Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

‍ Artificial intelligence (AI) used to be something that only existed in science fiction novels and dystopian movies. Then, technology advanced, and it became a reality, being slowly implemented into experimental projects and niche use cases. Now, however, it is shaping real business outcomes, accelerating decisions and automating processes in ways that are becoming commonplace in daily market operations. ‍

How AI can transform even Microsoft's own documentation to meet its style standards.

AI is now part of customer service, product design, operations, and decision making. That reach brings real benefits, and it also surfaces personal and sensitive data in new places. It raises the question: How do we ship useful AI while protecting people and meeting laws? This guide helps you understand AI and data privacy as one practice through core principles, common pitfalls, practical controls, and a step by step plan to build privacy into your AI stack from the start.

Security leaders are well acquainted with Shadow IT; the unsanctioned apps, services, and even devices employees adopt to bypass bureaucracy and accelerate productivity. Think rogue cloud storage, messaging platforms, or unapproved SaaS tools. These all often slip past governance until they trigger a breach, compliance issue, or operational failure. Now, a more complex threat is emerging - Shadow AI.

AI has redrawn the cyber battlefield. Adversaries are already automating every phase of the kill chain to strike faster, scale wider, and overwhelm defenders. Manual workflows and conversational assistants help teams move faster, but still bind them to human speed. Agentic AI changes the equation. It enables security teams to deputize trusted, mission-ready agents that reason, decide, and act on their behalf — at the speed of AI. The promise of agentic AI is clear.

The Internet of Things (IoT) ecosystem is expanding rapidly, connecting billions of devices across industries. While this connectivity drives efficiency and innovation, it also introduces massive cyber risks. The IoT ecosystem is an interconnected environment of devices, systems, and technologies, making security especially complex. Attackers are increasingly using automation and artificial intelligence (AI) to launch sophisticated attacks at scale.

Protecting humans means protecting the tools humans use. Human risk management (HRM) means reducing human-based risk, or in our particular area, human-based cybersecurity risk. Study after study has shown that, in one way or another, humans are involved in the vast majority of cybersecurity incidents.