Autonomous Service Optimization with AI

Challenge

Steering of Roaming is becoming more challenguing as partner network performance and subscriber expectations evolve faster than operational teams can respond. When incidents arise, teams must react quickly.

For most users, optimizing steering performance is complex. It requires interpreting alerts, troubleshooting issues, identifying the right configuration levers, and validating changes through trial and error. This leads to three common challenges:

• Slow response to incidents: Resolution times can be long and are often reactive, with additional delays caused by extended change management cycles to identify the right configuration.

• Inconsistency: When only specific scenarios are addressed, results can vary, leading to uneven steering performance and inconsistent subscriber experience.

• A widening expert gap: Critical knowledge is concentrated among a few specialists, while other users lack the guidance to act effectively.

The result is increased operational friction, slower performance improvements, higher roaming costs, and missed opportunities to keep steering aligned with business objectives.

Solution

TOMIA’s Autonomous Service Optimization uses AI to translate service alerts and faults into clear, configuration-level recommendations that teams can act on immediately.

Rather than requiring users to interpret alerts and log data manually, AI analyzes context and performance signals to suggest targeted optimizations, such as:

• Increasing the number of network redirections when performance degradation is detected

• Adjusting the manual selection time frame to prevent subscribers from being stuck on underperforming networks

• Fine-tuning steering rules and thresholds to improve consistency

• Highlighting the changes most likely to deliver the greatest impact, enabling confident prioritization

This approach reduces reliance on specialist expertise by embedding best practice logic directly into the workflow. It enables everyday users to act faster and more effectively, while allowing experts to focus on higher-value activities such as optimization strategy and exception handling.

In essence, AI closes the loop between detection and action, turning alerts into recommendations and recommendations into optimization. 

Result

Autonomous Service Optimization delivers tangible benefits across operations, service quality, and overall performance:

• Faster corrective action: Teams move from identifying an alert to applying optimization recommendations in minutes, not hours.

• Consistent steering performance: Recommendations standardize how issues are addressed, improving traffic distribution accuracy.

• Reduced reliance on specialists: Guided recommendations empower a broader set of users, narrowing the gap between experts and the wider operations team.

• Reduced operational effort: Less manual tuning, fewer trial and error cycles, and reduced time spent hunting through configurations.

• Better revenue protection: Quicker optimization reduces the duration and impact of service issues, helping protect roaming experience, satisfaction, and commercial performance.

Explore TOMIA’s AI‑driven approach to smarter roaming here. 

 You can request a demo to learn more about the AI autonomous service optimization.