[RCAC Workshop]
📅 Date:April 24th 2026 ⏰ Time: 1PM 💻 Location: Virtual 🏫 Instructor: Ashish
Description As AI adoption accelerates across organizations, governance can no longer rely on static policies, one-time reviews, or high-level principles alone. Responsible AI & Governance 2.0 focuses on how institutions can move toward a more mature operating model built on continuous evidence, lifecycle controls, accountability, and auditable processes. This session explores how modern AI governance is evolving in response to changing regulatory expectations, decentralised AI adoption, and growing pressure to deploy systems quickly without compromising safety, trust, or compliance. Drawing on practical governance frameworks, standards, and real-world case studies, we will discuss how to design governance processes that are risk-based, scalable, and usable in real environments.
Who Should Attend AI/ML leaders, technical directors, platform and product owners, data scientists, risk and compliance professionals, security and privacy staff, research software engineers, and institutional decision-makers responsible for evaluating, deploying, or overseeing AI systems. This session is especially useful for those who want to understand how to operationalize trustworthy AI beyond policy statements and into real governance workflows.
Topics What “Governance 2.0” means and how it differs from traditional governance models The main pressures shaping AI governance today, including regulation, delivery speed, risk, and trust Trustworthy AI dimensions such as validity, safety, security, accountability, explainability, and fairness How generative AI changes the governance risk surface Risk-based governance approaches, including intake, classification, routing, and review Documentation, testing, release gates, monitoring, and incident response as part of an evidence-driven governance model Third-party and foundation model governance, including vendor risk and change management Implementation roadmaps, leadership metrics, and common governance pitfalls to avoid
Level Intermediate. Attendees should have a basic understanding of AI systems and organizational technology use, but no prior background in formal AI governance frameworks is required. 🔗 Register now:LINK