5 Steps to Managing Shadow AI Tools Without Slowing Down Employees
This article discusses the growing ‘shadow AI’ gap – where employees use unapproved AI tools connected to corporate data without IT oversight. With 69% of organizations acknowledging this issue, it highlights the disconnect between employee productivity and security teams’ visibility. The piece outlines five steps to manage this risk, focusing on discovery, policy creation, and streamlining the approval process for new AI tools.
The rise of AI tools in the workplace is creating a significant security challenge for organizations. Employees are increasingly utilizing AI assistants for tasks like writing, coding, and meeting summarization, often without IT’s knowledge or approval. This ‘shadow AI’ landscape is characterized by tools connecting to corporate data through methods like OAuth tokens and browser sessions, bypassing traditional security controls. Gartner reports that a large percentage of organizations are aware of this issue, but only a small fraction have implemented governance policies. This lack of visibility creates a substantial risk of data breaches and compliance violations.
The article proposes a five-step approach to address this challenge. The first step involves discovering the extent of shadow AI usage through audits of OAuth connections, browser extensions, and bundled AI features within approved tools. The second step focuses on creating a practical AI governance policy that guides employees and clearly defines approved tools and data handling rules. Finally, the article advocates for establishing a ‘fast lane’ for new tool requests to reduce friction and prevent employees from seeking out unapproved solutions. This streamlined process, coupled with employee education, can help organizations gain control over their AI landscape and mitigate associated risks.