Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

AI! It's in everything, everywhere, all at once! It’s reading emails, summarising meetings, drafting documents, and writing code, and it’s no longer just giving us answers. We now also have agents that act on their own, access other systems, and make decisions with little to no human oversight. From a capability standpoint, it’s amazing.

The other day, someone said, “AI security is fundamentally data security”. And this got me thinking. Is it? Can AI security simply be solved with a typical data security strategy? It’s one of those statements that sounds correct when you first hear it, and it gets a few nods in the room, but then it quietly does a lot of damage to how people think about the problem. So, let’s dive into it, because the statement is really quite misleading.

Artificial intelligence is rapidly becoming embedded across manufacturing environments, from engineering and design to supply chain optimisation and operations. What was once experimental is now being applied in day-to-day workflows, often driven by the need for speed, efficiency, and competitive advantage. Recent research shows that 73% of manufacturing organisations report rapid AI adoption, with 90% ranking AI as a top security priority for 2026. The direction of travel is clear.

The recent breach at Vercel has drawn a lot of attention, not because the initial entry point was unusual, but because of what the incident quietly demonstrates about how modern workflows shape the impact of a compromise. This did not begin with a phishing email or an exposed service. It began with an AI tool.

On 7th April 2026, Anthropic published a system card for an AI model we may never be allowed to use: Claude Mythos. This preview demonstrated a significant leap in capability over Anthropic’s previous Claude Model (Opus 4.6), and their Responsible Scaling Policy (RSP) v3.1 led to them making the decision to withhold it from general availability, serving as a "defensive only" asset.

The Eskenzi IT Security Analyst & CISO Forum wasn’t a typical security event. This forum was a gathering of CISOs, analysts, and security leaders speaking candidly under Chatham House Rule about what’s actually breaking, what’s working, and where things are heading. Here are 5 key themes that came through loud and clear. None of them were surprising. But together, they paint a pretty stark picture of where security and AI are right now.

Surprise, surprise, agentic AI is advancing very quickly, and security isn’t quite keeping up. While most attention in recent times has focused on improving model capability, we’ve often been left wondering how to actually make these systems safe enough to trust with real-world tasks and limited interaction. This challenge has become particularly evident with the rise of platforms like OpenClaw, where autonomous agents can execute multi-step actions with minimal human oversight.

Artificial intelligence is moving rapidly from experimentation into everyday use across financial services. From client servicing and research to operations and risk analysis, AI is increasingly embedded in core workflows. This shift is widely recognised within the industry. Recent research indicates that 67% of financial services organisations report rapid AI adoption, with 93% ranking AI as a top security priority heading into 2026. At the same time, governance structures are being established.

RSA Conference 2026 made one thing clear very quickly. Security leaders are done with generic AI pitches. After two years of relentless “AI everything,” the market is now pushing back. There is a growing fatigue with vague promises, surface-level features, and what many are calling outright AI washing. The result is a trust gap. What cut through this year was not another AI-powered detection claim. It was a much more grounded question.