---
title: "AI Governance Studio: An Introduction and Demo"
url: "https://atlan.com/demos/ai-governance-studio-introduction/"
description: "Govern AI adoption with Atlan's AI Governance Studio, gaining complete visibility and control over all AI applications and models at scale."
format: "Video"
video: "https://videos.ctfassets.net/nwa1c00rtgxb/38UktiDCSKdnmykS8UJCNN/4a98cbdcf77a2a2ecfab8c55e241ad9e/Introducing_the_Atlan_AI_Studio_Center.mp4"
content_purpose: ["Product Overview"]
target_persona: ["General", "Data Steward", "Data Engineer"]
journey_stage: ["S2 - Discovery", "C1 - Onboarding", "C3 - Adoption"]
use_case_context: ["Training"]
product: ["Data Marketplace - Data Governance"]
content_type: "video transcript"
transcript_source: "contentful"
---

# AI Governance Studio: An Introduction and Demo

Transcript of the video at https://atlan.com/demos/ai-governance-studio-introduction/

<!-- Body: machine transcript stored on the Contentful entry (field contentBody), timestamps kept, product names corrected. Not yet edited by a person. -->

Introducing the Atlan AI Governance Studio

[00:00] Organizations we are working with are wrestling the same things. I have thousands of developers building AI apps. How do I keep track of what they're building? Which models are available for use? How do I capture the context I need on a new app to be able, not just to approve or reject, but truly advise on the best path forward?

These aren't small problems. They're the foundation of responsible AI adoption, and they're exactly why we've built our AI governance module. So let's imagine I'm building a new AI application. Before I start coding, I wanna know, has anyone else in the company already built something similar with Atlan that's no longer a blind spot.

I can open the AI app homepage and instantly see every AI application across the company in one place. Now I know what's already been built before I reinvent the wheel. So great. I've checked what's been built. The next question is, what [01:00] models am I actually allowed to use for my application? Most companies pay for multiple models from multiple providers, and keeping track is nearly impossible.

With Atlan, that confusion disappears. Models are automatically cataloged from my Databricks environment so I can search, browse, and understand every model available to me. I've checked the apps, I've found the right model. Now it's time to register my AI application as an idea to be approved For this demo, I'll use the UI so you can see the experience visually, but just remember.

Atlan is an API first company with a robust SDK. Most enterprises automate this process with their CICD pipelines, so developers don't need to fill out forms manually. Here you're seeing me fill out the basic details of the application. Then I associate the AI model, powering it. In this case, I'll select Atlan ai.

Next I fill out [02:00] the ethical AI section. Documenting compliance requirements like the EU AI Act. I can also capture any company specific standards here, like our internal fairness or transparency guidelines, so everything lives in one place. Once complete, the form routes to our governance team for review, here's where they can request additional details, like whether the app is internal or external, which regions it'll be deployed in, and a few other details.

I submit my app and move on to the next question. How do approvers know if they can approve an AI application? I heard from one customer that their legal team took three weeks to approve their chat bot because it's a new motion for them. With our app framework, we've given you the ability to build agents to handle the velocity of change.

Our launch partner TAVR built an AI risk classification agent that you're seeing here. The moment an application is submitted, the agent automatically classifies the [03:00] risk associated with it, giving approvers clear guidance before making a decision. You'll see more about this later. Finally, what about monitoring?

Most modern AI applications are rag based. With atlan, I can visualize the lineage for every model from data sources to knowledge bases, to downstream apps. That means I can continuously monitor compliance and ensure nothing slips through the cracks. AI is moving fast. Atlan gives you the visibility and control to move with it responsibly and at scale.
