls * privacy governance can provide privacy controls * compliance functions can provide regulatory interpretation * internal audit can provide independent assurance * existing change-management systems can govern AI system changes * existing incident-management systems can record AI incidents * existing document-management systems can maintain governance evidence The AIGO model should be adapted to the organization’s existing governance architecture while preserving traceability and accountability.21. Implementation maturity
Organizations do not need to implement every capability at maximum maturity immediately. AIGO implementation can progress from establishing basic governance foundations toward increasingly integrated and automated governance capabilities. A maturity progression may include: Establish → Document → Operate → Measure → Assure → Improve → Automate The appropriate maturity target depends on organizational size, AI system complexity, risk exposure, applicable requirements, and governance objectives. See Maturity for the AIGO maturity model.22. Machine-readable implementation
AIGO can also be implemented using machine-readable governance records and automated validation. The repository includes machine-readable components for: * governed objects * relationships * rules * evaluation * orchestration * validation * evidence and traceability These capabilities can support governance platforms, registries, workflow systems, GRC integrations, AI inventories, control-management systems, and automated governance checks. Automation should support governance decisions rather than obscure or replace organizational accountability.23. Implementation boundary
Implementing AIGO does not by itself establish: * legal compliance * regulatory conformity * certification * accreditation * approval by a regulator * absence of AI-related risk Organizations remain responsible for determining the requirements applicable to their circumstances and for obtaining appropriate legal, regulatory, technical, and assurance advice. AIGO provides a governance framework that organizations can adapt and implement to manage those responsibilities systematically.Next steps
After establishing the organizational governance foundation, continue with: 1. AI System Registration 2. AI System Profiles 3. Classification 4. Risk Assessment 5. Control Assessment 6. Approval 7. Monitoring 8. Assurance 9. Continuous Improvement For detailed operational instructions, use the corresponding procedures, templates, and examples in the Guidance section.Canonical source
The canonical implementation guidance for this page is maintained in:guidance/01-implementation/01-AIGO-Implementation-Guide-v0.1.md
The governance-specific implementation material is maintained in:
guidance/01-implementation/02-AIGO-Governance-Implementation-v0.1.md
This documentation page presents the implementation material as a practical entry point for organizations adopting AIGO.