Cybersecurity Expert

We’re getting good at writing policies about how AI should be used. Responsible AI principles. Acceptable-use policies. AI risk frameworks. Approval processes. Governance committees. All of these have a place. But there is a harder question that I think organisations need to start asking: What evidence proves those controls actually work? Because AI is changing the nature of the control problem. We are moving from AI that simply provides information to AI that can increasingly access data, make decisions, call tools, trigger workflows and take actions. And much of our traditional assurance thinking still assumes there is a human sitting somewhere in the process. That assumption is becoming increasingly uncomfortable.  Autonomy is scaling faster than assurance Consider a relatively simple AI agent. It might be able to: Read information from internal systems  Search documents and databases  Make decisions based on predefined criteria  Trigger workflows  Create or...

The recent decision by the U.S. administration to lift restrictions on Anthropic’s frontier AI models has generated plenty of debate. Some have questioned whether the original restrictions were justified, while others argue they reflected legitimate concerns about the cybersecurity capabilities of increasingly powerful AI systems. Regardless of where you stand, I believe the real story lies elsewhere. This is one of the clearest examples yet of governments treating AI models as technologies with potential national security implications rather than simply another software product. That should make every cybersecurity leader take notice. AI Security Is Different For decades, cybersecurity has focused on protecting systems from attack. Today, we are entering an era where AI itself can influence the speed, scale and sophistication of those attacks. Modern frontier models can assist with code analysis, vulnerability discovery, malware understanding and offensive research. While t...

By Brett Candon, VP International at Dropzone AI Trust has always been critical in security operations, but in the UK and Europe it carries significant regulatory weight. GDPR, NIS2 and similar related data‑protection frameworks shape far more than legal risk, they directly influence architectural decisions, supplier selection, and how security data can be accessed, processed and reviewed. That becomes more pronounced as autonomous AI systems move from proof‑of‑concept to daily SOC tooling.  The appeal is undeniable. Faster investigations, more consistent outcomes, and the ability to scale Tier‑1 response are all compelling. However, without clear answers on data flows, access and accountability, AI introduces risk as easily as it removes it. And speed alone does not result in trust. Against this backdrop, AI‑native approaches to SOC operations are gaining traction, grounded in the idea that autonomy, transparency, and repeatability must be foundational design principles rather tha...

AI is entering organisations faster than the security controls designed to govern it. Artificial intelligence is rapidly becoming embedded across organisations. AI assistants are now writing code, summarising documents, analysing data, and supporting operational decisions. What began as experimentation is quickly becoming operational dependency. For security teams, the challenge is not simply adopting AI. The real challenge is understanding how AI changes the way cybersecurity controls need to be validated. In many organisations, AI tools are already interacting with corporate data, internal systems, and operational workflows. Yet when security leaders ask a simple question “How do we know these AI systems are operating within our control boundaries?” …the answer is often less clear than expected. Why AI Security Controls Are Different Traditional software behaves in predictable ways. Security teams can audit ...

Dan Petrillo, VP of Product at  BlueVoyant     As artificial intelligence (AI) becomes more deeply embedded in security operations, a divide has emerged in how its role is defined. Some argue the security operations centre (SOC) should be fully autonomous, with AI replacing human analysts. Others believe that augmentation is the right path, using AI to support and extend existing teams.    Augmentation probably reflects how SOCs operate in practice. It helps analysts triage alerts, investigate incidents faster, and it brings better context into their work, while still ensuring humans are accountable for decisions.     Complete autonomy assumes a level of reliable, end-to-end decision-making that can operate without continuous human oversight. That’s a high bar. In real SOC environments, the technology, data quality, and operational constraints rarely support that ...

Written by Katie Barnett, Director of Cyber Security, and Gavin Wilson, Director of Physical Security and Risk, at  Toro Solutions After spending years working with organisations on security, one thing becomes hard to ignore. When something serious happens, the root causes are sadly rarely surprising and there is often a sense of inevitability to them. Access that was never quite tidied up, controls that were written down but not really enforced, multi factor authentication that was recommended but not mandatory or decisions that made sense in the moment and were never revisited. Last year’s headlines about the Louvre brought this into focus. The Louvre Museum, the world’s most visited cultural landmark, faced heavy criticism after investigators revealed that its internal video surveillance system was protected by the password “Louvre.” This came after a daylight heist in which thieves stole French Crown Jewels valued at over $100 million. The striking thing was not how bold the th...

What is the objective of implementing cybersecurity in a business? The answer might vary depending on whether you ask a security professional or a business executive. However, in any cybersecurity implementation, it’s very important to stay focused on the big picture: cybersecurity is there to secure the business and its assets, so the business can concentrate on achieving its business objectives. For example, if we are a coffee shop, then cybersecurity should be implemented to help the restaurant sell more coffee, and cybersecurity by itself is not an end goal. To do so, security professionals and executives must align cybersecurity with business objectives, which can be quite challenging in certain cases. Below, we’ll share important strategies that can help cybersecurity teams move business and cybersecurity alignment in the right direction, starting with the first one. Know the business objectives inside out One of the key challenges in aligning security with business objectives is...