Discover Microsoft AI tools, industry-specific governance solutions, and responsible AI practices to make smarter, more informed decisions about AI implementation.
AI Principles
A guiding framework for our responsible development and use of AI, alongside transparency and accountability in our AI development process.
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.
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.
Responsible AI
Discover how AWS is committing to developing AI responsibly – to built trust, promote the safe development of AI, and act as a force for good.
AI Economy Institute - Microsoft Research
The AI Economy Institute (AIEI) is Microsoft’s flagship think tank dedicated to shaping an inclusive, trustworthy AI economy. We building a network of scholars and convening that network with our subject matter experts to explore how artificial intelligence is transforming work, education, and productivity – and making this knowledge base available to policy-makers, educators, and […]
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...
Code of Conduct for Microsoft AI Services
Code of Conduct for Microsoft AI Services
Where AI Regulation Stands Today
The White House has released a National Artificial Intelligence Legislative Framework and new executive orders aiming to establish a single, nationwide standard for AI regulation...
Americans for Responsible Innovation on Twitter / X
NEW: Today ARI released a blueprint for federal AI governance, including three pillars that promote safe frontier AI development: ✅ Standards set by the government ✅ Independent assurance they are met ✅ Transparency into frontier AI development https://t.co/s2mlUP27Wm pic.twitter.com/X6IhBS9jKF— Americans for Responsible Innovation (@americans4ri) August 10, 2026
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.
Responsible Innovation at the Frontier - Americans for Responsible Innovation
ARI’s blueprint for federal AI governance is designed to promote safe frontier AI development in America. The blueprint is built around three governance functions any federal proposal should incorporate.
Greyhaven — Sovereign AI Systems for Enterprise
Greyhaven builds custom sovereign AI systems: on-premise inference, private data pipelines, and model-agnostic architecture so enterprises maintain full control over their AI.
AI Agent Standards: Navigating New NIST Governance | Nemko Digital
NIST's new AI agent standards are here. Learn what they mean for AI governance, compliance, and liability. Get ahead of the new regulations.
Guidelines on transparency obligations for providers and deployers of certain AI systems
These guidelines help providers and deployers of AI systems and competent authorities in ensuring compliance with the transparency obligations under Article 50 of the AI Act.
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
Irresponsible AI: big tech's influence on AI research and associated impacts
The accelerated development, deployment and adoption of artificial intelligence systems has been fuelled by the increasing presence of big tech in the AI field. This trend has been accompanied by growing ethical concerns and intensified societal and environmental impacts. This position paper argues that irresponsible AI development is strongly driven by big tech's influence and involvement in the field. First, we examine the growing and disproportionate influence of big tech in AI research and argue that its drive for scaling and general-purpose systems is fundamentally at odds with the responsible, ethical, and sustainable development of AI. Second, we review key current environmental and societal negative impacts of AI and trace their connections to big tech's influence. Third, we discuss the underlying economic forces driving big tech's actions. Finally, as a call to action, we invite AI researchers to counter big tech's influence in irresponsible AI development through strategies that build on the responsibility of implicated actors and collective action.
