Introduction AI has the potential to generate immense value across the telecommunications industry. From customer care to network operations, the possibility to generate new insights, new revenue and deliver efficiencies should not be underestimated. However, AI also comes with a number of risks which telecommunications leaders, technology teams and customers are becoming increasingly aware of. Our ambition is to bring together a diverse team of contributors from multiple Telecommunications and Technology organizations in order to define an approach to Responsible AI which highlights the potential benefits to the Telco industry, whilst also highlighting the key risks associated with traditional and generative AI. From here we look at how specific AI use cases align with key Governance, Risk and Compliance frameworks. By assessing input from each of the participating organizations, we have developed a consistent approach to AI Governance which covers three critical areas: 1: Risk management 2: Pre production design and evaluation 3: Post production monitoring This approach then leads into an overview of the key considerations, processes and technical approaches / tools required in order to identify, manage and mitigate AI risks. The key outcomes we aim to prove are as follows: * A view of the business opportunities presented by AI. * An understanding of the potential AI related risks faced by the Telecommunications industry. * A framework and approach to understanding and mitigating against these risks. * A view of the technical advancements which enable organizations to address these risks at scale and where possible in an automated manner. * A view of the business benefits associated with the adoption of an AI Governance function across the organisation. The "Responsible AI Moonshot Catalyst" underscores the imperative of investing in responsible AI governance for CSPs, emphasizing that neglecting this aspect could lead to detrimental consequences. By showcasing the risks associated with inadequate governance, the initiative aims to drive home the message that responsible AI practices are essential for mitigating risks and maximizing revenue and efficiency gains, projecting a potential 30% EBIDTA improvement for CSPs globally.