Shadow AI arises when individual departments or teams deploy AI solutions to accelerate their tasks and decision-making processes without going through the formal channels of governance. This practice can lead to significant security vulnerabilities, inconsistent data management, and compliance risks, as these AI implementations are not subject to the organization's standard security and operational checks.
Moreover, while Shadow AI can drive innovation by allowing for rapid deployment and testing of AI tools, it also poses a threat to the organization's overall data integrity and security framework. Organizations must establish robust AI governance and monitoring strategies to mitigate these risks, ensuring that all AI technologies are implemented within a controlled and secure environment, thus maintaining regulatory compliance and data protection standards.
References:
LinkedIn: The importance of software provenance
Cornell: Understanding Provenance in Industry
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