A strong AI governance programme typically includes several interconnected components. It begins with policy definition, where organisations outline acceptable use, ethical principles, and risk thresholds for AI. Next comes data governance, ensuring that training data is accurate, representative, and compliant with privacy laws. Model governance follows, focusing on explainability, fairness testing, version control, and continuous monitoring. Organisations also need operational governance, which defines roles, responsibilities, escalation paths, and documentation standards. Platforms like OneTrust play a major role here by offering automated workflows for risk assessments, AI impact evaluations, consent management, and compliance reporting. Meanwhile, agencies such as Pixole integrate these governance principles into digital products, ensuring that AI‑powered features — from analytics to personalisation — remain transparent, ethical, and user‑centric.