From 8 Hours to 7 Seconds: Root Cause Analysis Reimagined with Agentic AI

ORGANIZATION Tier-1 North American Communication Service Provider
INDUSTRY Telecommunications
USE CASE Agentic AI for automated network reporting and root cause analysis
RESULT 100% reduction in manual reporting effort. Daily analysis time reduced from up to 8 hours to 7 seconds.

Overview:

For one of North America's largest communication service providers, the gap between what network data could reveal and how well CSPs could make timely use of that information had become a daily operational burden. The Operations team responsible for monitoring outages, analyzing root causes, and reporting across a complex, multi-vendor environment was spending so much time compiling data, there wasn’t enough left to act  on it.

Amdocs was brought in to replace the existing workflow. The result is a fully operational, scaled Agentic AI solution, now running in production, that automates the Operator's entire insight discovery and root cause analysis process. What previously required four analysts working separately across dashboards, ticketing systems, and BI tools for up to eight hours, now completes in seven seconds, with agentic AI.

The new process has entirely eliminated manual reporting, freeing engineering resources to focus on improving the network rather than discovering and describing what went wrong.

The Challenge: Four Analysts, Three Dashboards, Eight Hours

The operator's network teams had relied on a sequential, manual process to generate daily outage insights and root cause analyses. The workflow looked like this:

• Analyst 1 checked three separate dashboards for outage and performance data
• Analyst 2 confirmed and cross-referenced ServiceNow tickets
• Analyst 3 navigated Power BI reports for trending and historical context
• Analyst 4 verified day-specific and market-site data

Each step depended on the one before it, creating a sequential bottleneck compounded by constant context switching between tools like Qlik, ServiceNow, and Quantum Insights. The process consumed up to eight hours of total analyst time per cycle, with multiple full-time resources dedicated to a task that was slow, error-prone, and fundamentally limited by human cognitive capacity.

The real cost wasn't just time;. it was insight. By the time a root cause report was assembled, the data was often stale and the opportunity to act on it had narrowed. Engineers were spending their expertise on reporting mechanics instead of network improvement.

The Solution: Agentic AI for Insight Automation

Amdocs Agentic AI solution was purpose-built for the operator's reporting and root cause analysis workflow. Rather than layering automation on top of existing tools, the solution reimagines how insight is generated, using parallel multi-agents in parallel execution to do achieve in seconds what previously took a team of four an entire workday.
Here's how it works:

• Real-time data consolidation — AI agents simultaneously pull and normalize data from multiple live sources, eliminating manual data correlation and context switching
• Automatic ServiceNow verification — Tickets are validated with agentic AI, removing a significant manual bottleneck
• Smart summarization — Relevant data is extracted and distilled into concise, actionable outage insights, generated and delivered daily without human intervention
• Root cause pattern identification — Multi-dimensional pattern recognition replaces the cognitive limits of manual analysis, surfacing root causes that sequential workflows would miss

`The solution includes a sleek, purpose-built front end that integrates directly into the operator's existing workflow, no without disruption, no or ramp-up time. And it was designed from the ground up as a scalable framework, ready for expansion to other teams and business units.

The shift is fundamental: dashboards show what happened. Agents explain why it happened and recommend what to do next.

The Results: Zero Manual Effort, AI-driven Insight Delivery

The impact was immediate and measurable: