In the first part of this series on ServiceNow AI control tower, we talked about why enterprises need AI Control Tower and the chaos it solves and the confidence it brings to AI adoption.
Now let us get into what really holds this tower together, its five core pillars. These are not just fancy headings from a slide deck, they represent the foundation every organization needs if they want to make AI useful, responsible, and valuable.
AI Strategy & Value
Starting with the “Why”: Every AI journey needs direction. It’s easy to get lost chasing hype without tying it back to business outcomes.The AI Strategy & Value pillar makes sure your AI initiatives are connected to your organization’s goals and whether that might be reducing costs, boosting efficiency, or improving customer experience.
Imagine deploying a GenAI assistant to summarize incidents. With AI Control Tower, you don’t just roll it out, you also measure its real impact on metrics like Mean Time to Resolve (MTTR) and operational cost savings.
It’s no longer about “we’re doing AI.” It’s “here’s how AI is making us better.”
AI Inventory
You Can’t Govern What You Can’t See: This pillar is simple but powerful.Most companies today have AI projects hiding in every corner sometthing like a proof of concept, a chatbot , maybe a model sitting in an Azure workspace that nobody remembers creating.
AI Inventory brings everything under one roof which includes the models, systems, prompts, datasets all mapped and linked using ServiceNow’s CMDB backbone.
Think of a bank managing its credit scoring AI, It can now see the models, datasets, cloud providers, and compliance controls all connected in a single record. That’s clarity.
AI Execution
Turning Ideas into Reliable AI Services: Every AI initiative has a lifecycle and this pillar brings discipline to that journey.
From Onboard → Assess → Build & Test → Deploy → Monitor, AI Execution makes sure every step is governed, reviewed, and approved before going live.
Before that new GenAI chatbot gets deployed, it is automatically routed through risk reviews, bias checks, and steward approvals. It is somethinng like DevOps for AI but with governance built in.
AI Risk & Compliance
Because Innovation Needs Guardrails: AI can do incredible things, but it can also go horribly wrong if left unchecked.
The AI Risk & Compliance pillar ensures every model or system aligns with frameworks like the EU AI Act, NIST AI RMF, or ISO 42001. It classifies risks, tracks controls, and visualizes them through dashboards and heatmaps — so you know where you stand.
For example: a healthcare triage model might be marked as high-risk under the EU AI Act. This can trigger closer monitoring and additional controls. The control is not as a punishment, but as protection.
This pillar is what turns AI governance from an afterthought into a continuous, proactive practice.
AI Value
“Cool” is not a KPI: Let us be real, every CIO or business leader wants to know: “What’s the ROI? (Return on investment)”
This pillar makes that conversation easy. It tracks adoption, cost savings, productivity improvements, and other measurable outcomes tied directly to AI usage.
For instance: a GenAI-powered customer support summarization tool might show a 25% reduction in handle time that’s a clear, quantifiable win.
AI Value connects the dots between innovation and impact, proving that your AI investments are actually paying off.
Conclusion
These five pillars are not just theoretical: they are practical, scalable, and built for the messy reality of enterprise AI.
- Strategy keeps AI connected to purpose.
- Inventory gives visibility and control.
- Execution brings structure and discipline.
- Risk & Compliance keeps things safe and trustworthy.
- Value shows the business impact loud and clear.
Together, they make AI adoption not just faster but also smarter.
