Cybersecurity in the Age of AI: Moving from Fragile to Resilient
Updated
In this Futurum Research report, Cybersecurity in the Age of AI: Moving from Fragile to Resilient, created in collaboration with N-able, we outline a modern framework for business resilience built on three pillars—minimize exposure, reduce impact, and maintain continuity—and explain how to apply AI…
Futurum's Fernando Montenegro,
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Fernando Montenegro, The Futurum Group, "Cybersecurity in the Age of AI: Moving from Fragile to Resilient," February 27, 2026. https://preview.erikbethke.com/research-reports/cybersecurity-in-the-age-of-ai-moving-from-fragile-to-resilient/
Artificial intelligence is rapidly changing the cybersecurity equation for the mid-market. The same capabilities that improve business efficiency also enable threat actors to scale reconnaissance, social engineering, and exploitation at machine speed—while the attack surface expands through new APIs, third‑party services, and “shadow AI” adoption across the business.
In this environment, cyber resilience becomes business resilience: organizations need the ability to withstand an incident, operate through it, and recover quickly with minimal disruption to revenue and reputation. That shift requires moving from fragmented, alert-driven security to a unified program that manages risk across the full threat lifecycle.
In the latest Futurum Research report, Cybersecurity in the Age of AI: Moving from Fragile to Resilient, created in collaboration with N-able, we outline a pragmatic resilience framework built on three operational pillars—minimize exposure (before an alert), reduce impact (contain at machine speed), and maintain continuity (rapid, verified recovery). We also explain how to apply AI safely by pairing generative AI for interpretation with deterministic AI for validation and trusted automation.
In this report, you will learn:
- Why AI is accelerating the threat landscape for small and mid-sized organizations (including the rise of AI-driven social engineering).
- How to shift from reactive, alert-driven defense to a resilience program built on minimizing exposure, reducing impact, and maintaining continuity.
- Where generative AI helps (querying, summarizing, drafting playbooks/scripts) versus where deterministic AI is essential (verification, guardrails, autonomous action).
- How behavioral detection and trusted automation reduce “swivel-chair” latency during an active incident and limit lateral movement.
- What “active resilience” could look like next: decentralized intelligence at the endpoint and agent-to-agent collaboration.
If you are interested in learning more, be sure to download your copy of Cybersecurity in the Age of AI: Moving from Fragile to Resilient today.
Published by Futurum.
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