AIPG-CMM Assessment

Welcome to the AIPG-CMM Assessment

This assessment evaluates your team’s or organisation’s governance maturity of AI usage in projects across four key pillars: AI Strategy & Governance, AI Tools & Infrastructure, Human Capability & Accountability, and Data Readiness & Quality. Reference to “projects” implies “projects and programmes” or the “project environment” as appropriate.

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Company Information

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Level 3: Standardised

AI governance processes in projects are documented, repeatable, and consistent in projects within parts of the organisation.

General Recommendations for Current Level

    The above recommendations provide general guidance to incrementally improve governance maturity in your AI-assisted projects and programmes. If some Pillars scored lower than others, use the AIPG-CMM Pillar statements to also guide actions for governance maturity. Check detail ratings in the radar chart to identify specific areas for improvement.

    The AI Project Governance Framework (AIPGF) offers a sensible methodology for facilitating ethical, efficient and effective human-AI project collaboration.  

    • Can be integrated with a chosen project management methodology or approach, such as Agile, PRINCE2, PMBOK or hybrid approaches.
    • Provides structured and scalable AI governance, supporting projects and programmes of varying size, complexity, risk and AI adoption maturity.
    • Facilitates and encourages a high standard of ethical, efficient and effective use of AI in projects and programmes.

    By implementing the Framework, organisations can systematically govern AI use across their portfolio of projects and programmes, as their AI adoption scales and as AI tools evolve.  The accompanying  AI Project Governance Capability Maturity Model (AIPG-CMM) can be used to establish maturity benchmarks and actions towards continuous improvement.

     

    Disclaimer

    The AIPGF is intended to provide practical guidance for governing the use of AI in projects and programmes. The author (Emanuela Giangregorio) expressly disclaims all liability to any person or organisation arising directly or indirectly from the use of, or for any errors or omissions in, the AIPGF guidance. The adoption and application of the guidance is at organisation discretion and is their sole responsibility.   

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