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AI Portfolio Visibility
Understanding how many AI systems exist across the enterprise.
The AI Governance Maturity Model helps organizations understand how prepared they are for the EU AI Act and responsible AI practices.
Complete this 10-minute assessment to understand your AI governance maturity.
AI adoption is accelerating across enterprises, but governance often lags behind. Without proper governance, organizations face growing risks and limited visibility into their AI systems.
Regulatory
Exposure
Organizations deploying AI without proper governance frameworks may face increasing regulatory pressure and compliance challenges.
Operational
Risks
Lack of structured AI oversight can lead to inefficient processes, unmanaged risks, and inconsistent decision-making.
Limited AI
Transparency
Without clear governance, organizations often struggle to maintain visibility and accountability across AI systems.
A Structured Path Forward
The AI Governance Maturity Model provides a structured way to evaluate governance capabilities and plan improvements.
Organizations typically progress through five stages of AI governance maturity—from early experimentation to fully operational governance embedded across the enterprise
AI systems are being used without formal governance. There is little visibility into where AI is deployed.
Organizations recognize the need for governance and begin creating policies, inventories, and basic oversight.
Governance frameworks and responsibilities are formally defined, but execution across the organization is inconsistent.
Governance is embedded into the AI lifecycle. Organizations maintain inventories, risk classification processes, and human oversight.
AI governance is fully integrated into enterprise strategy with continuous monitoring, executive oversight, and regulatory readiness.
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Understanding how many AI systems exist across the enterprise.
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Identifying governance accountability.
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Maintaining a centralized registry of AI systems.
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Determining which systems fall under high-risk classifications.
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Formal policies governing the AI lifecycle.
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Controls ensuring datasets are accurate and representative.
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Mechanisms allowing humans to review and intervene in AI decisions.
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Ability to demonstrate regulatory compliance.
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Leadership oversight of AI risks.
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Ability to produce evidence of compliance.
The assessment takes approximately 5–10 minutes to complete and provides immediate insights into your organization’s AI governance maturity.
Use the results to strengthen governance, reduce regulatory risk, and scale AI responsibly.
Your AI Governance Maturity Score
Your Maturity Level (Ad Hoc to Optimized)
A Gap Analysis highlighting governance weaknesses
Recommended next steps to improve governance maturity
Apply approved changes, update baselines, and reset the monitoring loop.
AI audit software captures an immutable entry with evidence, context, and reviewer notes for compliance.
Evaluate flagged issues to determine severity, scope, and whether regulatory reporting or remediation is required.
Detect deviations and trigger prioritized alerts when thresholds or drift detectors are breached.
Collect telemetry, performance metrics, and logs continuously from deployed models and pipelines.
Perform final approvals, lock the workflow state, and output the conformity decision trail for internal records or notified-body review.
Run configured readiness checks and reviews to confirm every checkpoint meets the criteria before advancing.
Execute the assigned tasks (testing, verification, and process steps) while recording outcome metadata and timestamps.
Allocate owners, deadlines, and required roles for each task so nothing remains unclaimed.
Map the system’s intended use and risk profile, then select the required conformity route and task set.
Produce a finalized technical file that is compliant, version-controlled, and ready for internal review or submission.
Perform completeness checks and ensure each section aligns with AI Act documentation requirements before finalizing.
Associate datasets, test results, and design files with their relevant sections to maintain a clear, auditable record.
Collect all necessary system information, design artifacts, and supporting evidence to prepare for Annex IV technical documentation.
Continuously update classifications and inventory entries as models evolve or new AI systems are introduced, ensuring enterprise-wide visibility.
Connect models to datasets, use cases, and previous assessments, maintaining a fully auditable history of changes.
Automatically evaluate each system against EU AI Act criteria and assign the appropriate risk tier among the four of them.
Add AI models and datasets into the centralized AI use case inventory with key metadata and ownership details.
Maintain audit integrity with real-time tracking, immutable logs, and compliance dashboards. CompliAI enables continuous monitoring of every AI system, helping organizations stay compliant as regulations evolve.
Simplify your path to CE marking and regulatory conformity. Follow built-in workflows that outline every requirement, track progress, and generate draft declarations of conformity in line with EU standards.
Automatically generate, organize, and update all required documentation in structured formats. CompliAI links evidence, datasets, and audit records to build comprehensive technical files, ensuring consistency and audit readiness.
Map every AI system across your organization and determine its regulatory risk level through guided assessments aligned with the EU AI Act. The platform centralizes system ownership, data, and accountability so that you can have full visibility from day one.
