AI Workflow Governance Diagram

A systems-level governance workflow diagram mapping the lifecycle of an AI system from procurement through decommission. Each stage includes defined governance controls, decision gates, and accountability assignments.

01 Systems Governance Lifecycle Diagram

The diagram below represents the full governance workflow for an AI system entering organizational use. Governance controls are applied at each stage. Decision gates are mandatory checkpoints where a system may proceed, return for remediation, or be rejected.

Stage 1
Intake

              Use Case Submission
              Business unit submits AI use case via standardized intake form. Includes purpose, data types, affected populations, and integration scope.
            

Risk Classification Governance lead assigns risk tier: Critical / High / Medium / Low based on autonomy, data sensitivity, and potential impact.

Stakeholder Assignment Data owner, technical owner, and business sponsor identified and formally assigned. All three required before proceeding.

Intake Complete

Gate 1
Triage

Decision: Proceed to Assessment?

Pass: Full risk classification assigned, proceed Fail: Insufficient info, return to submitter Reject: Use case prohibited by policy, close

Stage 2
Assessment

Vendor Risk Review Third-party AI tools assessed against vendor risk questionnaire: data handling, security certifications, breach history, model documentation.

              AI Impact Assessment
              Structured assessment of potential harms: bias exposure, privacy impact, safety risks, workforce impact, and regulatory exposure.
            

Security Architecture Review CISO team reviews integration design, API access patterns, data flows, and access control configuration against policy requirements.

Legal and Compliance Review Legal reviews for regulatory obligations, IP considerations, data residency requirements, and contractual risk.

Assessment Complete

Gate 2
Approval

Decision: Approved for Deployment?

Pass: All reviews complete, controls confirmed, proceed Conditional: Approved with mandatory mitigations before go-live Reject: Risk exceeds appetite, escalate to executive review

Stage 3
Deployment

Access Provisioning IAM team provisions AI system identity, scopes permissions per approved access tier, configures credential rotation schedule.

              Monitoring Baseline
              Performance, behavior, and security monitoring configured. Alert thresholds set. Anomaly detection activated. Log retention confirmed.
            

Pilot Release System released to limited user group. Feedback loop established. Incident reporting channel activated. Full production gated on pilot outcome.

System Registry Entry AI system formally entered in organizational AI registry with owner, tier, approved use cases, review date, and dependency map.

Production Active

Stage 4
Operations

Continuous Monitoring Automated monitoring of output quality, bias indicators, security events, and API usage. Escalation to owner on threshold breach.

Periodic Review Scheduled review against registry record. Frequency determined by risk tier: Critical (quarterly), High (semi-annual), Medium/Low (annual).

              Incident Management
              AI-specific incident classification, response procedures, and post-incident review. Patterns feed back into risk assessment framework.
            

Change Control Model upgrades, integration changes, and scope expansions trigger reassessment at appropriate gate. No silent changes permitted.

End of Life Trigger

Stage 5
Decommission

Decommission Trigger Initiated by: planned end-of-life, vendor discontinuation, policy conflict, security incident, or governance review outcome.

Access Revocation All credentials and permissions revoked. API keys rotated or deleted. Integration dependencies removed or rerouted.

Data Disposition Data retained, transferred, or deleted per data classification policy and vendor contract terms. Disposition documented.

Registry Closure AI registry entry marked closed. Lessons learned documented. Post-decommission review scheduled for Critical/High tier systems.

Key governance control

Mandatory decision gate

Registry / compliance record

Standard workflow node

02 Stage Summary and Role Accountability

Each stage of the governance lifecycle has defined responsibilities. The table below maps governance activities to organizational roles and NIST AI RMF function alignment.

Stage	Primary Activity	Accountable Roles	NIST AI RMF Function	Key Artifact
Intake	Risk classification, stakeholder assignment, initial scoping	AI Governance Lead Business Sponsor	GOVERN, MAP	Use Case Intake Form
Assessment	Vendor risk, impact assessment, security and legal review	CISO Legal / Compliance Data Owner	MAP, MEASURE	AI Impact Assessment Report
Deployment	Access provisioning, monitoring setup, pilot release	IT / IAM Technical Owner AI Governance Lead	MANAGE	AI Registry Entry
Operations	Monitoring, periodic review, incident management, change control	Technical Owner Security Ops Business Sponsor	MEASURE, MANAGE	Monitoring Reports, Incident Logs
Decommission	Access revocation, data disposition, registry closure	IT / IAM Data Owner AI Governance Lead	MANAGE	Decommission Checklist

Design Note

This diagram represents a governance workflow for systems-level AI adoption. For individual LLM tool use cases or lower-risk deployments, an abbreviated version of this workflow may be appropriate. The governance lead should determine which stages apply based on the system's risk classification.