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AI Governance: The Problem of Shadow AI

By Linn Foster Freedman on March 20, 2025
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If you hang out with CISOs like I do, shadow IT has always been a difficult problem. Shadow IT refers to refers to “information technology (IT) systems deployed by departments other than the central IT department, to bypass limitations and restrictions that have been imposed by central information systems. While it can promote innovation and productivity, shadow IT introduces security risks and compliance concerns, especially when such systems are not aligned with corporate governance.”

Shadow IT has been a longstanding problem as IT professionals can’t implement security measures and guidelines when they are unaware of its use.

Now that artificial intelligence (AI) is widely used for purposes including work, it is imperative that organizations address its governance, as they previously addressed employees’ use of IT assets. Otherwise, employees will use AI tools without the organization’s knowledge and outside of its acceptable use policies, exacerbating the problem of shadow AI in the organization.

A recent TechRadar article concluded that “you almost certainly have a shadow AI problem.” The risks of having shadow AI in the organization include: “the leakage of sensitive or proprietary data, which is a common issue when employees upload documents to an AI service such as ChatGPT, for example, and its contents become available to users outside of the company. But it could also lead to serious data quality problems where incorrect information is retrieved from an unapproved AI source which may then lead to bad business decisions.” And don’t forget about the problem of hallucinations.

Implementing an AI Governance Program is one way to address the shadow AI problem. AI Governance programs differ depending on business needs, but all of them address who owns the program, AI tools usage, what tools are sanctioned, how AI tools can be used, guardrails around the risks of data loss, data integrity and accuracy, and user training and education. Governing the use of AI tools in an organization is similar to governing the use of IT assets. The most important thing is to get started before shadow AI gets out of hand.

Photo of Linn Foster Freedman Linn Foster Freedman

Linn Freedman practices in data privacy and security law, cybersecurity, and complex litigation. She is a member of the Business Litigation Group and the Financial Services Cyber-Compliance Team, and chair’s the firm’s Data Privacy and Security Team. Linn focuses her practice on…

Linn Freedman practices in data privacy and security law, cybersecurity, and complex litigation. She is a member of the Business Litigation Group and the Financial Services Cyber-Compliance Team, and chair’s the firm’s Data Privacy and Security Team. Linn focuses her practice on compliance with all state and federal privacy and security laws and regulations. She counsels a range of public and private clients from industries such as construction, education, health care, insurance, manufacturing, real estate, utilities and critical infrastructure, marine and charitable organizations, on state and federal data privacy and security investigations, as well as emergency data breach response and mitigation. Linn is an Adjunct Professor of the Practice of Cybersecurity at Brown University and an Adjunct Professor of Law at Roger Williams University School of Law.  Prior to joining the firm, Linn served as assistant attorney general and deputy chief of the Civil Division of the Attorney General’s Office for the State of Rhode Island. She earned her J.D. from Loyola University School of Law and her B.A., with honors, in American Studies from Newcomb College of Tulane University. She is admitted to practice law in Massachusetts and Rhode Island. Read her full rc.com bio here.

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  • Posted in:
    Intellectual Property
  • Blog:
    Data Privacy + Cybersecurity Insider
  • Organization:
    Robinson & Cole LLP
  • Article: View Original Source

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