AI GOVERNANCE SERVICES
AI Governance Integration
Service Overview
Integrating AI governance early in project management is crucial for successful implementation. Responsible AI governance facilitates stakeholder alignment and ensures compliance with regulations such as the EU AI Act, GDPR and ethical AI principles outlined by the OECD and NIST AI RMF.
By embedding a structured AI governance framework from the outset and throughout the project lifecycle, organizations ensure that AI systems are developed, integrated, and deployed responsibly and in compliance with emerging laws and policies. following the global best practices, maximizes ROI, fosters trust and accountability, and secures long-term competitive advantage.
Our Approach
This high-level plan follows the NIST AI RMF and shall be customized to each client’s AI use cases, risk profile, and compliance needs. Every phase is adaptable to the organization’s structure and objectives.
Phase 1: Preparation and Assessment
Laying the groundwork for AI governance starts with a clear understanding of the organization’s AI landscape, regulatory obligations, and strategic goals. This may involve assessing current AI use cases, evaluating governance frameworks, identifying compliance requirements, and defining risk thresholds.
Phase 2: Governance and Leadership
Establish governance roles, forming oversight committees, aligning AI policies with enterprise risk management, and securing leadership buy-in to drive responsible AI adoption.
Phase 3: Risk Identification and Mapping
Conduct AI system inventories, analyze risks related to bias, security, and transparency, and assess external dependencies, such as third-party AI models or datasets.
Phase 4: Risk Measurement and Performance Evaluation
Define performance metrics for accuracy, fairness, and security, implementing validation and audit processes, run stress tests, and ensure AI explainability for regulatory compliance.
Phase 5: Risk Management, Controls, and Training
Implement incident response plans and integrate AI governance training programs to ensure teams understand ethical AI principles, security measures, and regulatory requirements.
Phase 6: Monitoring, Oversight, and Continuous Improvement
Establish robust monitoring frameworks. regular governance reviews and policy reviews, embed AI risk awareness into corporate culture to maintain compliance and operational resilience.