Indosat Ooredoo Hutchison and Huawei have earned a major industry recognition for intelligent network operations. The partners won the TM Forum 2026 “Excellence in AI & data for business impact” award at DTW 2026 in Copenhagen.
The award highlights their AUTINOps deployment across Indonesia’s telecom network. The system uses an AI-Native Framework for Intelligent Operations. In simple terms, it helps networks detect faults, predict risks, and guide repairs faster.
For Indonesia, this matters greatly. The country spans more than 17,000 islands. That geography creates tough operating conditions for mobile and fixed networks. Engineers must manage faults across wide areas, diverse sites, and multiple network layers.
The AUTINOps platform combines several technologies. These include Digital Twin Network, multi-agent collaboration, and EDNS 2.0. A digital twin creates a live model of the real network. AI agents then work together to assess events and suggest actions.
According to the partners, the results look significant. The system achieved an 80% one-hop closure rate for fault handling. This means many issues reach resolution without long escalation chains. Mean time to repair also fell by 15%.
Meanwhile, network quality improved. Availability rose from 99.3% to 99.7%. Site traffic loss dropped by 15%. These figures show how AI can support customer experience, not only internal efficiency.
The project also changed daily operations. The teams reduced a nine-step manual workflow into a two-step intelligent loop. They used a data framework called “Identify-Analyze-Optimize-Retain” to guide network improvements.
However, this shift also changes the role of telecom staff. More than 400 operations employees received skills upgrades. The project also introduced 65 “digital employees,” meaning AI-based work assistants.
The new operating model focuses on “humans supervising/enhancing AI Agents to execute and close tasks.” This approach keeps people in control. It also lets software handle routine and repetitive tasks.
For operators, the attraction is clear. Faster repair times can lower service disruption. Better prediction can prevent failures before customers notice them. At scale, these gains can improve margins and service quality.
Still, AI-driven operations demand strong data discipline. Poor data can lead to weak decisions. Operators also need clear accountability when automated systems recommend actions. Staff training remains essential, especially when AI tools affect live networks.
The partners have deployed the solution across wireless, microwave, IP, transport, and energy domains. Annual agent calls now exceed 2 million. They also contributed 15 standards, protocols, and methodologies to TM Forum.
This award positions Indonesia as a reference market for AI-led telecom operations. It also signals growing momentum behind agent-based network management worldwide. For carriers, the message is simple: intelligent operations are moving from trials to real networks.
