AI Governance is rapidly becoming one of the most important challenges organisations face as AI adoption accelerates.<\/p>\n\n\n\n
Over the past few months, We’ve seen many organisations struggle with the same questions:<\/p>\n\n\n\n
\u2022 Where do we start?<\/p>\n\n\n\n
\u2022 How do we align with ISO 42001?<\/p>\n\n\n\n
\u2022 What governance artefacts do we actually need?<\/p>\n\n\n\n
\u2022 How do we demonstrate accountability, oversight, and risk management without creating excessive bureaucracy?<\/p>\n\n\n\n
To help address these challenges, We’ve developed an AI Governance Framework Map based on the ERM Framework Map we previously shared and work we have done over the past couple of years. This provides a practical view of the key components needed to establish a robust AI Governance and AI Management System.<\/p>\n\n\n\n
The framework is designed to help organisations understand the relationships between governance, risk management, data governance, model governance, compliance, assurance, and continual improvement.<\/p>\n\n\n\n
If you’re currently navigating AI Governance, implementing ISO 42001, preparing for regulatory requirements, or simply trying to bring structure to your AI initiatives, We would be happy to share the framework and discuss your challenges.<\/p>\n\n\n\n
The conversation around AI Governance needs to move beyond theory and into practical implementation.<\/p>\n\n\n\n
Feel free to reach out if you’d like a copy or would like to exchange ideas.<\/p>\n","protected":false},"excerpt":{"rendered":"
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