governance

The Problem AI agents are moving from answering questions to taking actions — calling APIs, querying databases, executing code, managing memory. The security surface has shifted from "what the model says" to "what the agent does." Most guardrail solutions address the first problem. They filter content. They detect prompt injection. They moderate output. These are necessary but insufficient. The g…

What to Know: North Central Texas Council of Governments Chief Innovation Officer Tim Howell discussed AI pilots on a Technology Foresight Council panel. He said NCTCOG is approaching AI adoption through three pillars: governance, enablement and access. Howell said his organization has backed that approach with an AI committee, annual strategic planning, an agent governance framework, staff train…

FOR IMMEDIATE RELEASE Toronto, March 23, 2026 — As artificial intelligence (AI) reshapes the financial sector, institutions must strengthen governance, operational safeguards and workforce capabilities to manage a new generation […] The post AI Governance, Operational Resilience and Workforce Readiness are Critical for Advancing Responsible AI, Global Risk Institute Finds appeared first on Global…

As organizations move beyond single-purpose models toward autonomous and adaptive AI systems, governance requirements are changing rapidly. Traditional AI governance frameworks—designed for static models and offline decision-making—are increasingly insufficient for agentic AI systems that plan, act, and interact across complex environments in real time. This article provides a structured, enterpr…

by Tara Pozzi, Mark Lubell, Tanya Heikkila, Andrea K. Gerlak, & Pamela Rittelmeyer Science enterprises play an increasingly important role in shaping the policy process. While existing literature explores the nexus of science and decision-making, research is limited by a lack of empirical institutional analysis—specifically how science is shaped by and a feature of governance … Continue reading "…