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The AI Maturity Model for Cybersecurity

Move from AI experimentation to measurable security outcomes

This paper gives a full deep dive into Darktrace's AI Maturity Model – the only available framework capable of guiding CISOs and cybersecurity teams

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ressources téléchargées ce mois-ci

14%

of security professionals allow AI to take independent remediation actions in their SOC today

92%

of security professionals say they need to understand how a defensive AI tool makes decisions before they can trust it

74%

of security professionals say they are limiting the autonomy of AI taking action in their SOC until explainability improves

77%

of security professionals say generative AI is now playing a role in security stacks

Que contient cette ressource

What's inside this resource

Understand where your security operations truly stand

Identify your current maturity level across detection, investigation, and response and uncover the gaps limiting your team’s effectiveness.

See how AI actually changes security workflows

Learn how responsibilities shift from manual triage to AI-driven investigation and response, and what that means for your team structure.

Build a roadmap to scale without adding complexity

Discover how to progress from reactive operations to autonomous security reducing alert fatigue, improving accuracy, and accelerating response.

White Paper

This paper gives a full deep dive into Darktrace's AI Maturity Model – the only available framework capable of guiding CISOs and cybersecurity teams

AI is already reshaping how security teams operate but most organizations are still treating it as an add-on rather than a transformation. The result is a gap between expectation and reality: tools generate more alerts, automation creates more complexity, and teams remain stuck in reactive workflows.

This is where the AI Maturity Model becomes critical.

Instead of asking whether AI is present, it reframes the conversation around outcomes. How effectively AI improves detection, accelerates response, and reduces operational strain. It provides a structured way to understand where your security operations stand today, and more importantly, what meaningful progress looks like next.

The model breaks down AI adoption into clear stages, showing how responsibilities shift from manual effort to AI-driven execution, and how security teams evolve alongside it. It connects technology decisions to real operational impact, helping leaders prioritize investments that reduce risk and improve resilience.

In a landscape where threats are moving faster and becoming harder to detect, incremental improvements are no longer enough. Security teams need a path to scale without adding headcount or complexity.

This document offers that path, grounded in how security operations actually work, not how AI is marketed.