Agentic AI is moving from hype to reality
Cut through the hype and find out what agentic AI means to the world of service management.
Agentic AI v Generative AI
Generative AI is already helping IT teams create content, summarise tickets, and curate knowledge—but it still needs to be asked. Agentic AI is different.
This infographic helps you understand how agentic AI is different—by comparing capabilities with generative AI.
Is your organisation ready to benefit from agentic AI?
To help you assess where you are and where you need to get to, we’ve created an interactive Agentic AI Readiness Assessment.
Just answer a few questions and in under 10 minutes you'll receive your tailored mini‑report and an agentic AI readiness score.
The agentic AI survival guide
Read this 10 page guide to discover:
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Why some organisations scale and others stall
Find out how agentic AI differs from traditional IT projects, and why control, trust, and clarity of purpose matter more than models and features.
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How to deploy safely and scale with confidence
Discover how thinking beyond AI features reveals the secret sauce of agentic success. We cover the importance of clear outcomes. We discuss why governance and guardrails are critical. And we map out how you can start simple, gain trust, and scale up in a way that really works.
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Why data and change management make or break AI
Poor data amplifies risk, so how good does your data really need to be? We'll show you a data quality framework for agentic AI readiness. Plus, we'll discuss the impact on roles and skills—sharing some insights on how you can smooth the path.
The question we often hear is this:
"How good does our data need to be to get started?"
The minimum data coverage and accuracy required to start experimenting with agentic AI in a meaningful way is 70%. Otherwise, the data coverage won't support the use cases, and the inaccuracies will translate into dangerous hallucinations.
Data readiness
Governance boundaries & controls
Human-in-the-loop
