Foundry Is the Next Shadow IT Risk (Without This Purview Rule)

Shadow IT didn’t disappear — it evolved. In this episode, we break down why Foundry is quietly becoming the next major Shadow IT risk inside organizations, especially as teams rush to build AI apps, copilots, and agents faster than security and governance can keep up. What used to be unsanctioned SaaS tools has now turned into unsanctioned AI workloads — and the implications are far more serious. 🚨 The New Face of Shadow IT: AI & Agents Foundry makes it incredibly easy for developers, data teams, and even business units to spin up powerful AI-driven applications and agents. That speed is exactly the problem. When Foundry environments are created without guardrails:

• Security teams may not even know the apps exist
• Sensitive data can be accessed or processed without oversight
• Agents may run autonomously with excessive permissions
• Compliance boundaries become blurred or completely bypassed

This episode explains why AI platforms amplify Shadow IT risk, rather than just repeating old mistakes. 🔐 Why One Missing Purview Rule Changes Everything We dig into the critical role of Microsoft Purview in governing Foundry environments — and how missing even a single policy can create a massive blind spot. Without the right Purview configuration:

• Data classification may not apply to AI prompts or outputs
• DLP controls may never trigger
• Sensitive information can be exposed through agent workflows
• Organizations lose visibility into how data is being used, transformed, or shared by AI

This isn’t about blocking innovation — it’s about ensuring AI is deployed safely, visibly, and intentionally. 🤖 AI Agents Are Not “Just Apps” One of the biggest mindset shifts discussed in this episode: AI agents must be treated as first-class IT assets. Agents don’t just read data — they act on it.
They can:

• Chain tools together
• Make decisions
• Trigger downstream systems
• Operate continuously without human review

If these agents are created in Foundry without identity controls, policy enforcement, and governance, they effectively become autonomous shadow employees with access to your data. 🧠 Where Organizations Are Getting This Wrong We explore common mistakes teams are making right now:

• Letting developers deploy Foundry solutions before governance is ready
• Assuming Purview “just works” for AI by default
• Treating AI experimentation as low-risk
• Ignoring agent identities and permissions
• Failing to inventory AI workloads across the environment

The result? Security teams are left reacting after incidents instead of preventing them. ✅ What You Should Be Doing Instead This episode outlines practical steps organizations should take immediately:

• Define ownership for every Foundry environment and agent
• Apply Purview policies before AI goes to production
• Ensure data classification follows AI inputs and outputs
• Monitor agent behavior, not just user behavior
• Bring security into the AI development lifecycle early

The goal isn’t to slow teams down — it’s to make sure speed doesn’t come at the cost of control. 🔑 Key Takeaways

• Shadow IT is no longer just apps — it’s AI platforms and agents
• Foundry dramatically lowers the barrier to creating risky workloads
• One missing Purview rule can eliminate visibility entirely
• AI agents require the same (or stronger) governance as human users
• Security must evolve alongside AI, not chase it afterward

🎯 Who This Episode Is For

• Security leaders worried about AI risk and governance
• IT teams managing rapid AI adoption
• Architects designing modern AI platforms
• Compliance professionals navigating AI-driven data usage
• Developers building in Foundry who want to do it right

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