#governance
8 articles
US State AI Laws Are Filling the Gap Federal Inaction Left
With no comprehensive federal AI law in the United States, states have stopped waiting. Colorado, California, and a growing list of others are writing binding AI rules that are becoming the real compliance floor for any company selling into the US market.
Companies Are Writing Their Own AI Rules Before Regulators Finish Theirs
With comprehensive AI workplace regulation still incomplete in most jurisdictions, employers have stopped waiting. Internal AI-use policies, disclosure requirements, and approval workflows are becoming standard practice ahead of any legal mandate to have them.
Voluntary Safety Commitments Are Turning Into a De Facto Regulatory Floor
Frontier labs signed a round of voluntary safety commitments with little enforcement mechanism behind them. Government AI safety institutes have since started treating those same commitments as the baseline they evaluate against, which is quietly giving them the force regulation usually takes years to acquire.
Copyright Lawsuits Are Quietly Rewriting AI Product Roadmaps
The training-data lawsuits against AI companies are still working through courts, but their outcome is already visible in product decisions: licensing deals, opt-out tooling, and provenance features that did not exist two years ago and now ship as standard.
The EU AI Act's Real Deadline Is the One Builders Keep Missing
Most coverage of the EU AI Act focused on the ban on the worst use cases, which took effect first and affected almost nobody building ordinary products. The obligations that actually touch mainstream AI development are arriving in phases most teams have not scheduled for.
A Human in the Loop Is Not a Control System
Human review is often added to AI products as a reassuring label, even when reviewers lack time, context, or authority. Real oversight must be engineered as an operating system for exceptions, not assigned as ceremonial responsibility.
Stop Hiring AI Agents. Start Designing Their Jurisdiction.
An agent’s job description matters less than the boundaries around its tools, approvals, and responsibility. Teams should organize autonomous software around jurisdiction: what it may observe, change, spend, and commit.
Coding Agents Need Change Budgets, Not Blank Checks
The central risk of AI-assisted software development is not that agents write bad code; teams already know how to reject bad code. It is that they can create more plausible change than an organization can responsibly understand.