Services
Comprehensive AI governance solutions that bridge regulatory requirements with operational reality.
AI Governance Frameworks and Practices
Build the structure, accountability, and controls that make AI governance real.
Responsible AI demands clear governance. This service turns governance from aspiration into operational practice.
What's Delivered:
- Governance model design: Charters and procedures aligned with ISO/IEC 42001
- Decision frameworks: Stage-gate criteria and approval workflows
- Accountability structures: Clear roles for AI owners and compliance leads
- Monitoring and reporting: KPIs, dashboards, and audit trails
- Policies and codes: Enforceable standards for teams and vendors
Who This Is For:
- Businesses formalizing AI operations
- Public agencies with regulatory and oversight duties
- Risk and compliance officers establishing AI governance
- Organizations preparing for regulatory audits
Bridging the Gap Between AI Regulation and Operationalization
From compliance to operational reality — across the entire AI lifecycle.
Navigating AI regulation isn't just about ticking boxes. It's about embedding compliance into every phase of your AI system.
What's Delivered:
- Full lifecycle mapping: Regulatory requirements translated into actions aligned with ISO/IEC standards and NIST RMF
- Role-based implementation playbooks: Tailored guidance for developers, compliance officers, and operations teams
- Continuous compliance integration: Requirements embedded into existing workflows
- Evidence and documentation frameworks: Specific templates aligned with policy instruments such as the AI ACT, Council of Europe Framework Convention, UNESCO Recommendation on the Ethics of AI and other relevant guidance
Who This Is For:
- AI developers and tech companies launching AI products
- Businesses operationalizing AI across business units
- Organizations demonstrating lifecycle compliance to customers and regulatory bodies
Risk and Impact Assessment in the Design and Use of AI Systems
Identify, measure, and mitigate AI risks before they become problems.
Every AI system carries potential risks. Understanding and managing these risks is essential.
What's Delivered:
- Comprehensive risk profiling: Context scoping following UE AI Act FRAIA, ISO/IEC 42005 and 23894, NIST AI RMF, Council of Europe HUDERIA methodology, OECD AI Principles
- Stakeholder impact mapping: Identification of who is affected and what safeguards are needed
- Pre-alignment and readiness checks: Data quality, human oversight design, capability gaps
- Control plans: Risk mitigation strategies and go/no-go decision frameworks
Who This Is For:
- SMEs adopting vendor AI tools
- Public agencies piloting AI-driven decision support
- Businesses launching high-risk AI use cases
- Organizations demonstrating due diligence to regulators and boards
Change and Process Management for AI Adoption
Redesign your processes to unlock AI value while embedding compliance.
Success requires redesigning processes, redefining roles, and managing the human side of change.
What's Delivered:
- Process reengineering: As-Is and To-Be mapping with compliance checkpoints
- Change readiness planning: Stakeholder engagement and training programs
- RACI redesign: Clear accountability for AI oversight and decision-making
- Reinforcement mechanisms: Ongoing monitoring and feedback loops
Who This Is For:
- Operations leaders integrating AI into core processes
- Private and public organizations adopting AI systems
- Teams delivering productivity gains and regulatory compliance
