General Purpose AI (GPAI) Model Governance: Systemic Risk Controls

Providers of General Purpose AI models face specialized obligations under the EU AI Act. Learn how to build systemic risk controls around GPAI models.

Mitigating Systemic Risks in Frontier GPAI Models

General Purpose AI (GPAI) models—especially those with systemic risk capabilities—are subject to model evaluations, adversarial testing, and energy consumption reporting under the EU AI Act.

When enterprise systems wrap GPAI models into autonomous agents, they must ensure that model outputs do not propagate systemic errors. ATL-Trust acts as a protective shield around GPAI models.

// GPAI risk evaluation check
if gpai_model.has_systemic_risk_flag && !sanitizer.is_clean(prompt) {
    return Err(ComplianceError::SystemicRiskViolation);
}

Adversarial Input Screening

Our gateway screens incoming prompts for systemic threat patterns before sending them to the GPAI backend, blocking adversarial exploits before they hit foundation model endpoints.

This dual-layer architecture decouples foundation model reasoning from deterministic risk enforcement.

• Shields GPAI foundation models from adversarial prompt exploits.
• Provides model-agnostic governance for multi-LLM routing.
• Satisfies GPAI systemic risk management guidelines.