Security and privacy are foundational pillars of AI governance. AI systems often rely on vast amounts of personal and sensitive data, making them attractive targets for cyber threats and data breaches. Ensuring robust data protection, secure model training, and privacy-preserving techniques like differential privacy and federated learning is essential. Moreover, governance frameworks must enforce compliance with data protection laws such as the GDPR and India’s Digital Personal Data Protection Act. By embedding security and privacy into the design and deployment of AI systems, organizations can build trust, safeguard individual rights, and foster responsible innovation

At AI Governance Symposium, we would dive into key aspects of AI Governance decisions such as On Premi Vs Cloud AI, LLM to LAM, Copyright/IPR and AI Generated Content such as code, Model selection, Secured deployment of Multi-Agent Architecture, AI organization set up and more