AIUC-1
E005

Assess cloud vs on-prem processing

Establish criteria for selecting cloud provider, and circumstances for on-premises processing considering data sensitivity, regulatory requirements, security controls, and operational needs

Keywords
Deployment
Cloud Security
On-Premise Security
Data Residency
Application
Mandatory
Frequency
Every 12 months
Type
Preventative
Crosswalks
AML-M0017: AI Model Distribution Methods
MAP 4.2: Internal risk controls
LLM03:25 - Supply Chain

Control activities

Conducting deployment risk assessments. For example, evaluating data sensitivity, regulatory compliance requirements, IP protection needs, and security controls for cloud vs. on-premises AI processing.

Documenting decision criteria and rationale. For example, establishing clear selection factors, maintaining records of deployment choices with business justification.

Implementing deployment-appropriate security controls. For example, configuring cloud-specific protections or on-premises security measures based on selected deployment model.

Implementing hybrid deployment strategies. For example, using on-premises for sensitive data, cloud for less sensitive workloads, with secure data flow controls.

Establishing cloud vendor management procedures. For example, conducting provider due diligence, implementing contractual protections for data sovereignty and IP.

Reviewing deployment decisions when requirements change. For example, reassessing choices when data sensitivity, regulations, or threat landscape evolves.

Organizations can submit alternative evidence demonstrating how they meet the requirement.

AIUC-1 is built with industry leaders

Phil Venables

"We need a SOC 2 for AI agents— a familiar, actionable standard for security and trust."

Google Cloud
Phil Venables
Former CISO of Google Cloud
Dr. Christina Liaghati

"Integrating MITRE ATLAS ensures AI security risk management tools are informed by the latest AI threat patterns and leverage state of the art defensive strategies."

MITRE
Dr. Christina Liaghati
MITRE ATLAS lead
Hyrum Anderson

"Today, enterprises can't reliably assess the security of their AI vendors— we need a standard to address this gap."

Cisco
Hyrum Anderson
Senior Director, Security & AI
Prof. Sanmi Koyejo

"Built on the latest advances in AI research, AIUC-1 empowers organizations to identify, assess, and mitigate AI risks with confidence."

Stanford
Prof. Sanmi Koyejo
Lead for Stanford Trustworthy AI Research
John Bautista

"AIUC-1 standardizes how AI is adopted. That's powerful."

Orrick
John Bautista
Partner at Orrick and creator of the YC SAFE
Lena Smart

"An AIUC-1 certificate enables me to sign contracts must faster— it's a clear signal I can trust."

SecurityPal
Lena Smart
Head of Trust for SecurityPal and former CISO of MongoDB
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