Implement Strict Data Policies
- Create clear guidelines on what types of data can and cannot be input into AI tools. Prohibit sharing of confidential information, personally identifiable information (PII), intellectual property, and other sensitive data.
- Develop comprehensive AI usage policies and provide thorough training to employees on responsible AI use.
- Limit access to AI tools to only necessary business areas and employees.
Secure Data and Infrastructure
- Consider using private AI models rather than public ones, as they offer greater security and customization options.
- Implement strong access controls, encryption, and other security measures for any systems interacting with AI tools.
- Conduct regular security audits of AI usage and infrastructure.
- Use data loss prevention tools to monitor for potential leaks of sensitive information.
Sanitise and Control Data
- Train employees to remove all identifying information from prompts before inputting them into AI tools.
- Use data privacy vaults to isolate and protect sensitive data, replacing it with de-identified tokens for use in AI systems.
- Investigate secure versions of AI tools that can be deployed on company infrastructure without sharing data externally.
Oversight and Governance
- Establish human review processes for AI-generated content before external use.
- Create an AI governance council with experts from legal, ethics, and security domains.
- Conduct data protection impact assessments before implementing new AI tools.
- Designate a prompt engineer or review board to oversee AI interactions.