Why organizations are falling into an AI Security Illusion

Date:
Wed, 12 Aug 2026 14:39:44 +0000

Description:
If AI strengthens security, why do organizations continue to suffer breaches?

FULL STORY ======================================================================Copy link Facebook X Whatsapp Reddit Pinterest Flipboard Threads Email Share this article 0 Join the conversation Follow us Add us as a preferred source on Google Newsletter Subscribe to our newsletter Many organizations believe they are successfully leveraging AI tools to strengthen their security posture.

Investment is rising, AI is being embedded across multiple workloads and workflows, and governance frameworks continue to expand, giving the
impression on the surface that progress is being made. Danielle Kinsella Social Links Navigation

EMEA director at Gigamon. But beneath this AI adoption lies an unseen
problem: a growing gap between what organizations believe about their infrastructure security, and what they can actually evidence. Latest Videos From TechRadar Watch full video here: Confidence is rising, but so are breaches According to a global 2026 Hybrid Cloud Security Survey, which gathered the views of more than 1,000 Security and IT leaders, 93 percent
have invested in new security technologies, yet despite this, breach rates have hit their highest point. Sixty-five per cent of organizations
experienced a data breach in the past 12 months, an 18 percent rise year on year, and a near 40 percent rise over three years.

These worrying statistics are starting to ring alarm bells, highlighting that within organizations we are starting to see an illusion of security creeping in. Organizations are investing heavily in security tools, yet still seem to lack clear visibility into the outcomes of their investments. In other words, leaving security to be measured by what has been implemented, rather than
what can actually be verified. You may like The AI security paradox: Why are organizations trusting what they cant fully see? If everyone is rushing to board the AI ship why are so few workflows secure? Security's AI advantage will go to the organizations already built for accountability

A perfect storm of conditions has brought us to this point: AI adoption has scaled faster than governance and security teams can keep pace with, and hybrid cloud has added another dimension of complexity that few organizations have fully reckoned with.

AI is now embedded across enterprise environments, accelerating not just how organizations operate, but how risk moves through them. As adoption has outpaced oversight, the consequences are starting to surface, with nearly
half of organizations surveyed reporting a rise in AI-related insider
threats, including data leaks, and unsanctioned use (shadow AI). Perhaps surprisingly confidence hasn't reduced. Many organizations continue to classify their AI security posture as "defined" or "integrated," despite evidence portraying a radically different story. Are you a pro? Subscribe to our newsletter Sign up to the TechRadar Pro newsletter to get all the top news, opinion, features and guidance your business needs to succeed! Contact me with news and offers from other Future brands Receive email from us on behalf of our trusted partners or sponsors By submitting your information you agree to the Terms & Conditions and Privacy Policy and are aged 16 or over.

That confidence often rests on assumptions, and the scale of the disconnect
is striking; AI is now involved in 83 percent of security incidents, spanning external attacks, internal exposures, and direct targeting of AI systems. As threats move faster across increasingly fragmented and distributed environments, assumptions about whats secure quickly fall apart and without clear visibility into how data moves and systems behave, organizations cannot reliably manage risk. The warning signs No single indicator reveals a false sense of AI security, but several recurring patterns make it obvious.

The first is investment without impact. Many organizations are expanding
their security stacks, yet detection and response times are still moving in the wrong direction. More than 40 percent report that it now takes longer to detect and investigate breaches than it did previously, and that's not a coincidence. What to read next How AI agents are wrecking havoc in legacy security setups and enterprises are catching up Why AI is accelerating old cyber risks, not creating new ones Cracking down on shadow AI is making your business less secure, not more

When signals are spread across systems that don't connect, teams spend longer piecing together what happened rather than acting on it. Adding tools without improving visibility doesn't create more clarity. It creates more data, and more data without context is just more noise to wade through not to mention more false positives and perhaps even worse more false negatives.

The second is an inability to trace incidents back to their source. More than one in four organizations cannot determine the root cause of a breach, which means incidents are being closed out without fully understanding how they happened. The consequences are predictable: nearly one-third of organizations report multiple incidents within the same year. Without traceability, there
is no learning, and without learning, the same gaps simply get exploited again.

The third is the visibility gap opening in AI-driven environments. With
nearly three-quarters of organizations reporting limited visibility into AI-driven data flows, which span APIs, models, cloud services , and distributed infrastructure that is dynamic by design and doesn't map cleanly onto traditional monitoring approaches. Security teams can often see that something happened, but simply cant get to the how or the why. That gap between knowing an incident occurred and understanding it, is exactly where the illusion lives. Moving from illusion to evidence In response to growing complexity, organizations are collecting more telemetry than ever; metrics, events, logs and traces (MELT data), but more data does not necessarily
equate to better understanding. These signals each offer only a partial view: one measures performance, another records activity, other flags issues after the fact.

None of them, on their own, are able to explain how systems behave as a
whole. Whats missing is the connective tissue, the context that shows how these signals relate, how one event triggers another, and how issues
propagate across the environment. Without that, organizations arent gaining insight; theyre just accumulating noise.

Shattering the AI security illusion requires a shift from reactive security
to proactive monitoring and real-time observation of how systems behave. Security leaders agree, with more than 90 percent of organizations reporting that complete visibility across data in motion is critical to their
successful security outcomes.

This is where network-derived telemetry becomes essential. Unlike logs, which show what systems say theyre doing, network telemetry proves what is happening: how data moves, how systems interact, and how threats develop.
It's the shift from assumption to evidence and then proof, and it's the only foundation solid enough to build real security on. The network is the source of truth for todays security teams. AI security must be measured, not assumed AI is reshaping the threat landscape, enabling faster, more adaptive attacks while increasing the complexity of enterprise environments. But defenders are not without their own advantages.

The same technologies fueling attacks are already supporting security teams, automating detection, accelerating response, and investment in these capabilities continues to grow.

But let there be no mistake: investment is not proof. Security must be measured by the ability to observe, understand, and validate what is actually happening across the environment.

In the age of AI, the real risk is not organizations underinvesting in security, but the belief that they are secure without the evidence to prove it. We've reviewed, rated, and ranked the best cloud backup . This article
was produced as part of TechRadar Pro Perspectives , our channel to feature the best and brightest minds in the technology industry today.

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