As AI drives unprecedented network traffic and complexity, communications service providers (CSPs) have realized that manual, command line interface (CLI)–driven processes can no longer keep pace with network demands. They are embarking upon the most significant evolution of their transport networks in decades, shifting from legacy processes to intelligent, autonomous, AI-driven operations.  

Commissioned by Cisco and Ciena, a new Omdia white paper provides a close look at how global CSPs are using agentic AI to greatly enhance network performance. By analyzing the ambitious three-year roadmaps of 80 global operators, the research uncovers the top AI transport use cases, real-world challenges of legacy tool integration, and the massive potential for self-optimizing networks. It’s a blueprint for the future of autonomous connectivity management. 

Visibility, intelligence, and autonomy: The new mandate for network resilience 

Use of AI is skyrocketing, so it’s not surprising that 79% of CSPs are already seeing AI services generating much higher traffic volumes. To accommodate this scale, an emerging strategy is to add greater visibility, intelligence with AI-based forecasting and optimization, and autonomy using agentic AI and closed-loop systems. 

Today, 61% of CSPs are still in the early stages of automation. Within three years, however, 56% of all those interviewed expect their networks to run autonomously or semi-autonomously with AI. 

Clear business outcomes driving adoption use cases 

Operators are adopting AI to enjoy several clear business outcomes. For the 47% already using AI in production networks, the value proposition is about: 

• Digital resilience: 48% cite faster troubleshooting and root cause analysis as a contributing factor. 
• Risk mitigation: 48% point to reducing human error by replacing manual processes. 
• Savings: 40% report lower OpEx with AI-enabled operations. 

To achieve these outcomes, CSPs are prioritizing use cases that deliver predictive analytics, network performance monitoring, and network optimization. Before deploying them, 64% of operators will deploy digital twins next year. These virtual models allow IT teams to test AI-driven features before applying them to the production network. 

Nearly half of CSPs (47%) now view agentic AI as critical to their three-year strategy. They plan to use these agents primarily for live performance optimization, troubleshooting, and natural language reporting. 

The human element: Navigating workforce evolution 

The rise of autonomous networks will also impact the telecommunications workforce. The report reveals that employees view the shift to agentic AI with a mix of anxiety and uncertainty. A majority of CSPs anticipate modest impacts to IT roles that rely on manual processes while a minority expect a 30% reduction in the workforce.  

Leadership is tasked with managing the technical deployment of AI while simultaneously addressing cultural and human impacts. The report highlights that the transition to AI-driven transport networks is not just an IT project; it is a profound organizational change that requires a clear strategy for reskilling and workforce management. 

The strategic mandate for network operators 

The technology is maturing. The use cases are proven. The business outcomes are clear. The only variable left is the pace of execution. As AI traffic continues to grow exponentially, the manual networks of yesterday will quickly become the bottlenecks of tomorrow.  

The mandate for CSPs is clear: integrate, automate, and evolve. Your network’s ability to think for itself is no longer a luxury—it’s your most critical business advantage. 

Read the full Omdia white paper