Tanium, ServiceNow launch autonomous IT operations tool

Tanium and ServiceNow have launched a joint autonomous IT product, ITOM AI Prime powered by Tanium. It combines Tanium's platform with ServiceNow IT Operations Management AI Prime.

The product links Tanium's endpoint data with ServiceNow's configuration management database, workflows and AI agents in a single package. It is designed to detect, resolve and verify IT issues without manual intervention.

The partnership formalises a deeper product relationship between the two software groups as companies seek to automate IT operations while maintaining tighter control over endpoint data, patching and change processes. A central aim is to address a longstanding enterprise IT problem: the gap between asset visibility and the ability to act.

Tanium's platform feeds real-time endpoint data into the ServiceNow CMDB, allowing workflows to run against current asset states rather than outdated records. That gives AI agents live telemetry and remediation status to guide decisions, including for operating system and third-party patching.

The process is intended to run through approved change procedures rather than ad hoc scripts or manual handoffs. The expected result is lower investigation times, less manual work and more accurate configuration records across large IT estates.

Closing the loop

The product centres on what the companies describe as a closed-loop model. In practice, data collected from endpoints feeds directly into workflow and remediation systems, so the same environment that identifies a problem can also trigger and confirm a fix.

For large organisations, that could affect routine IT tasks that have often remained labour-intensive, especially patch management, service desk work and maintenance across thousands of devices. Tanium said its endpoint intelligence is intended to support faster, more consistent action at scale.

"Most organizations want autonomous IT but can't get there because their automation is built on stale data. We've solved that. Tanium gives ServiceNow continuous, accurate endpoint truth, and together we close the loop from detection to remediation without manual intervention," said Harman Kaur, Chief Technology Officer, Tanium.

"This sets a new baseline for the industry: real-time visibility, AI-driven decision-making and autonomous remediation, unified for the first time in a single offering," Kaur said.

Customer link

The announcement also builds on an existing commercial relationship. According to the companies, ServiceNow already uses Tanium technology within its own operations.

That internal use appears to have shaped the latest product tie-up, with ServiceNow positioning the joint offering as a way to extend methods tested in its own environment to other customers. The companies highlighted endpoint management and security as core areas where tighter automation could have measurable operational effects.

"Together with Tanium, we've fundamentally changed how endpoints are managed and secured at scale-60% projected reduction in MTTR, autonomous patching and a clear path to our bold goal of zero breaches," said Sankha Nagchoudhury, SVP, Digital Business Services and Experiences, ServiceNow.

"This is execution at scale, and we look forward to extending this proven value to customers," Nagchoudhury said.

Operational focus

The launch comes as software suppliers push further into AI-led systems management, arguing that automation must be tied to live operational data to be trusted in production environments. CMDB accuracy has long been a weak point for many organisations, especially where asset inventories, patch levels and device states change faster than back-end records can be updated.

By tying endpoint telemetry directly into ServiceNow workflows, Tanium and ServiceNow are targeting that issue as much as the automation challenge itself. If successful, the model could make AI-led decision-making in IT operations less dependent on stale records and more closely aligned with actual device conditions.

The system covers remediation tasks including third-party and operating system patching, with actions carried out through established change controls rather than bypassing governance processes. That emphasis on governed automation reflects a wider concern among enterprise buyers that AI systems in IT must act quickly without weakening oversight.

According to Nagchoudhury, ServiceNow's own use of the software included a projected 60% reduction in mean time to resolution.