01
Maturity assessment
Governance and controls assessment across three areas.
- ISO/IEC 42001: AI management system.
- NIST AI RMF: Govern, Map, Measure, and Manage.
- Google SAIF: risks and technical controls.
AI Governance · Vultus
AI governance for GenAI and vibe coding.
Understand how AI is used in your company. Connect governance, risk management, and technical validation to guide next steps.
Using AI without governance stops being a technical issue and becomes business risk.
Start with a preliminary 15-question assessment.
Your next decision
Before the roadmap, understand your starting point.
Your company already uses AI. How about assessing its maturity to govern that use?
Answer the 15 questions in our preliminary AI Governance assessment and identify where to focus your next steps.
15 questions · 4 areas
An initial look at four areas
- Governance and responsibilities.
- Processes and controls.
- Technology and risk management.
- People and organizational readiness.
At the end, receive a preliminary view of maturity, areas requiring attention, and an initial improvement roadmap.
A connected journey
Four steps to establish AI Governance.
02
Current AI risks
Adversarial investigation to validate controls in practice.
- Adversarial assessment and AI pentesting.
- Prompt injection, jailbreaks, and tool misuse.
- Risk catalog prioritized by impact.
03
Consolidation and roadmap
From assessment to a prioritized improvement plan.
- Consolidated gaps.
- Quick wins and foundational initiatives.
- Roadmap with priorities and owners.
04
AI governance
Action plan execution and continuous improvement.
- Policies, roles, and governance routines.
- Addressing identified gaps.
- Indicators and progress tracking.
Visibility before control
The risk of ungoverned AI use is already measurable.
GenAI and vibe coding are already running in your company. Do you know how they are being used?
For organizations developing AI applications and using GenAI models, a lack of visibility obscures which tools are in use, which data leaves the perimeter, and which agents are already making decisions on their own.
78%
AI brought in by users themselves
Among AI users surveyed in 2024, 78% brought their own AI tools to work, a practice known as BYOAI.
Microsoft and LinkedIn · Work Trend Index 2024 ↗US$ 4.88 million
Financial impact of incidents
Global average cost of a data breach in IBM's 2024 study. The indicator covers breaches overall, not just AI-related incidents.
IBM · Cost of a Data Breach Report 2024 ↗27.4%
Sensitive data sent to AI
This was the proportion of sensitive corporate data entered into AI tools in the sample monitored by Cyberhaven in March 2024.
Cyberhaven Labs · AI Adoption & Risk Report 2024 (PDF) ↗From technology to business
AI risk affects operations, data, and reputation.
Ungoverned AI use can expand known exposures and create new attack paths.
Decisions, permissions, and integrations must be assessed in the context of who uses AI, what data it accesses, and what it can execute.
- Financial fraud and improper authorization.
- Data extortion and ransomware.
- Leaks of sensitive data or intellectual property.
- Unauthorized actions with operational impact.
- Destruction or tampering of data and models.
- Unavailability of AI services and systems.
- Harmful outputs with legal, regulatory, or reputational consequences.
Evidence-based governance
From exposure to methodology: what AI Governance proposes.
Exposure
Memory and data leakage
Models, knowledge bases, and integrations can expose sensitive data when their controls fail.
Method
Maturity assessment
Governance and controls assessment supported by ISO/IEC 42001, NIST AI RMF, and Google SAIF.
Exposure
Autonomy amplifies impact
Agents take actions and access tools. Errors and excessive permissions can spread through integrations.
Method
AI Risks
Mapping use cases, assets, and threat scenarios, with prioritization based on likelihood and business impact.
Exposure
Controls not yet validated
Policies and configurations must be checked against the actual behavior of applications and agents.
Method
Adversarial validation
AI-focused pentesting and red teaming to investigate attack paths and produce evidence of control effectiveness.
Strategy and technical depth
Govern, test, and improve throughout the same journey.
Vultus connects risk management with offensive validation to turn assessment findings into decisions and action.
Also explore Ares autonomous AI pentesting →Strategy + technical depth
AI risk translated into decisions, with business insight and technical investigation.
Governance + validation
We assess the governance structure and test controls to guide improvement.
Real risk
Prioritization by impact and context: each organization's data, permissions, integrations, and processes.
Recognized references
ISO/IEC 42001, NIST AI RMF, and Google SAIF support the assessment of management, risks, and technical controls.
From analysis to execution
Roadmap, quick wins, and follow-up to sustain continuous improvement.
Vultus experience
Technology changes. Risk management experience remains essential.
Start with visibility
Take the first step toward improving your AI Governance.
Take the maturity assessment and turn your questions into a starting point for progress. To deepen the diagnosis and structure your next steps, speak with Vultus specialists.