Today, we're announcing the general availability of Govern AI Assistant (GAIA), the first AI governance agent purpose-built for the speed and scale of modern AI adoption.
Why Now?
Until recently, AI governance teams could keep up. AI projects were few, centralized, and built in-house. That world is gone: based on our State of AI Governance Survey, 60% of organizations now deploy AI across multiple departments or company-wide, and the distinction between AI builder and AI user has effectively dissolved.
The operational math no longer works. Only 4% of organizations report governing AI at scale, while 45% lose 11–20 hours a week to manual intake. The gap between what AI governance teams are asked to review and what they can realistically process keeps widening. One Director of AI and Data Science in our recent State of AI Governance survey put it plainly: of more than 100 AI requests across their organization, their team had been able to approve six.
AI governance teams are among the most AI-literate functions in any organization. The move now is to adopt AI to meet agentic AI's pace. Let AI handle the documentation and intake so people can focus on the judgment, without giving up control. That is what GAIA is built to do.
How Agents Accelerate AI Governance Tasks
At Credo AI, we have led the market in meeting the needs of AI governance admins every stage of enterprise AI adoption. GAIA represents the next stage of that evolution, with many more features to come that will equip AI governance people with the skills, tools, and knowledge needed to deliver agentically governed AI at scale.
GAIA automates the documentation, risk identification, and compliance workflows that can cost governance teams time, so those teams can focus on the most critical checkpoints for human expertise and judgment:
- Accelerated Use Case Intake. Governance teams spend significant time documenting new AI use cases. With GAIA, users provide a text description or upload relevant documents — product briefs, PRDs, project plans — and the agent suggests descriptions, domains, and key metadata fields. What used to take hours of back-and-forth takes minutes.
- Context-Aware Questionnaire Assistance. Intake questionnaires are thorough by design, but completing them is tedious. GAIA read use case information and draft suggested responses to each question, giving reviewers a strong starting point rather than a blank page. Every suggestion can be edited, rejected, or approved individually — with reasoning provided for each.
- Proactive Risk Identification. As AI use cases multiply, the risk of overlooking edge cases grows. GAIA analyzes the specific characteristics of each use case and recommends relevant risk scenarios from Credo AI’s library, surfacing things a stretched team might not have time to find on their own.
- Risk-Matched Controls. Once risks are identified, GAIA suggests appropriate mitigating controls from the Credo AI Control Library, mapped to each risk scenario based on the context of the specific use case. Teams get a defensible, documented starting point for governance planning — not a generic checklist.
GAIA today, and what's coming next
GAIA runs inside the Credo AI platform and uses our risk and control libraries to make its recommendations. The agent itself is configured by Credo AI, refined across four years of enterprise governance deployments, and ready to deploy without setup.
Building on GAIA, Credo AI is also previewing a public MCP server that exposes the platform to customer-built agents. Organizations can connect agents running on the models, contexts, and configurations of their choice, with the ability to read use case data, submit assessments, trigger reviews, and act on their own policies and risk taxonomies.
General Availability
GAIA is generally available today to all Credo AI platform customers, with the Credo AI MCP server following in preview later this quarter.
You can request a demo of GAIA, and see it in action here.
GAIA is the first release of Credo AI's agentic AI governance roadmap — purpose-built for the speed and scale that today's governance teams require. Next is runtime governance: continuous monitoring of AI systems in production, with policy enforcement and intervention at the point of use.
Agentic AI finally unlocks the scale AI governance teams need to operate at the speed of AI adoption. Stay tuned for what’s coming down the pipe.
DISCLAIMER. The information we provide here is for informational purposes only and is not intended in any way to represent legal advice or a legal opinion that you can rely on. It is your sole responsibility to consult an attorney to resolve any legal issues related to this information.
