The webinar will explore how to transform unchecked “Shadow AI” adoption into a strategic advantage by presenting a practical, multi‑layered governance roadmap. Attendees will learn to audit AI entry points, implement a “Governance‑as‑Enabler” framework, and establish cross‑functional oversight for secure, scalable AI deployment.
Credo AI has joined the Coalition for Health AI (CHAI) Partner Program to bring its AI governance platform to healthcare, helping organizations manage risk, compliance, and auditability across clinical and operational AI systems. The partnership aims to operationalize CHAI’s framework, streamline regulatory obligations, and advance standardized AI governance for health AI.
China’s AI regulators are tightening rules, demanding platforms like ByteDance clearly label AI-generated content to curb misinformation and boost transparency. This stricter enforcement aims to balance responsible AI use with innovation, shaping the future of digital ecosystems in China and beyond.
The guide outlines a practical, risk‑based governance playbook for compliance leaders to safely adopt generative AI while maintaining transparency, accountability, and regulatory readiness. It details a tiered risk classification, use‑case registry, and controls such as approved platforms, technical guardrails, and continuous education to mitigate hallucinations, data privacy, bias, and Shadow AI risks.
The bipartisan Senate bill, known as the CHATBOT Act, aims to protect children by requiring AI companies to create family accounts with parental controls, privacy safeguards, and limits on manipulative features and targeted ads. It also seeks to study the mental health impact of chatbot use on minors while navigating potential First Amendment challenges.
AI integration in unified communications and customer experience boosts efficiency but creates significant compliance and governance challenges, especially with shadow IT and fragmented tech stacks. Organizations must adopt structured frameworks, like “approve, pilot, restrict,” and strengthen identity, access, and policy management to ensure secure, responsible AI adoption.
The AI Governance Conference in Chennai gathered policymakers, technologists, legal experts, industry leaders, and academics to discuss AI ethics, data protection, liability, bias, and sovereign AI, aiming to create actionable regional roadmaps for responsible AI governance. Organized by DCIR, Dhirubhai Ambani University – School of Law, and IITM Pravartak with MeitY support, the event featured keynote addresses, thematic sessions, and a special address by the CEO of Tamil Nadu Technology Hub.
The White House is pushing a federal AI regulatory framework to replace fragmented state laws, while states like California, Colorado, Utah, and Texas continue to enact their own AI legislation. This creates legal uncertainty, requiring businesses to comply with existing state rules until federal preemption is clarified.
PolicyGuard enables enterprises to define, edit, and enforce custom AI policies across models, agents, and applications in real time, with built-in reasoning and audit-ready decisions. It integrates over 30 regulatory frameworks and continuously refines policies using Policy Lab, all without requiring engineering effort.
SAS announced extensive platform updates that add a new AI governance layer, SAS AI Navigator, and enhanced agentic AI features such as Viya Copilot and industry‑specific AI agents. These enhancements aim to help enterprises operationalize AI at scale while ensuring trust, compliance, and integrated data management.
