Articles

Responsible AI Governance

Bias, Model Drift, Hallucination: Mapping AI Risks to Governance Controls

Bias, Model Drift, Hallucination: Mapping AI Risks to Governance Controls As artificial intelligence (AI) becomes more deeply embedded in business operations, managing AI risks has become just as important as achieving performance or innovation. Organizations are no longer experimenting with AI in isolation. AI systems now influence hiring decisions, customer interactions, financial forecasts, security monitoring,…

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EU AI Act, NIST AI RMF, and ISO/IEC 42001: A Plain English Comparison

EU AI Act, NIST AI RMF and ISO/IEC 42001: A Plain English Comparison Security practitioners, governance/risk/compliance leaders, internal auditors, risk managers, and executives need to navigate a thicket of emerging artificial intelligence (AI) regulations and standards. The European Union’s Artificial Intelligence Act (EU AI Act), the U.S. National Institute of Standards and Technology’s AI Risk Management…

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Board-Level Metrics for Measuring AI Accountability

Boards are being asked to oversee artificial intelligence (AI) without the signals they need to do it well. Most AI reporting still focuses on performance factors, including accuracy, adoption, and cost savings. These metrics matter operationally, but they do not answer the questions boards are responsible for answering. That includes who owns the risk, who…

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