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    Data Governance — AI transformation lever in the Future Positive Atlas

    PREPARE YOUR DATA / DA-05

    Data Governance

    0.32Adaptability average

    Data governance for AI sits where regulatory mandate meets operational discipline. Article 10 of the EU AI Act sets the legal floor for high-risk systems: training, validation and testing datasets must meet specified quality and representativeness standards, with documented practices for collection, preparation and bias identification. IBM AI Ethics extends this into lifecycle governance — continuous controls from collection through training, deployment and retirement — while KPMG Trusted AI and the broader Responsible AI frameworks add the institutional layer of policies, accountability structures and audit mechanisms.

    Potential across the 5 Future Positive Principles

    Self-Directed
    Agency-Centered
    Impact-Led
    System-Focused
    Evolution-Driven
    Industry Standard baseline
    Future Positive potential

    Source Frameworks