Privacy Principles in AI

AI systems often process large volumes of data, including potentially sensitive business or personal information. This makes privacy a critical consideration when designing and using AI.

In SAP Business AI, privacy is embedded into how AI solutions are designed, deployed, and operated. This helps organizations to:

• Protect sensitive data
• Support regulatory compliance
• Maintain trust with users and customers

Learn about one of SAP’s approaches to secure and compliant AI environments, the EU AI Cloud: EU AI Cloud

SAP’s approach to AI aligns with widely recognized privacy principles, such as Data Minimization: only the data that is necessary for a specific task should be used.

In AI scenarios, this means:

• Limiting the amount of data included in prompts or processing
• Avoiding unnecessary exposure of sensitive information
• Applying techniques such as data masking or anonymization where appropriate

Data should only be used for a specific, defined purpose.

In AI contexts, this means:

• Data provided for one task is not reused for unrelated purposes
• AI processing is aligned with the intended business use case
• Data handling follows defined policies and governance rules

These principles help ensure that data is used in a controlled and expected way.

SAP follows a privacy-by-design approach, where privacy controls are embedded into the architecture and operation of AI systems.

Controlled data flows

Data is processed within defined architectural patterns and trust boundaries.

Data minimization and masking

Sensitive data can be reduced or anonymized before being processed by AI services.

Controlled data processing

SAP applies contractual and technical controls to ensure that customer data is processed only to fulfill the request and is not used for model training by external providers.

Policy-driven processing

Data handling is governed through defined policies, including filtering and access controls.

In practice, privacy in SAP AI scenarios is applied through a combination of technical and governance controls.

For example:

• Only relevant data is included in AI requests
• Sensitive information can be masked before processing
• AI interactions are governed through access controls and audit mechanisms

This helps ensure that privacy is not just a principle, but something that is actively enforced in real-world AI usage.

Privacy in SAP Business AI is based on established principles and is embedded into the design of AI systems.

SAP supports this through:

• Data minimization, ensuring only necessary data is used
• Purpose limitation, ensuring data is used only for defined tasks
• A privacy-by-design approach, embedding privacy controls into AI architecture and processes
• Technical and governance measures such as masking, policy enforcement, and controlled data flows

Together, these approaches help ensure that AI solutions respect privacy while enabling business value.