Control Shadow AI
AI adoption does not wait for your internal governance committee to act.
Employees can begin entering client information, financial data, contracts, or internal documents into AI tools long before leadership establishes an approved AI use policy. At that point, “shadow AI” becomes more than a technology concern—it becomes a data-governance and internal-control risk for your company.
Blocking every AI tool is rarely the right solution. A practical AI governance program should:
• Inventory the approved AI tools at the company (especially critical for AI tools that can read/write or share data on their own, such as AI agents)
• Determine what effective use cases are for these tools at the company
• Define which data may—and may not—enter and leave an AI system
• Evaluate the data retention, privacy, training, and user access practices
• Assign clear ownership and human-review requirements (meaningful human review is critical)
• Monitor AI usage, policy exceptions, and emerging risks
The objective is not to slow responsible innovation. It is to give employees an approved path that is easier to follow than an unsafe workaround using shadow AI—and to create controls the company can explain, validate, and improve over time.
Before expanding your next AI initiative, ask three questions:
1. What company data will the tool access and/or modify?
2. Who will approve and administer that access?
3. How will we demonstrate that our AI governance controls are working?
Thoughtful AI governance turns experimentation into sustainable and defensible adoption. Please contact us Alpha Secure LLP, if you have any questions surrounding your AI governance initiatives, or you need help putting common sense internal controls for AI in place.
Email: contact@GoAlphaSec.com
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