Gartner’s How to Achieve the Minimum Viable AI Governance
AI arrived in the enterprise faster than governance did. These articles cover the attack surface AI adds, how shadow AI slips past existing coverage, and what practical control over AI use on managed endpoints looks like.
From patches and configuration changes to software removal, the devil is in the details when it comes to remediating endpoints. Here we look at the role played by impact analysis, controlled execution, verification, and rollback in preventing operation disruption.
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The Hugging Face incident shows that, as AI changes the economics of the vulnerability backlog, security teams must shift from managing risk on paper to safely eliminating it at scale.
Most cyber risk isn’t unknown, it’s unresolved. Identity drift, exposed remote access, and shadow AI keep known exposures alive. Here's how continuous risk reduction can close the gap.
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Shadow AI is reshaping enterprise risk. Learn why discovering AI tools isn't enough without governance, policy enforcement, and continuous control.
AI has introduced new applications, identities, permissions, and data flows. Explore five ways it is expanding the enterprise attack surface and increasing risk.
As AI adoption accelerates, organizations need visibility and control over AI applications, agents, and permissions before they become unmanaged risk.
AI is changing how enterprises operate and how security must respond. Explore why governance and remediation must evolve to keep pace with machine-speed change.
In fast-moving, interconnected environments, cybersecurity is no longer all about the perimeter. As AI adoption accelerates and cyber conflict grows more indiscriminate, organizations must evolve their defenses and overall posture to stay ahead of threats.
