Introducing Trustible’s Model Risk Assessment: A Structured Way to Evaluate Third-Party AI Models
Models are the heart of an AI system and the source of many risks. With many developers now choosing to use external models instead of building them from scratch, it is important to be able to choose a model that both performs well and provides a clear understanding of potential risks. This can be challenging […]
AI Monitoring After Deployment: What NIST 800-4 Reveals About Where Most Governance Programs Fall Short
TL;DR: In March 2026, NIST published the first major government framework for post-deployment AI monitoring. It identifies six monitoring categories, two orientations, and a core problem most organizations haven’t solved: monitoring generates signals, but only if the program is watching broadly enough to catch the ones that matter. Download our AI Monitoring Guide for more […]
A Governance Framework for Agentic AI
AI governance has always been about reviewing outputs before anything consequential happens. Agentic AI changes that. These systems don’t just generate content, they take action. They call APIs, execute code, send messages, and interact with software on their own. The human checkpoint that traditional governance relied on is no longer guaranteed. Most organizations already have […]
Everything You Need to Know About New York’s RAISE Act
New York became the second state last year to enact a frontier model disclosure law when Governor Kathy Hochul signed the Responsible AI Safety and Education (RAISE) Act. The new law requires frontier model providers to disclose certain safety processes for their models and report certain safety incidents to state regulators, with many similarities to California’s slate of AI laws passed last fall. The RAISE Act will take effect on January 1, 2027. This article covers who must comply with the RAISE Act, what transparency obligations the law creates, and how the law will be enforced.
Everything You Need to Know About the Executive Order on a National AI Policy Framework (2025)
On December 11, 2025, President Trump signed an Executive Order directing the federal government to build a “minimally burdensome” national framework for AI and to push back against state AI laws the Administration views as harmful to innovation. The EO takes a new, novel approach via Executive Branch authority, creating an AI Litigation Task Force and asking the U.S. Department of Commerce to evaluate state AI laws and identify “onerous” laws (explicitly citing laws that require models to “alter their truthful outputs”.)
5 AI Governance Trends Heading into 2026
AI has moved from experimental pilots to systems that shape real-world decisions, customer interactions, and mission outcomes. Organizations across sectors, including financial services, healthcare, insurance, retail, and the public sector, now depend on AI to run core operations and deliver better experiences. And their enthusiasm to adopt the technology responsibly is also growing.
Healthcare Regulation of AI: A Comprehensive Overview
AI in healthcare isn’t starting from a regulatory vacuum. It’s starting from an environment that already treats digital tools as safety‑critical: medical device rules, clinical trial regulations, GxP controls, HIPAA and GDPR, and payer oversight all assume that failing systems can directly harm patients or distort evidence. That makes healthcare one of the few sectors where AI is being plugged into dense, pre‑existing regulatory schemas rather than waiting for AI‑specific laws to catch up.
AI Governance Best Practices for Healthcare Systems and Pharmaceutical Companies
In the rapidly evolving landscape of healthcare, AI promises to revolutionize patient care, but it also brings significant risks. From algorithmic bias to data privacy breaches, the stakes are high. Effective AI governance is essential to harness the benefits of these technologies while safeguarding patient safety and ensuring compliance with regulations. This article delves into the critical challenges healthcare systems and pharmaceutical companies face, offering practical solutions and best practices for implementing trustworthy AI. Discover how to navigate the complexities of AI in healthcare and protect your organization from potential pitfalls.
Introducing the Trustible AI Governance Insights Center
At Trustible, we believe AI can be a powerful force for good, but it must be governed effectively to align with public benefit. Introducing the Trustible AI Governance Insights Center, a public, open-source library designed to equip enterprises, policymakers, and consumers with essential knowledge and tools to navigate AI’s risks and benefits. Our comprehensive taxonomies cover AI Risks, Mitigations, Benefits, and Model Ratings, providing actionable insights that empower organizations to implement robust governance practices. Join us in transforming the conversation around trusted AI into tangible, measurable outcomes. Explore the Insights Center today!