Network trends in 2024
Network trends in 2024
The trends and key market expectations driving connectivity standards and networks in 2024 will unlock turnkey innovation, further opportunities, and fresh offerings across telco.
An aerial view
As another year's end approaches, it is customary to endeavor to make technological forecasts with the utmost precision deserving a technologist. Although these exercises may elicit amusement and intrigue, their objectives extend beyond challenging prevailing consensuses. They also aim to expose latent movements frequently disregarded by the conventional network industry.
Notwithstanding the similar ominous circumstances that marked the end of 2022 and amid market unpredictability resulting from the impending recession, supply issues, and war, telecommunications industry market executives and specialists maintain their dedication to cost management, accelerating digital transformation, augmenting service infrastructure monetization, and enhancing market competitiveness.
Let us observe the following compelling network trends for 2024:
- Accelerated monetization with Network & Service Exposure
- AI & GenAI evolution
- Cloud Strategy and the exposure portal
- AIOps & NetOps for ensuring customer visibility & control
Accelerated monetization with Network & Service exposure
To enhance their monetization prospects, communication service providers are perpetually advancing their service infrastructures toward greater programmability and automation.
Service providers (of any kind) aim to enable enterprises to access novel opportunities. From a business-to-business perspective, the activation of newly exposed API capabilities de facto increases the programmability and adaptability of services beyond connectivity to meet a variety of needs and expectations.
API-based network/service exposure, as illustrated in Figure 1, pertains to the potential for CSPs to utilize and access the capabilities and services of others via an exposure portal, as viewed from a B2B2X standpoint. It enables an unparalleled degree of financial gain and facilitates the development of new services through the integration of connectivity, network capabilities, cloud or data services, devices, and network slicing, broadening their service outreach.
![Exposure-based bundling offering]](/sites/default/files/2024-01/network-trends-blog-image-01-opt.jpg)
AI & GenAI evolution
While preparing for intense competition and confronting a new cooperative scenario with hyperscalers, telecommunications operators are under pressure to discover further ways to evolve and transform. AI and generative AI (GenAI) were the focus of numerous telecom providers seeking to enhance consumer experience, revenue, and productivity.
The transformational effect and main benefit of GenAI is its capability to create new contextual content, powered by Deep Learning and Reinforcement Learning to train neural networks based on enormous volumes of data and to apply the latest AI techniques to use models that appreciate where to focus on.
When strategically implemented, GenAI has the potential to significantly transform the telecommunications industry in terms of innovation, productivity, the development of new service concepts, instantaneous modification of service definitions, and charging and billing adjustments based on service consumption. Numerous facets of telecommunications could benefit significantly, including BSS, OSS, data analytics, and even exposure. However, the ubiquitous implementation of Gen AI will not be devoid of obstacles. The telecom industry will be obligated to confront issues of data privacy, security vulnerabilities, and the rectification of AI model flaws.
Cloud strategy leading to API exposure perspectives
Service providers on our small blue planet have been enticed by the prospects of increased efficiency, cost optimization, on-demand cloud, peripheral infrastructure, and expanded reach. As a result, they initially implemented a single-cloud strategy but transitioned to a multi-cloud approach.
Telcos are driven to employ a Techco or Digital Service Provider (DSP) strategy for a variety of reasons:
- Increase demand for and utilization of cloud-based products and services
- Transitioning from proprietary to native cloud tools
- Convert private clouds to hybrid/public clouds
- Integrate with hyperscalers that offer more appealing and innovative solutions Integrate strategic duties gradually into hyperscaler platforms NFVi/CNFi software layers, Next-Gen OSS, AI/ML, data-driven functionalities, and more
A DSP/Techco cloud strategy may have as its ulterior motive the development of multiple monetization models, with API and network exposure constituting a principal component of their strategy for the next generation of services. API Network and service exposure would operate as an abstracted service layer function consisting of three primary components—Orchestration/Monetization/API management—to facilitate third-party partners' resale of their services/function assets in conjunction with those of hyperscalers and to increase return on investment.
AIOps & NetOps for ensuring customer visibility & control
While Service Providers of all shapes and sizes accelerate their digital transformation with the help of AI and cloud-native technologies, performance monitoring undergoes an additional, covert transformation. The utilization of Cloud Native has enabled the streamlining of network operations and the incorporation of cloud services into operations. Consequently, network deployments have become more decentralized and reliant on automation tools. However, this has also necessitated an alternative approach to performance monitoring, such as AIOps and NetOps.
AIOps is a contemporary methodology that involves the utilization of Artificial Intelligence and associated technologies, including Machine Learning, to manage IT operations. From this standpoint, AIOps facilitates the work of IT operation professionals (DevOps or SRE teams) by enabling them to detect and resolve issues before the disruption of services and customers using observability and algorithmic analysis of IT data. In summary, AIOps can reduce operational expenses, expedite innovation, enhance employee productivity, and optimize the overall customer experience, thereby fostering customer loyalty and retention.
Conversely, NetOps uses DevOps' agility to manage, expand, and scale network management capabilities. Service infrastructure is monitored as closely as hardware components by NetOps tools, which automatically gather network health data from layers. NetOps personnel may then analyze the data to customize network components for end-to-end customer support to provide the optimum experience. NetOps helps with quicker and leaner deployments, continual upgrades, proactive/predictive (with AI) cross-domain remediation, granular visibility, and speedier troubleshooting.
AIOps and NetOps work well together, especially NetOps teams' efforts to optimize networks and service infrastructure. Network operation teams use DevOps tools and methodologies, but AIOps and ML (Machine Learning) technologies should not be overlooked as service infrastructure becomes more disaggregated and private, public, or hybrid clouds and edge computing increase complexity.
A final word about 2024 network trends
These network trends for 2024 are forward-thinking as they are thought-provoking. Except for a few anticipated developments that will streamline operations across service domains and enhance the end-user experience, vendors have historically been sluggish in adopting cloud-native principles.
The increasing adoption of network and service exposure is expected to primarily stimulate a domino effect that leads to the development of new models, and consequently, monitoring and service capabilities whose immense potential we have yet to fully comprehend.
Having said that, Amdocs continues to be committed to aiding all your digital pursuits.
May peace, warmth, and acceptance find us all in 2024.
