What is exactly AI control tower does in real time.

Devansh1 · 3 weeks ago

I am a bit confused about AI control. As we know, it controls all AI models and assets used in your system or organization by any department or team. My confusion is that we already see some AI systems that appear after installing plugins — are these ServiceNow out-of-the-box (OOB)? And if we fill out an intake form to add new AI, how are they added? Are they added directly by ServiceNow, or do the company's developers develop them first and then add them to the system?
Any explanation??

Thanks

Marcos Gianoni · 3 weeks ago

1. What AI Control Tower actually is

AI Control Tower is not another AI model or skill.
It’s a governance and inventory workspace that sits on top of all your AI, native and external.

Officially, it provides:

A single pane of glass to see AI systems, models, prompts, datasets, their owners and where they are used. ServiceNow+2ServiceNow+2
A lifecycle to manage those assets from intake → assess → build & test → deploy and beyond. ServiceNow+1
Embedded risk, compliance and value tracking for AI (NIST AI RMF, EU AI Act content, etc.). store.servicenow.com+2ServiceNow+2

Think of it as mission control for AI: it doesn’t “do the prediction” itself; it tracks, governs and monitors the things that do.

Roles that typically work there include sn_ai_governance.ai_steward and sn_ai_asset_mgmt.ai_asset_owner. ServiceNow

2. What it does “in real time”

“Real time” in this context means:

Up-to-date inventory of AI assets (systems, models, prompts, datasets). ServiceNow+1
Near-real-time metrics about usage, state, and risk/compliance posture pulled from connected systems (Now Assist skills, discovered models, cloud AI services, etc.). ServiceNow+1
Live workflow status of each AI asset’s lifecycle (which stage it’s in, open review tasks, approvals, cases, issues). ServiceNow+1

So AI Control Tower doesn’t “control every inference call” like a low-level orchestrator; instead it gives you continuous visibility and governance over:

What AI is running
Where it is used
Whether it is approved, compliant and delivering value

3. Why you already see AI systems after installing plugins

When you install AI Control Tower and AI-related products (Now Assist, predictive models, etc.), the solution ships with and/or discovers some out-of-the-box AI assets.

From the Store listing and release notes you’ll see that it supports:

A centralized AI asset inventory, including AI systems, models and prompts.
Automated discovery of Now Assist skills and ServiceNow-deployed models into that inventory. store.servicenow.com+1

That’s why, right after activation, you may already see:

Records for standard ServiceNow AI capabilities (e.g., Now Assist skills, pre-built models).
Some baseline configuration/strategy records to get you started.

These are OOB records created or discovered by the app so you don’t start from a blank inventory.

4. How new AI gets added (intake vs. implementation)

The intake form in AI Control Tower is part of the AI asset lifecycle, which is a governance process, not a model-builder. ServiceNow+2ServiceNow+2

High-level flow:

Intake / Idea / Request
- Someone submits an AI idea or requests onboarding of an existing AI system (e.g., a new LLM, a 3rd-party model, or a custom Now Assist skill).
- This creates/updates an AI asset record in the inventory.
Assess
- AI stewards, security, legal, risk, etc. complete risk, impact, and compliance assessments attached to that asset.
- Policies and controls are applied (IRM / GRC style).
Build & Test
- Your internal teams or vendors actually build/integrate the AI (e.g., configure Now Assist, deploy a model in Azure OpenAI, create an IntegrationHub connection, etc.).
- AI Control Tower tracks this work via tasks, approvals and lifecycle stage.
Deploy & Monitor
- Once deployed, telemetry/usage can be surfaced back into AI Control Tower via the platform and any configured connectors. store.servicenow.com+1

So to your question:
Submitting the intake form does not cause ServiceNow to automatically create or host the AI for you.
It registers and governs an AI asset that your organization (or a provider you choose) builds or connects.

In some cases, AI Discovery can automatically pull existing assets from hyperscalers (e.g., Azure, AWS) into the inventory. You still own and manage those models; AI Control Tower just gives you unified visibility and governance over them. store.servicenow.com+1

5. Short answers to your specific questions

“Does AI Control Tower control all AI models and assets in real time?”
It provides centralized, near-real-time visibility and governance over AI systems, models, prompts and datasets across the enterprise, plus their lifecycle, risk and value. It isn’t the thing actually running the model; it’s the governance and inventory layer on top.
“Are the AI systems we see after installing plugins OOB from ServiceNow?”
Yes. Some AI assets are delivered or auto-discovered out-of-the-box (for standard Now Assist skills and ServiceNow-hosted models) so that they appear in the AI asset inventory immediately after you enable the product. store.servicenow.com+1
“If we fill an intake form to add new AI, who actually builds it?”
The intake belongs to AI Control Tower; the implementation belongs to your organization or your providers. Control Tower orchestrates approvals, risk checks and lifecycle, but doesn’t magically develop the model for you.

6. Where to read more (official)

You may want to look at:

AI Control Tower product page (high-level capabilities and positioning). ServiceNow
AI Control Tower docs – landing & home page (Zurich/Yokohama). ServiceNow+1
AI asset lifecycle & lifecycle views (New / Assess / Build & test / Deploy). ServiceNow+1
AI Control Tower app in the ServiceNow Store (feature list: AI Discovery, AI asset lifecycle, risk & compliance). store.servicenow.com
AI Control Tower release notes for your target release (Yokohama/Zurich) to see what’s included OOB. ServiceNow+1

7. Possible follow-up topics you might want to explore

How AI Control Tower ties into IRM / GRC for AI risk and control monitoring.
How to integrate external LLMs (Azure OpenAI, Bedrock, etc.) into the AI inventory.
How AI Control Tower works alongside AI Agents / AI Agent Fabric and Now Assist in your architecture.

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MaxMixali · 3 weeks ago

OOB AI (Automatic - Built by ServiceNow)

When you install plugins like Now Assist, Virtual Agent, or Predictive Intelligence:

ServiceNow's pre-built AI automatically appears
Auto-registers in AI Control
You just configure and use it
Who built it: ServiceNow product team

2. Custom AI (Manual - Built by YOU)

When you submit an AI intake form:

NOT added by ServiceNow company
Your internal developers build it using:
- ServiceNow's Predictive Intelligence tools
- Integration Hub to connect external AI (OpenAI, Azure, etc.)
- AI Agent Studio for custom skills
Auto-registers in AI Control when created
Who builds it: Your team (or paid consultants/ServiceNow Professional Services)

The Intake Form Process (Simplified)

Department submits request → "We need AI for X"
Your governance team reviews → Approves/rejects
Your developers build it → Using ServiceNow platform tools OR external AI integration
Auto-registers in AI Control → Governance tracks it

Key Point

ServiceNow provides:

OOB AI features (pre-built)
Platform/tools to BUILD custom AI
AI Control to GOVERN all AI

ServiceNow does NOT:

Monitor your intake forms
Build custom AI for every customer request
Automatically add AI based on your submissions

Your team does the custom development work.

Simple Analogy

OOB AI = Apps that come pre-installed on your phone
Custom AI = Apps you build yourself using development tools
AI Control = Your company's policy for managing all apps