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AI Governance

From AI inventory to governed AI decisions.

Continuum connects AI systems to classification, applicable obligations, controls, evidence, approvals, ownership, and monitoring so governance decisions can be reviewed.

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AI change, evidence, controls, incidents, and human approval remain connected in one governance workflow.

Continuum AI assists work inside the platform, grounded in connected operating context. AI Governance governs the AI systems an organization operates or relies on.

01 / AI systems in context

An AI inventory needs more than names.

A model or provider name does not make an AI system governable. It becomes governable when the inventory captures use case, owner, data exposure, classification, approval state, and review history.

AI SystemNot defined by a model name alone
Business useOwnerData / process contextProvider / modelRisk / classificationApproval state

02 / Core governance model

The governed AI lifecycle.

An AI system becomes governable when its classification context is established, making it possible to determine which obligations, controls, and evidence apply and to record a governance decision that remains reviewable.

AI SystemThe governed system under review.
ClassificationUse case and context that determine what applies.
OwnerBusiness processChange stateIncident / finding
ObligationsWhat applies, given the classification.
Controls & evidenceThe controls and evidence that address the applicable obligations.
Governance decisionWhere the system stands, with context.

03 / Obligations and controls

Applicable obligations follow the AI system's context.

Not every AI system is subject to the same governance obligations. What applies depends on the system's classification and use context. ISO 42001 and EU AI Act requirements are considered where applicable, not applied uniformly by default. Controls and evidence stay linked to the AI system they apply to.

Applicable where relevantScoped to use caseClassification informs applicabilityNot uniform across AI systems
AI SystemApplicable obligationControl & evidence

04 / Governance readiness

How governance readiness builds.

  1. InventoriedThe AI system is recorded for governance.
  2. ClassifiedIts use case and applicable governance context are defined.
  3. ControlledControls and supporting evidence are connected and tracked.
  4. GovernedReview, approval state, and decision history are recorded.

Readiness reflects the classification, evidence, and approvals connected to this AI system, not a compliance percentage or automated score.

05 / Product view

See AI systems, approvals, incidents, and controls in one governance view.

AI change, evidence, controls, incidents, and human approval remain connected in one governance workflow.

06 / Change, incident, and review context

Monitoring matters because AI system context changes.

An AI system may need review when its use case, model or provider, controls, evidence, incidents, or monitoring signals change. These changes may trigger review; they do not automatically approve or reclassify the system.

Governance recordA reason to review, not an automatic decision
Model / provider changeUse-case changeControl / evidence changeIncidentRed-team findingApproval / review

07 / Ownership and approvals

Governance decisions remain accountable.

Classification, controls, and change events inform the decision. The decision itself belongs to an accountable owner, not to the AI system, and not to an automated process.

Change / findingA reason to look again.
OwnerAccountable for the governance decision.
Governance decisionReviewed and recorded by an accountable owner.
Decision history & escalationWhat was decided, when, and where it escalates.

08 / Related workspaces

AI governance connects across the platform.

Explore how AI governance connects to the other Continuum workspaces.

FrameworksCompliance AssuranceAudit & EvidenceSecurity RiskContinuum AI

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Govern AI systems from inventory through approval and monitoring.

Request a focused briefing to see how Continuum connects AI systems, classification, obligations, controls, evidence, ownership, approvals, and monitoring.

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