At CANDA, we know that AI Governance is more than just documentation, it's organisational change. We also know that AI regulation is fragmented and developing fast.
Our solutions are guided by international safety standards, guardrails and regulations including ISO/IEC 42001, NIST AI RMF, EU AI Act, Australian and Hong Kong guidance and more recently, Vietnam's new AI Law. As experts in this field, we've identified the core and common components that harmonise across jurisdictions and frameworks. Our DARTS Framework represents the foundational pillars upon which all organisations can prove their responsible and trustworthy AI practices.

Data quality and governance should ensure clear data provenance and controls related to data security, privacy and confidentiality impacted by the adoption of AI.

Establish a strong foundation for Accountability by assigning clear roles and responsibilities across the AI lifecycle, including human intervention, training and AI related policies.

Augment existing or adopt new risk practices to ensure thorough AI risk assessments, impact analysis and the implementation of AI-specific mitigation strategies.

Ensure transparency and clear explanations to stakeholders on your use of AI, including the testing and monitoring of AI system performance.

Foster proactive stakeholder engagement by providing mechanisms for feedback and opportunities to raise concerns on your organisations AI use.
Managing AI is an enterprise-wide responsibility and therefore, AI governance needs to be incorporated into your existing management systems. This is why we say AI Governance is more about transforming your operating model, than it is about overseeing your operating model.
Our solutions only take shape after we have conducted a current-state assessment of your existing practices. This way, we can ensure that you are directing resources to the areas that matter the most. This also ensures we our optimising integration with your existing management framework.
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