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Automating IT service desk operations with AI and endpoint data -Tanium Tech Talks #155 video thumbnail
Module Deep Dive

Automating IT service desk operations with AI and endpoint data - Tanium Tech Talks #155

Real-time endpoint intelligence meets autonomous IT workflows as Tanium VP, Solution Architecture Saqib Khan walks through how the Tanium AI Agent for ServiceNow transforms incident triage, root cause analysis, and remediation into a closed-loop, data-driven process.

IT service desk teams face a familiar and compounding set of challenges: incidents constantly flowing in from machines around the world, each requiring investigation, root cause determination, and fix validation before resolution can even begin. The time it takes to log on, contact a user, pivot to diagnosing the issue, and confirm a fix adds up quickly, and the problem multiplies when the same issue is silently affecting hundreds of other machines at the same time.

The Tanium AI Agent for ServiceNow is designed to address exactly this, bringing real-time endpoint intelligence directly into the incident management workflow to eliminate guesswork, reduce investigation time, and enable data-driven decisions at scale.

In this episode of Tanium Tech Talks, Saqib walks through a live demonstration of the agent running inside a real ServiceNow environment connected to 1,500 live machines managed by Tanium. He covers how the agent automatically analyzes new incidents, runs live command-line sensors against the affected endpoint, surfaces a root cause analysis with a Confidence Score, and recommends or executes remediation—all without requiring the service desk agent to pivot between tools, remote into the machine, or interact with the user.

Saqib also explains the guardrails built into the agent through a concept called bounded autonomy, how the agent can identify patterns across the fleet to prevent incidents before they occur, and exactly what it takes to get started. Watch the full episode below to see it in action.

Key takeaways

  • The core investigation problem: IT support teams spend significant time on investigation, root cause determination, and validation before they can begin to fix an issue, and the same problem may be affecting hundreds of other machines simultaneously, with no efficient way to identify or prevent those additional incidents.
  • Query and action at scale: Tanium's ability to combine query at scale with action at scale makes it a source of truth that not only tells you the truth but confirms and validates it, and allows you to act on that truth so you can get things done quicker without spending 30 minutes to investigate.
  • Agentic triage in seconds: When a new incident is created in ServiceNow, the Tanium AI Agent automatically connects to the affected machine and checks every process, CPU, reboot time, who's last logged in, and services that are running, delivering a summary of exactly what's notable in the current state, connected to the machine live with evidence. No static snapshot, no server, no database—directly from the machine.
“This is literally running command line sensors from Tanium on the machine coming back with live answers. Now, it's not gonna stop until it gets to a 100% confidence level—that it either is high confidence, low confidence, or medium confidence based on the type of data that gets live from the machine. So what that means is reasoning here is a real AI, and reasoning with live telemetry is what makes this thing so great.”
Tanium VP, Solution Architecture Saqib Khan
  • Root cause analysis with confidence scoring: Rather than making high-level assumptions, the agent collects live data across multiple diagnostic questions, connects the dots, and arrives at a root cause with a confidence score, ensuring that decisions are evidence-based and data-driven rather than a risk to the customer.
  • Bounded autonomy and guardrails: The agent operates within a configurable access control framework using personas and roles, similar to Tanium RBAC, that limits what each service desk agent can query or act on, distinguishing between low-risk autonomous actions like clearing a cache and higher-risk actions like rebooting a machine that can be configured to require human approval.
“Autonomy is important, but it has to be controlled and bounded by guardrails.”
Tanium VP, Solution Architecture Saqib Khan
  • Incident avoidance across the fleet: Beyond resolving the current incident, the agent can scan the entire fleet in seconds for similar patterns on other machines—before they cause issues. This proactive approach, which Saqib calls incident avoidance, delivers significant return on investment.
  • Setup requirements and availability: Getting started requires ServiceNow ITSM and the Analysis product, plus the core Tanium platform with the Performance module recommended for deeper investigation and autonomy. Setup takes approximately 15 to 20 minutes with no customization required beyond token and persona configuration, and the agent is currently free.

Additional resources