Agentic AI Governance: A Strategic Framework for Autonomous Systems

Agentic AI Governance: Securing Autonomous AI Agents in Enterprise

When AI agents start making decisions, calling tools, and coordinating with other agents without waiting for human approval, the governance playbook most...

From chatbots to assistants: governance is key for AI agents

AI's shift into agentic technology ushers in a new set of governance and security challenges that will mean defining to what extent they should be autonomous

Introducing the Agent Governance Toolkit: Open-source runtime security for AI agents | Microsoft Open Source Blog

Discover how the Microsoft Agent Governance Toolkit brings policy, identity, and reliability to autonomous AI agent systems.

MI9: An Integrated Runtime Governance Framework for Agentic AI

Agentic AI systems capable of reasoning, planning, and executing actions present fundamentally distinct governance challenges compared to traditional AI models. Unlike conventional AI, these systems exhibit emergent and unexpected behaviors during runtime, introducing novel agent-related risks that cannot be fully anticipated through pre-deployment governance alone. To address this critical gap, we introduce MI9, the first fully integrated runtime governance framework designed specifically for safety and alignment of agentic AI systems. MI9 introduces real-time controls through six integrated components: agency-risk index, agent-semantic telemetry capture, continuous authorization monitoring, Finite-State-Machine (FSM)-based conformance engines, goal-conditioned drift detection, and graduated containment strategies. Operating transparently across heterogeneous agent architectures, MI9 enables the systematic, safe, and responsible deployment of agentic systems in production environments where conventional governance approaches fall short, providing the foundational infrastructure for safe agentic AI deployment at scale. Detailed analysis through a diverse set of scenarios demonstrates MI9's systematic coverage of governance challenges that existing approaches fail to address, establishing the technical foundation for comprehensive agentic AI oversight.

AI agent runs amok in Fedora and elsewhere

Agentic AI systems can be used to do a variety of things autonomously on behalf of a human user [...]

The Agentic Systems Series - The Agentic Systems Series

Welcome to the complete guide for building AI coding assistants that actually work in production. This comprehensive three-book series takes you from fundamental concepts to implementing enterprise-ready collaborative systems.

Agentic Engineering Management

To what extent AI is OK to use in software development might be debated, but in general, the idea is not a controversial one anymore. The debate rather moved on from code completion and simple PR summarizations to Agentic Engineering, where an execution loop allows an AI Agent to function

Microsoft offers devs a better way to control AI agent behavior | TechCrunch

The specification lets developer, compliance, and security teams define their own policies for agents to follow in portable policy files.

What is Agentic AI? Examples, Use Cases, and Platforms [wcyear]

Everything you need to know about agentic AI solutions, including real-life examples of use cases, workflows, and frameworks.

Can AI Be Governed? Only If We Build Normatively Competent AI

Hadfield's discussion brings the idea of AI governance back to the core idea of steering the behavior of an AI system. As she notes, this not only involves technical questions about how AI systems ar...

Human-Centered Artificial Intelligence: Three Fresh Ideas

Human-Centered AI (HCAI) is a promising direction for designing AI systems that support human self-efficacy, promote creativity, clarify responsibility, and facilitate social participation. These human aspirations also encourage consideration of privacy, security, environmental protection, social justice, and human rights. This commentary reverses the current emphasis on algorithms and AI methods, by putting humans at the center of systems design thinking, in effect, a second Copernican Revolution. It offers three ideas: (1) a two-dimensional HCAI framework, which shows how it is possible to have both high levels of human control AND high levels of automation, (2) a shift from emulating humans to empowering people with a plea to shift language, imagery, and metaphors away from portrayals of intelligent autonomous teammates towards descriptions of powerful tool-like appliances and tele-operated devices, and (3) a three-level governance structure that describes how software engineering teams can develop more reliable systems, how managers can emphasize a safety culture across an organization, and how industry-wide certification can promote trustworthy HCAI systems. These ideas will be challenged by some, refined by others, extended to accommodate new technologies, and validated with quantitative and qualitative research. They offer a reframe -- a chance to restart design discussions for products and services -- which could bring greater benefits to individuals, families, communities, businesses, and society.

How to Deploy AI Agents for Safety

agentOS - Everything Agents Need to Run and Operate - Rivet

The complete platform for production AI agents. Stateful runtime, universal agent interface, and secure code execution. One SDK, one platform, deploy anywhere.

AI Agents Are Taking Over: And That’s Good For Business

Autonomous AI societies are transforming commerce with self-governing, agent-driven systems, redefining the future of business through collaborative intelligence.

The 8 Levels of Agentic Engineering — Bassim Eledath

AI's coding ability is outpacing our ability to wield it effectively. That gap closes in levels — 8 of them. Here's the progression from tab complete to autonomous agent teams.

Build Agent Advocates, Not Platform Agents

Language model agents are poised to mediate how people navigate and act online. If the companies that already dominate internet search, communication, and commerce -- or the firms trying to unseat them -- control these agents, the resulting platform agents will likely deepen surveillance, tighten lock-in, and further entrench incumbents. To resist that trajectory, this position paper argues that we should promote agent advocates: user-controlled agents that safeguard individual autonomy and choice. Doing so demands three coordinated moves: broad public access to both compute and capable AI models that are not platform-owned, open interoperability and safety standards, and market regulation that prevents platforms from foreclosing competition.