What began with Chatbots and AI assistants has now evolved beyond AI agents into autonomous multi-agent systems. AI Assistants → AI Agents → and now Autonomous Workforces – each phase has increased AI capability while simultaneously widening the governance gap.
While the emerging autonomous workforce brings several advantages, such as exponential productivity gains and more connected experiences across the enterprise, it also introduces a new challenge that organizations are not yet fully equipped to handle: the proliferation of non-human identities (NHIs) – digital credentials used by automated processes to authenticate and interact with other systems.
AI agents deployed across an organization can generate thousands of requests per hour, create new identities, access sensitive data, and make autonomous decisions. Monitoring and governing these activities at scale is becoming increasingly difficult, as traditional security and identity management systems were not designed to handle this volume, speed, and complexity.
As these risks grow, organizations are becoming more aware and proactive about AI governance. The risk and security business for ServiceNow surpassed $1 billion in Annual Contract Value (ACV) in Q3 2025, making it one of the fastest-growing segments on the ServiceNow AI platform. This reflects a growing recognition that AI innovation must be accompanied by robust controls to manage the risks posed by ungoverned AI.
TL;DR
- Enterprises are rapidly deploying autonomous AI agents, but their existing governance frameworks can hardly keep up. This creates invisible risks around identity, access, and accountability.
- ServiceNow AI Control Tower, paired with Autonomous Security & Risk, gives enterprises a single governed view of every agent, identity, and connected asset.
Table of Contents
The Hidden Risk of Non-human Identities
Several enterprises are governing agentic AI in conventional ways, and the consequences are glaring.
- The sprawl of NHIs has reached a steep ratio, with NHIs outnumbering human identities at 82:1 in the enterprise and even higher ratios observed in cloud-native and hyper-automated environments. (Source: CyberArk’s 2025 Identity Security Landscape Report)
- Further compounding the risk, around 42% of machine identities possess privileged or sensitive access, yet 88% of organizations still define privileged users exclusively as human identities. This creates significant blind spots across AI environments.
- The core problem today is the lack of comprehensive visibility into an enterprise’s AI assets, raising critical questions around shadow AI tools, approvals, validity, and relevance.
- Fragmented tools and siloed approaches no longer cater to the rigorous governance needs of this agentic era. Enterprises need a unified platform approach to map every identity and every permission to take control of their AI estate, and this is exactly what the ServiceNow AI Control Tower is designed to do.
What is the ServiceNow AI Control Tower?
ServiceNow AI Control Tower is ServiceNow’s centralized AI governance platform providing a unified governance framework for AI systems, models, datasets, prompts, inputs and outputs, and the underlying CMDB and CSDM relationships that connect AI assets to business services and infrastructure. Key capabilities include AI Asset Inventory, AI Agent Advisor, AI Lifecycle Management, Audit Logging and Traceability, enabling organizations to maintain visibility, accountability, and control across the AI lifecycle.
Five Questions Enterprise Leaders Ask
- Which AI agents are currently active across the enterprise?
Organizations can effectively govern their AI estate only when they possess a reliable inventory of their AI deployments and assets. Without proper guardrails, several AI agents may operate outside traditional identity frameworks and can sometimes be deployed without centralized oversight, creating visibility gaps. - What data is being accessed by these AI models?
Research shows that beyond what their function requires, risking access and exposure of sensitive information. Without clear data boundaries, autonomous agents could lead to legal repercussions and reputational damage. - Are AI-generated decisions aligned with company policies?
AI agents do not inherently understand an organization’s internal policies, ethical guidelines, and compliance requirements. These guardrails must be explicitly embedded in their environments to ensure that AI agents align with company policies. - How can we ensure regulatory compliance and auditability?
Global regulatory bodies are rolling out frameworks (NIST AI RMF, ISO 42001, etc.) and legislation to govern AI systems. To stay compliant and avoid regulatory scrutiny, organizations must equip themselves with the necessary infrastructure and policies for agentic AI governance. - Who is accountable when AI actions impact business outcomes?
