As IT leaders, it's crucial to address the potential risks linked with AI systems early on. Implementing an AI Trust, Risk, and Security Management (AI TRiSM) programme can help align these systems with your company's guidelines, reliability and reputation, and data privacy requirements right from the start.
“By 2026, AI models from organizations that operationalize AI transparency, trust and security will achieve a 50% improvement in terms of adoption, business goals and user acceptance.” – Gartner
AI TRiSM matters because it's about making sure AI systems are reliable, trusted, secure, and private. This means that not only will AI be used by more people, but they'll also trust it more, helping your company meet its objectives and gain a competitive edge.
1. Explainability: Be clear about how the AI model works and monitor it continuously.
2. Model Operations (ModelOps): Ensure your AI models are well-managed and running smoothly.
3. AI Application Security: Secure your AI applications against threats.
4. Privacy: Protect user data and respect privacy standards.
1. Understanding AI: If people can't grasp what AI does, they won't trust it.
2. Access Control: Tools like ChatGPT may need controlled access to prevent misuse.
3. Third-party Risks: External AI tools could expose your data, so be careful.
4. Ongoing Monitoring: Constant monitoring of your AI tools will allow you to catch issues early.
5. Cybersecurity: As AI evolves, so must our methods to protect it from attacks.
6. Regulatory Compliance: Stay prepared for upcoming laws that will set new standards and compliance controls for AI use.
Incorporating these practices will ensure that your AI initiatives are built on a foundation of trust and security, paving the way for successful AI integration in your business.
To read more about AI TRiSM, read What it Takes to Make AI Safe and Effective from Gartner.
