AI Governance
AI Regulation Is Here. Is Your System Ready?
72% of enterprises have AI in production. Only 52% have formal governance policies. EU transparency rules take effect August 2026. High-risk requirements follow in December 2027. US states are already enforcing. The compliance surface is expanding faster than most teams can track.
Download the Compliance RoadmapAI Governance Is an Infrastructure Problem
Most companies embedded AI into their products before building a governance framework around it. The regulatory gap is structural, not procedural, and it's widening.
The EU pushed high-risk system deadlines to December 2027, but transparency obligations, general-purpose AI rules, and US state enforcement are already live. The extended timeline is a planning window, not a reprieve.
AI compliance requires engineering: audit trails for traceability, human-in-the-loop oversight, continuous observability, and documented risk management. These aren't features that bolt on after launch.
Meanwhile, the US enforcement landscape is moving independently. The FTC established a dedicated AI enforcement unit in January 2026 and has already secured an $18M judgment for deceptive AI marketing. Colorado's AI Act requires bias testing and disclosure for high-risk automated decisions, and over 30 states have enacted deepfake laws. A federal court recently ruled that AI vendors can be treated as an employer's agent for discrimination liability. Enterprises with US operations face a regulatory patchwork that's harder to navigate than any single regulation.
And shadow AI is already inside most organizations. Employees are using AI tools with no visibility or controls. It's a governance liability hiding in plain sight.
The gap between using AI and governing AI is where regulatory risk lives. Closing it requires a governance platform, not a policy document.
Production AI with governance built in
- We build production AI systems for enterprises like Nike.
- Our open-source governance platform, Airbender, provides system-level control: logging, human oversight, and monitoring built into the application layer.
- We've shipped agentic systems in weeks, not months. Governance is built in from day one.
- Open source (Apache 2.0). Self-hosted. Your data stays yours.
Get the AI Compliance Roadmap
A practical guide for engineering teams navigating AI regulation across jurisdictions. Covers the EU AI Act (updated for the Omnibus timeline), US state enforcement, and what to prioritize in the next 12 months.
Frequently Asked Questions
Want to know where your systems stand?
Book a 30-minute AI governance assessment with our team.
Book an AssessmentFrom the blog
Why AI Roadmaps Stall in Regulated Environments
Across regulated industries, the AI roadmap stalls at the same wall: a managed-service stack that cannot host the operational layer agentic workflows need. What sovereign infrastructure means, why AI makes now the moment, and what the actual work looks like.
Agentic Platform Studio
What Is Agentic AI? A Practical Guide
Agentic AI is software that pursues goals across multiple steps using tools, planning, and judgment. What it is, how it works, when to use it, and when not to, from a team that builds it for enterprise clients.
Agentic Platform Studio
We rebuilt rangle.io for agentic search. Here's what we learned.
Five weeks of buildout, 850 pieces of content off Sanity, one engineer plus Claude. What rebuilding rangle.io for agentic search taught us.
Escape CMS & Commerce Lock-In