No AI deployment without proper sign-off
Configure multi-step approval workflows for use cases and projects with flexible approver requirements and automatic framework creation.
The challenge
AI deployments need governance gates—not just good intentions
Deploying AI without proper review creates risk. Technical teams may miss compliance requirements. Legal may not see privacy implications. Leadership may be unaware of reputational exposure. Without formal approval workflows, AI systems can go live without the oversight that regulations increasingly require.
No formal gate between AI development and deployment
Unclear who needs to approve before a system goes live
Approvals tracked informally via email or meetings with no audit trail
Different stakeholders (technical, legal, executive) need to review at different stages
Compliance frameworks should only be created after proper approval
Benefits
Why use Approval workflows?
Key advantages for your AI governance program
Require sign-off before AI systems go live
Configure who must approve at each stage
Choose between any-approver or all-approvers requirements
Auto-create compliance frameworks upon final approval
Capabilities
What you can do
Core functionality of Approval workflows
Multi-step workflows
Define sequential approval stages—technical review, legal review, executive sign-off—each with its own approvers.
Flexible approval requirements
Per-step configuration: require all assigned approvers or allow any single approver to advance the workflow.
Request lifecycle management
Track requests through Pending → Approved/Rejected/Withdrawn with complete timeline and comments.
Framework auto-creation
When a use case is approved, automatically create linked compliance frameworks (EU AI Act, ISO 42001, etc.).
Enterprise example
How an organization formalized AI deployment governance
See how organizations use this capability in practice
The challenge
An organization had no formal process for approving AI deployments. Technical teams would build systems, get informal verbal approval from their managers, and push to production. When regulators asked about the approval process for a specific AI system, the organization couldn't demonstrate that appropriate stakeholders had reviewed it.
The solution
They implemented a three-step approval workflow: Technical Review (any engineering lead can approve), Compliance Review (requires both legal and compliance officers), and Executive Sign-off (requires CISO approval). Each use case now goes through this workflow before compliance frameworks are created.
The outcome
Every AI deployment now has documented approval from technical, compliance, and executive stakeholders. The organization can show regulators exactly who approved each system, when, and with what comments. Compliance frameworks are only created after proper review, ensuring no system enters the governance process prematurely.
Why VerifyWise
Approval gates that scale with your organization
What makes our approach different
Sequential multi-step workflows
Define stages like Technical Review → Legal Review → Executive Approval. Each step must complete before the next begins.
Flexible approval requirements
For each step, choose: require all assigned approvers (unanimous), or allow any single approver to advance. Match your organization's decision-making patterns.
Complete audit trail
Every approval, rejection, and comment is logged with timestamps and user attribution. When auditors ask who approved what, you have the answer.
Automatic framework creation
When a use case receives final approval, linked compliance frameworks (EU AI Act, ISO 42001, etc.) are automatically created with all controls and requirements.
Regulatory context
Approval processes demonstrate governance maturity
AI regulations emphasize organizational accountability and proper oversight. Formal approval workflows demonstrate that AI deployments receive appropriate review before going live—a key indicator of governance maturity.
Article 9 requires risk management procedures and Article 17 requires quality management systems. Formal approval workflows demonstrate these systems are in place.
Clause 8.1 requires organizations to plan, implement, and control processes needed to meet AI management system requirements. Approval workflows are a key control mechanism.
Board-level AI oversight increasingly requires demonstrable approval processes. Workflow audit trails provide evidence of proper governance.
Technical details
How it works
Implementation details and technical capabilities
4 request statuses: Pending, Approved, Rejected, Withdrawn for complete lifecycle tracking
3 step statuses: Pending, Completed, Rejected for granular step-level visibility
2 entity types supported: Use cases and projects can both use approval workflows
Per-step approver configuration: Assign specific users to each workflow step
Requires-all vs any-approver: Configure whether one approval or unanimous approval advances the step
Entity data snapshot: Captures use case/project state at request time for audit purposes
Automatic framework creation: Upon final approval, pending frameworks are created with all controls
Supported frameworks
Integrations
FAQ
Common questions
Frequently asked questions about Approval workflows
More from Operate
Related capabilities
Other features in the Operate pillar
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See how VerifyWise can help you govern AI with confidence.