When autonomous agents cause unintended consequences, the effects can extend across workflows and downstream entities. As a result, accountability often becomes scattered across teams, vendors, and models. Nevertheless, organizations remain accountable for the actions and outcomes of their AI systems under emerging regulatory frameworks and existing accountability principles, irrespective of their level of autonomy.
How ServiceNow AI Control Tower Addresses These Challenges
As AI agents are onboarded into the enterprise, ServiceNow AI Control Tower helps inventory, monitor, and govern them throughout their lifecycle. These autonomous agents are automatically scored for risk, enforced with least-privilege access, and thoroughly monitored throughout their lifecycle.
When something drifts from the policy, the AI Control Tower detects and flags it before it cascades across the organization. Every decision and action of the autonomous agents is traced and documented, helping establish clear audit trails and facilitating compliance.
How ServiceNow Autonomous Security & Risk Extends AI Control Tower
The recently introduced ServiceNow Autonomous Risk and Security works in synchrony with the AI Control Tower to further strengthen governance by providing greater visibility into identities, permissions, and connected assets. Two notable capabilities include:
- Veza’s Access Graph: Veza from ServiceNow provides a continuous, real-time map of every access relationship across the enterprise, for both human users and non-human identities. This helps identify risky behavior early and automatically triggers downstream remediation.
- Armis’ Real-Time Asset Intelligence: Armis works across IT, IoT, and connected devices to enrich asset records with device type, behavioral data, and live risk posture. This data is then directly fed into ServiceNow’s security incident response workflows for effective mitigation of security threats.
Customer Outcomes
Organizations using ServiceNow’s risk and security capabilities are already seeing measurable outcomes:
- A global energy company operating in over 70 countries saved 1.2 million hours by automating security operations and reduced threat containment time by 97%.
- A major US financial services firm eliminated 96% of inactive non-human identities, preventing NHI sprawl.
- A Fortune 100 aerospace manufacturer reduced control attestation time by 75% and closed compliance gaps by 85%.
Source: ServiceNow
Final Thoughts
As organizations scale autonomous AI, governance becomes as important as innovation. Success depends on ensuring agentic systems operate within clear boundaries, with complete visibility, accountability, and trust built into every workflow.
The ServiceNow AI Control Tower helps build that foundation by bringing every agent, identity, permission, and connected asset into a unified governance space, along with accountability structures that meet the demands of the agentic era.
As an AI-first ServiceNow partner, KANINI helps organizations implement AI Control Tower and develop agentic AI governance frameworks that deliver measurable outcomes.
Frequently Asked Questions
It is never too late, but the longer governance is deferred, the more complex remediation becomes. ServiceNow AI Control Tower is designed to meet enterprises exactly where they are, automatically discovering and inventorying active agents from the moment it is implemented, risk-scoring them continuously, and applying least-privilege enforcement in real time. From there, governance can be applied progressively, starting with the highest-risk agents and most sensitive data interactions first.
AI governance no longer belongs to just IT and security teams. It also requires working together with legal and business units. Leaders must focus more on regulatory frameworks, AI model behavior, and AI risk management. ServiceNow AI Control Tower supports this by providing a single shared view of every agent, identity, permission, and risk across the enterprise, giving CIOs and CISOs a common operational picture rather than siloed dashboards.
A practical maturity assessment covers four dimensions: visibility, control, auditability, and accountability, all of which are directly covered by the ServiceNow AI Control Tower. Most enterprises deploy AI quickly, but do not have a strong foundation for these four dimensions, leaving the organization vulnerable to risks. Talk to KANINI for a detailed AI maturity assessment.
Author
Yoganandh Mookkaiah
Yoganandh is Director – ServiceNow with 20+ years of experience building and scaling high-impact ServiceNow practices. He currently leads the ServiceNow Practice at KANINI with end-to-end ownership of strategy, P&L, delivery governance, and customer success. His expertise spans enterprise delivery, strategic presales, portfolio governance, and executing complex programs across ITSM, ITOM, ITAM, IRM, and CSM under tight timelines.
