Challenge
The customer wanted to establish a scalable and compliant AI governance framework aligned to evolving global regulations, including the EU AI Act. However, meeting requirements around lifecycle risk management, technical documentation, data governance, transparency, human oversight, auditability, and post-market monitoring required a structured governance operating model capable of managing high-risk AI systems consistently across the enterprise.
Solution
Through close collaboration between governance, compliance, and digital engineering teams, Tata Technologies helped the customer establish an EU AI Act-aligned AI governance framework designed to operationalize responsible, transparent, and compliant AI adoption across the organization. We implemented a governance operating model with clearly defined roles, RACI structures, approval workflows, and quality management controls to support enterprise-wide AI lifecycle governance.
To strengthen risk visibility and regulatory readiness, we deployed lifecycle-based AI risk assessment mechanisms, risk tiering frameworks, and standardized control libraries aligned to high-risk AI system requirements. We also established corrective action workflows to improve issue resolution, governance responsiveness, and compliance accountability across AI initiatives.
To support auditability and responsible AI practices, we standardized data governance processes and bias mitigation approaches for training, validation, and testing datasets while maintaining comprehensive evidence packs and technical documentation repositories. We further enabled transparency and human oversight playbooks, automated logging capabilities, and post-market monitoring frameworks to ensure continuous compliance, operational governance, and lifecycle monitoring of AI systems in production environments.