Accelerating the adoption of autonomous networks: It is not optional anymore

However, adoption has been slow, considering obstacles such as integration challenges, the lack of skills, and organizational inertia toward embracing change.

As many as 83% of CSPs are at level 1 or 2 autonomy for their overall network, based on TM Forum’s six-level autonomous network maturity model. To move up the maturity curve, CSPs need to recalibrate their organizational capabilities on both technological and cultural fronts.

Drivers of Autonomous Networks

Autonomous operations and network management are crucial for CSPs to transition to 5G to realize the full business potential of the latest wireless technology. With that, it will be easier for CSPs to handle tasks such as network optimization, provisioning, supervision, and maintenance and manage the exponential increase in data traffic and connected devices. Besides technology drivers, CSPs stand to make business gains by adopting autonomous networks.

Customer satisfaction: McKinsey research shows that 73% of senior telecom executives want to leverage CX as a differentiating factor to create value. Customer-facing autonomous network use cases focus on understanding subscriber behavior and taking proactive corrective actions to improve customer satisfaction and retention. For instance, AI-powered microanalysis enables CSPs to assess network performance, such as latency at the customer level, predict failures, and improve the reliability of the network. The end outcomes are improved service quality and customer satisfaction.

Cost efficiency: Autonomous networks enable CSPs to optimize operations and maintenance, reduce operational expenditure, and improve profitability as revenue from traditional telecom services remains static. With automation, CSPs do not have to keep expensive resources to conduct routine tasks such as provisioning and fault detection, thus lowering costs and the turnaround time from weeks to days.

New revenue opportunities: Autonomous networks offer CSPs new revenue streams, such as network slicing for tailored enterprise solutions, predictive maintenance, and data monetization through analytic services to third parties. Analysys Mason reports that 43% of CSPs consider revenue generation among the top three automation drivers.

Promoting sustainability: Autonomous networks deliver sustainability benefits with reduced energy consumption, intelligent workload management, and optimal resource utilization. Japan-based CSP, KDDI, implemented network energy management using Machine Learning (ML) to create models that utilized real-time data to assess demand on the network and adjust power consumption by RAN resources to match demand.

Top factors hindering adoption

Despite demonstrated benefits, implementation has been slow because CSPs must expertly navigate an ecosystem with rapid technological evolution. They must co-opt partners, including vendors, system integrators, hyper-scalers, and software providers, to keep pace with change and manage implementation challenges.

Cultural challenges, such as changing employee mindsets and behaviors, are among the top challenges CSPs face. Network operations have evolved, and the skills required to manage them have changed tremendously. Simultaneously, the telecom business has become more customer-oriented, requiring organizational cultural transformation to become customer-focused and innovative for successfully implementing emerging technologies.

Integrating autonomous network solutions into existing network architectures and operations is also impeding adoption. Many CSPs have legacy network infrastructure and proprietary hardware that may not be compatible with or optimized for autonomous network technologies. TM Forum research reveals that 58% of CSPs find integrating solutions at different levels challenging.

Another challenge is the unavailability of talent, as CSPs require specialized skills in areas such as AI, ML, automation, and Software-Defined Networking (SDN). Close to half (43%) of CSPs believe they lack the skills needed for autonomous networks.

In addition to internal challenges, CSPs must overcome regulatory issues related to data sovereignty, data protection, and AI regulations that can hinder progress.

Multi-year, multi-step approach

Attaining higher levels of autonomy entails a multi-year journey requiring a C-level strategy and vision encompassing data management, security, sustainability, and employee upskilling. Some telcos have taken a domain-led approach, selecting 1-2 network domains over others for autonomy use cases. ROI considerations are key factors guiding such decisions. Such strategies must be aligned with the broader business goals and outline the objectives, scope, timeline, and Key Performance Indicators (KPIs) for adoption.

Considering the complexities involved, the adoption journey must be broken into manageable phases, starting with low-risk use cases and applications delivering tangible benefits. Progress tracking requires clearly defined success metrics against milestones and industry benchmarks.

It is equally important to appoint a dedicated leader for the transition program. The leader will be responsible for establishing the business case with the right use cases, driving technology investments, creating an ecosystem of partners, and championing change within the organization.

Autonomous networks are the neural pathways that power today’s economy and society as the world moves increasingly toward touchless transactions and data-driven, intelligent processes. Higher levels of autonomy will soon become critical, and not optional, to retain a competitive edge in this scenario.