Shadow AI Risk Scanner '26

An employee copies confidential source code into ChatGPT to fix a bug. Another uploads a financial report to Gemini for a quick summary. A marketing team uses AI to draft a campaign. Within minutes, sensitive company information has unknowingly left the organization's secure environment.

This is the growing challenge of Shadow AI—employees using public Generative AI tools without proper governance or visibility. Organizations need a way to embrace AI without putting their data, compliance, and intellectual property at risk.

Your challenge is to build an Enterprise AI Governance Platform that helps organizations monitor AI usage, detect sensitive data before it is shared, enforce responsible AI policies, and enable secure adoption of Generative AI.

Answer These Questions: How can organizations identify which AI tools employees are using? How can sensitive business data be detected before it is shared? How can AI usage policies be monitored and enforced? How can leaders measure enterprise AI risks while encouraging responsible AI adoption?

What To Build: Enterprise AI Governance Platform:Build a secure web application to monitor enterprise AI usage and protect sensitive business information. AI Risk & Compliance: Detect sensitive data, analyse AI risks, enforce usage policies, and manage compliance. Executive Dashboard: Visualise AI adoption, risk scores, security insights, and compliance metrics. Secure & Scalable System: Implement secure authentication, role-based access, APIs, and an enterprise-ready architecture.

One Sentence: Complete this statement:"The moment my platform prevents confidential business data from reaching an unauthorised AI tool is...