The Road to Autonomous Networks: Why CSPs Must Automate OSS Now

Telecommunications networks are evolving at an unprecedented pace. As operators transition to fiber, 5G, and cloud-native architectures, they face mounting challenges in managing network complexity, ensuring service reliability, and controlling operational costs.

However, many Communication Service Providers (CSPs) still rely on legacy Operational Support Systems (OSS) that are heavily manual, reactive, and fragmented. This is leading to:

• Escalating OPEX – Network expansion requires an increasing number of engineers and support staff.
• Surging Ticket Volumes – More complexity means more faults, overwhelming NOC teams.
• Slow Incident Resolution – Manual troubleshooting extends service downtime.
• Strained Resources – Higher demand for technical staff, with limited scalability.
• Customer Experience Risks – Operational inefficiencies impact service quality, increasing churn risk.

With next-generation networks like XGS-PON and 5G scaling rapidly, CSPs must shift from traditional OSS models to AI-driven automation. Without it, costs will continue to rise while service quality and agility decline.

Many CSPs face critical challenges as they expand their XGS-PON fiber broadband networks. Key points to address include:

• Escalating support demand – A multi-fold increase in customer activations requires a corresponding increase in engineering and support staff.
• High ticket volumes – A large percentage of tickets are avoidable or redundant, adding unnecessary operational overhead.
• Slow fault resolution – Too many manual steps mean longer downtimes and increased customer complaints.
• Rising OPEX – Without automation, costs are projected to rise significantly over the next five years.

To continue aggressive network expansion without incurring unsustainable cost increases, CSPs need a modernized, automated OSS solution.

By partnering with technology providers to design and implement a cloud-native, AI-driven OSS automation framework, CSPs can modernize how networks are planned, provisioned, and assured. Leveraging AI and automation capabilities, the solution can introduce:

• Phase 1 (3 months): Deploy real-time network monitoring and unified assurance.
• Phase 2 (6-8 months): Introduce AI-driven problem identification and automated ticket suppression.
• Phase 3 (6-8 months): Implement intent-based automation for real-time network optimization.
• Ongoing: Drive continuous automation enhancements for long-term scalability and efficiency.
• The Expected Impact: Significant Gains for CSPs

These developments intend to yield the following operational gains:

This initiative is just one example of how technology providers are helping CSPs worldwide transition to autonomous networks. With deep expertise in:

• Cloud-native OSS transformation
• AI-driven network intelligence
• Intent-based automation
• We enable CSPs to scale efficiently, improve service assurance, and future-proof their networks.

Discover how we can help accelerate your journey towards Autonomous Networks. Contact us to learn more about our innovative solutions and collaborative opportunities.