IBM Introduces Autonomous Security Operations with Agentic AI

Apr 28, 2025
IBM has launched new agentic AI capabilities to enhance its security operations, including the Autonomous Threat Operations Machine (ATOM) and Predictive Threat Intelligence (PTI).
IBM Introduces Autonomous Security Operations with Agentic AI

IBM has introduced new agentic AI capabilities to its managed detection and response services, as announced in a press release. The company launched the Autonomous Threat Operations Machine (ATOM), an AI system designed to autonomously handle threat triage, investigation, and remediation with minimal human intervention.

ATOM is part of IBM's Threat Detection and Response (TDR) services and uses an AI agentic framework to enhance existing security analytics solutions. It accelerates threat detection, analyzes alerts, performs risk analysis, and executes investigation plans, allowing security teams to focus on high-priority threats.

Additionally, IBM unveiled the X-Force Predictive Threat Intelligence (PTI) agent for ATOM. PTI integrates AI with expert human analysis to provide predictive threat insights, minimizing manual threat hunting efforts. It gathers data from over 100 sources to create intelligence reports tailored to specific organizational needs, focusing on indicators of behavior rather than just indicators of compromise.

We hope you enjoyed this article

Consider subscribing to one of our newsletters like Cybersecurity AI Weekly or Daily AI Brief.

Also, consider following us on social media:

Free newsletter

Cybersecurity AI Weekly

Weekly newsletter about AI in Cybersecurity.

Whitepaper

Tensordyne Napier: What If One Rack Could Do the Work of Nine?

Tensordyne

This Tensordyne whitepaper presents Napier, an inference-focused AI processor and rack-scale system based on the company’s TDN Math logarithmic number system. It examines infrastructure requirements for large mixture-of-experts and agentic models, compares major inference architecture approaches, and details the TDN AIP processor, TDN72 pod, TDN Link fabric, and Napier Ultra configuration. The paper reports simulation-based performance, cost, and accuracy-validation results, including Tensordyne’s projected comparison of one Napier rack with a nine-rack Nvidia Rubin plus Groq deployment; the chip is reported as taped out and in fabrication.

Read more
Free, six days a week

Daily AI Brief: the AI news that matters, in your inbox.