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Artificial intelligence is quickly moving from passive tools to active digital agents. Traditional AI systems mainly responded to prompts, generated content, or helped users analyze information. Agentic AI goes further. These systems can perceive context, reason over goals, call tools, interact with APIs, move data, and even create sub-agents to complete tasks. That shift is powerful, but it also changes the cybersecurity conversation. When AI can act, it is no longer just a

As more organizations experiment with autonomous AI agents—systems that plan, reason, call tools, read/write memory, and execute real tasks—I keep noticing the same pattern: everyone is excited to deploy them, but very few are prepared to secure them. What surprises me most is not the complexity of the technology, but the gaps in our understanding of the risks . Most teams start with good intentions. They pull out familiar ML security frameworks, map out the architecture, an

As digital transformation accelerates across industries, governance frameworks have become essential for managing emerging technologies...

As cloud computing becomes foundational to modern enterprise IT infrastructure, assessing security strategies in cloud environments is...

Here are practical measures to ensure your organisation stays updated and compliant: 1. Comprehensive Governance and Policies Define and...

Here are key practical security measures to implement: 1. Robust Risk Management Effective risk management is paramount for AI systems,...

Here are some of the key potential risks associated with AI technologies: 1. Content and Output Risks Hallucinations are a critical...