Ai Governance
5 articles
Governing Enterprise AI Agents: A Three-Layer Architecture and an Ethics-to-Engineering Checklist
Enterprise AI agents require robust governance to prevent failures like data breaches or scope creep. This article presents a three-layer architecture and an ethics-to-engineering checklist to ensure responsible development and deployment.
Uber Deploys MCP Gateway, Revealing a Blueprint for Enterprise AI Governance
Uber has deployed its Model Context Protocol (MCP) Gateway, a platform designed to manage AI agent interactions and provide a blueprint for enterprise AI governance. This system utilizes a dual-plane architecture and integrated security to ensure accountability and scalability across thousands of internal services.
AI's Unchecked Power Will Outpace Our Ability to Govern It by 2026
Despite AI's growing integration into critical societal functions, a stark reality persists: there are no testing standards, no requirement for AI to explain its decisions, and no organization equippe
Emerging AI Agent Development Tools and Frameworks
Despite one-third of organizations citing quality as the biggest barrier to production, 57.
Two Different Tools, Two Different Problems: How to Choose Between AI Coding Agents and No-Code Automation
AI workflow automation tools are split into developer-focused coding agents and no-code/low-code platforms for business teams. Selecting the right tool hinges on the user and organizational context, with governance being key to realizing sustainable productivity gains.