Autonomy with control:
a guide to agentic AI in risk and resilience
AI ambition is running ahead of what most organisations have actually delivered. According to the ServiceNow Enterprise AI Maturity Index, 59% have moved beyond piloting agentic AI, but only 9% have made real progress building autonomous, multistep workflows.
In this whitepaper, we turn a year of conversations with senior practitioners, regulators and AI leaders into practical frameworks for TPRM and operational resilience leaders. It draws on the insights from our webinar series and what we’re already doing with our customers, so you can move from experimenting with AI to getting real value from it.
In this paper, you’ll get practical guidance including:
- 01The four foundations of governed AI, drawn from one of the first AI Control Tower implementations
- 02Five ways AI is already improving TPRM
- 03The Agentic Resilience Framework for putting agents to work on your critical services
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What’s in the paper
- 01Abstract
A short summary of the paper, what it draws on and what readers will take away.
- 02Pulsar’s AI vision
Why AI ambition is outpacing execution, the foundations of governed AI and how we delivered one of the first Super Intelligence Control Tower implementations.
- 03Themes in risk and resilience
What practitioners are telling us in 2026 about operational resilience, third-party risk and the external forces bearing down on both.
- 04AI in TPRM
Where agents are already improving third-party risk management, and a deep dive into intelligent, data-driven monitoring.
- 05AI in operational resilience
Scoping, testing and cyber pain points, and the Agentic Resilience Framework for enterprises of any size.
- 06Agentic systems
The five connected layers of the ServiceNow agentic architecture, from AI agents to the enablers that keep them governed.
- 07Final thoughts
The key ideas from this paper, and where to start.
