Managing Generative AI Risk in the Enterprise: ChatGPT, Copilots, and RAG Under the AI Act

GenAI Is Everywhere — And Increasingly Regulated

ChatGPT-style assistants, Microsoft Copilot, RAG knowledge base systems, and code generation AI are deployed across European enterprises at scale. The EU AI Act's GPAI chapter (in force since August 2025) creates compliance obligations throughout this landscape for both model providers and enterprise deployers.

The High-Risk Trap: When GenAI Becomes High-Risk AI

Many enterprises assume that deploying a GPAI model means minimal regulatory exposure. This is wrong. If the GenAI use case matches an Annex III high-risk category, the deployment is high-risk regardless of the underlying model: GenAI screening job applications (high-risk, Section 4), GenAI assessing creditworthiness (high-risk, Section 5), GenAI summarizing medical records for clinical decisions (potentially high-risk). The enterprise deployer becomes responsible for high-risk AI compliance for its specific use case.

Building an Enterprise GenAI Governance Framework

Step 1 — Use Case Registry: Document every GenAI deployment with risk classification. Step 2 — High-Risk Compliance: Apply full Annex III compliance to any high-risk GenAI use cases. Step 3 — Vendor Due Diligence: Require AI Act compliance documentation from all GPAI model providers (technical documentation, training data transparency, adversarial testing evidence for systemic-risk models). Step 4 — Article 4 Literacy Program: Train staff on GenAI limitations, acceptable use policy, when human review is required, and how to report concerns. Step 5 — Output Monitoring: Automated checks for prohibited content, human review of high-stakes outputs, feedback mechanisms for users to flag problematic outputs.

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