Artificial intelligence(AI) continues to redefine industries through automation, prediction analytics, and decision-making capabilities. However, the rapid pace of deploying machine learning (ML) and AI models embodies an underlying systemic risk whereby organizations
tend to validate models only at the time of launch, with no brick-mould mechanisms for ongoing oversight. This failure of continuous monitoring retains risks like model drift, bias propagation, adversarial vulnerabilities, and unintended business consequences to persist
unchecked until the damage cannot be done.
The white paper will review why organizations find themselves in a “compliance theater” mode, where initial validations are mistaken for long-term assurance, while delving into the organizational, technical, and cultural barriers that prevent effective monitoring. Strategies
proposed will include continuous risk management, best practices borrowed from regulated industries, and a framework for resilient AI governance.