The governance gap is widening
Across industries, AI adoption is accelerating. Departments deploy models, integrate AI services, and experiment with generative AI — often without centralised visibility or structured approval processes. The result is a growing inventory of AI systems that nobody can fully account for.
This isn't just a compliance problem. It's a risk management problem. AI systems that process personal data, make consequential decisions, or interact with customers carry ethical, legal, and reputational risks that demand the same governance rigour as any other critical business capability.
Three steps to start governing AI now
First, build your AI inventory. You can't govern what you can't see. Catalogue every AI model, dataset, and system across the enterprise. Second, establish classification and risk assessment. Not all AI carries the same risk — align your approach to EU AI Act categories. Third, implement governance workflows that balance oversight with velocity. Business units should be able to request, assess, and deploy AI safely without bureaucratic bottlenecks.
Making governance operational
AI Control Tower on ServiceNow provides the platform to make these steps operational. A centralised AI registry, embedded compliance workflows, continuous monitoring, and regulatory evidence generation — all within the same platform your risk and compliance teams already use.
Key Outcomes
Assessment of current AI governance gaps across most organisations
Practical steps to establish governance without slowing innovation
Role of AI Control Tower in operationalising governance frameworks
Alignment to EU AI Act and NIST AI RMF requirements
Building organisational capacity for responsible AI at scale
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