Security for AI Lifecycle Management

This document is a guide that outlines the services provided for securing AI adoption throughout its lifecycle. It details how organizations can manage emerging risks and threats to AI models, data, infrastructure, and applications while complying with global standards. The guide identifies specific risks such as data poisoning, adversarial attacks, model inversion, and bias amplification, and mentions relevant regulatory frameworks including the EU AI Act, ISO/IEC 42001, and NIST AI Risk Management Framework. It describes a suite of services designed to facilitate safe AI adoption, including risk assessments, continuous testing, and AI asset protection. Additionally, it presents a Secure AI Lab for experimentation and testing of AI strategies. The guide emphasizes the importance of tailored engagement models to support organizations in achieving their AI goals while maintaining security and compliance.