Shadow AI

Shadow AI refers to artificial intelligence systems and applications developed and used within an organization without the knowledge, approval, or oversight of IT or data governance departments. These systems often arise from individual employees or departments seeking to solve problems or enhance productivity using AI tools. While these efforts can be beneficial, shadow AI poses risks, including data security vulnerabilities, compliance issues, and inconsistencies in ethical standards. Without centralized oversight, these AI systems may not adhere to the organization’s security policies or data protection measures, leading to potential negative consequences.

The rise of shadow AI is driven by the increasing accessibility of AI technologies, enabling non-specialists to create and deploy AI solutions. However, this can result in fragmented and uncoordinated AI efforts, complicating data integrity management and cohesive strategy implementation. To mitigate these risks, organizations need to encourage transparency and collaboration, involving IT and data governance teams in AI projects. Clear policies and guidelines for AI development can ensure alignment with strategic objectives, ethical standards, and regulatory requirements.

References:

Gartner: Managing Shadow AI

Forbes: What is Shadow AI and What Can IT Do About It?

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