Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

Software development is undergoing its biggest shift since the rise of cloud and DevOps. The difference this time? The shift is being driven by artificial intelligence, and it’s moving fast. AI-powered coding tools have rapidly made their way into developer workflows. Agents and LLMs are helping teams move faster, automate more, and build in entirely new ways. But speed often comes with tradeoffs.

Artificial intelligence is no longer a future consideration. It’s here — and it’s changing how software is built. Fast. Enterprise teams are moving beyond AI pilots and proof-of-concepts. They’re rolling out real-world, high-value use cases and doing it at scale. According to IDC forecasting, AI spend will more than double by 2028. At the center of that surge is AI-assisted software development.

Let’s be honest. Most cloud security alerts feel like trying to read a book with half the pages missing. You get bits and pieces — “unusual login,” “suspicious process,” “network traffic spike” — but no real explanation of what actually happened or what you should do about it. That’s the daily reality for security teams. You’re not just fighting attackers; you’re fighting for context.

Modern IT is innately complex, which leads to matching complexity in the security environment and indeed for managing privileged accounts. Companies rely on multi-cloud and hybrid cloud deployments to get more flexibility and to enhance resilience. But the flipside of a distributed, decentralized IT approach is a variety of security models across platforms. That creates a broad attack surface, and a complex web of privileged accounts.