How to govern and scale AI effectively

There’s an old Indian parable about a group of blind people who encounter an elephant for the first time. Each person touches a different part of the animal. One feels the leg and thinks it’s a pillar. Another calls the trunk a tree branch. And a third describes the ear as a fan. While each interpretation is true in its own way, none reflects the full reality.

This parable is a useful analogy for how organizations approach AI governance. Different groups—customers, partners, product and engineering teams, and internal governance functions—examine AI through their own lens and reach conclusions shaped by their immediate needs.

At ServiceNow, we frequently hear different expectations about managing AI. Customers are concerned about their ability to scale AI while preventing security and risk issues. Engineering teams want best practices guidance for managing AI risks, such as hallucinations and data leakage. Internal functions are trying to understand how AI governance affects their daily work and the cross-functional projects accelerating AI adoption.

Project managers ask how to connect demand management to AI, investments, and roadmaps. Risk and compliance teams are focused on managing risks and complying with regulations, such as the EU AI Act. Security teams seek to establish controls and monitoring for AI and AI-related risks, such as data poisoning and leakage. Enterprise architecture teams need to establish standards for in-house AI use.

Each group’s perspective is shaped by its own priorities, but collectively, these viewpoints form the complex landscape that defines how AI should be governed. How do you move faster with AI and not just focus on one team’s narrow scope? That leads to a much bigger question: How can teams link arms and individually contribute to an organization with the goal of transforming its business with AI?

Establish a control tower to manage AI

To address business adoption of AI, many organizations have established an AI Center of Excellence (CoE) led by a chief AI officer who reports to a chief technology officer or a chief information officer. The AI CoE works with product teams and various corporate functions to oversee the organization’s AI-related activities, including AI strategy, governance, execution, monitoring, and value.

CoEs generally approach oversight in one of two ways. Some opt for point solutions focused on compliance, inventory, discovery, and/or large language model (LLM) monitoring. These point solutions operate in isolation, making it difficult to unify workstreams or scale adoption. More importantly, they often don’t connect AI to a technology system of record—a configuration management database (CMDB)—limiting the impact of AI.

To scale AI, you need an integrated set of capabilities that take into account the various aspects of AI planning, deployment, and monitoring across the enterprise. I think of it this way: Just as railroad companies, laborers, investors, and engineers worked to lay down tracks, provide coal, build railway stations, and plot train routes to win the West, organizations need to orchestrate many resources and capabilities to get the most out of AI.

That’s why ServiceNow built AI Control Tower—a central hub for managing, monitoring, and measuring AI strategy, governance, and compliance. Individual teams are empowered to independently implement AI, but a control tower approach enables them to align and support broader organizational transformation and not be slowed down by onerous and disconnected governance.

Using AI Control Tower, a CoE can embed AI governance across the organization’s AI ecosystem while aligning with business goals and diverse needs:

• AI Control Tower provides a central space to manage, monitor, measure, and oversee all AI activities.
• The AI inventory (contained in the CMDB) supports both manual entry and automated AI discovery and links AI to the organization’s business applications, services, and infrastructure.
• The onboarding process automatically identifies relevant risks and establishes the necessary controls to govern each AI agent, model, or asset.
• Engineering teams have the systems and guidance to create, embed, and use AI solutions in their daily work.
• Program management, risk, compliance, security, IT, data governance, legal, and other teams can connect and align their AI-related activities to a corporate AI strategy that’s managed by the AI CoE.

Balance innovation and oversight

ServiceNow^® AI Control Tower caters to and connects different voices and priorities in a way that scales, delivers value, and evolves along with organizational change. It goes beyond governance to balance innovation with responsible oversight while encouraging collaboration, adaptability, and long-term transformation.

AI is the new language of business. Siloed solutions or a single executive champion can't solve the challenges of governing AI throughout the corners of your business. You need a cross-functional team with centralized oversight using a single platform and a single data model. You must manage conversations about AI strategy, governance, execution, and value with key stakeholders—customers, partners, and third parties.

Successful organizations that build a thriving AI ecosystem will do so by empowering their people to champion AI adoption so that they can reach and surpass business goals together. In other words, they can visualize the elephant and its legs, trunk, and ears.

Find out how ServiceNow AI Control Tower can help you scale AI confidently and responsibly.