By Markus Persson, Global Industry Director for Telecom at IFS
As the deployment of 5G unfolds, Telecommunications Service Providers (TSPs) find themselves under pressure from all sides. Connectivity, once a premium service, is now deemed a basic human right according to the UN. Relying solely on airtime sales is no longer sufficient to cover expenses, and the strain is evident. In August 2023, T-Mobile US announced a reduction of 5,000 jobs (7%) in the US. Similarly, AT&T has slashed 45,000 jobs over the last two years, and Verizon has seen a loss of 18,000 positions.
The surge in network traffic volumes brings a proportional increase in the burden and cost of storing and managing Big Data. To stay competitive, operators must turn to rapid automation, optimization, and diversification of their business. This blog delves into the role of Artificial Intelligence (AI) in helping operators cut costs and transform the data challenge into a revenue-generating opportunity. Additionally, it explores how AI is driving automation in the telecommunications sector.
The Challenge of Data: Enhancing Data Literacy and Harmonization in Telecommunications
The telecommunications industry is undergoing a substantial transformation driven by the rapid growth of valuable data and the utilization of AI to discover new revenue streams. To fully unlock the potential of AI and automation, individuals and organizations in the sector must prioritize developing data literacy and ensuring data harmonization. In a landscape influenced by personal data, preferences, and biases, data literacy becomes essential for telecommunications organizations. It enables them to efficiently collect, structure, and extract insights from their operations.
Despite AI’s capability to process Big Data swiftly and accurately, a significant challenge arises from the diverse versions of systems used by telecom operators. This complexity makes it difficult for AI engines to comprehend the data fully. Solutions like IFS Cloud address this challenge by providing a unified platform and master data set, emphasizing data harmonization for consistency and accuracy across the entire business. Interestingly, research commissioned by Nokia reveals that despite 87% of surveyed operators initiating AI implementation in their network operations, legacy systems with proprietary interfaces hinder their access to high-quality data sets required for swift AI integration. Only 6% expressed confidence in successfully applying AI and machine learning algorithms for achieving ‘zero touch’ network operations.
AI: Tackling 5G Slicing and Mobile Edge Challenges
Network slicing involves creating multiple virtual networks on a shared physical infrastructure, each with distinct characteristics and service level agreements (SLAs). Mobile edge computing deploys applications and services at the network edge to enhance performance and reduce latency. Both technologies empower operators to offer flexible, scalable, and efficient services to diverse customer types. Effectively implementing these approaches requires operators to understand customer segment needs and associated costs. AI becomes crucial in this process by helping telecom operators analyze network data to inform decision-making. AI assists operators in:
- Analyzing usage patterns, preferences, and pain points to identify customer segments and industries that could benefit.
- Discovering use cases like enhanced mobile broadband, massive IoT, ultra-reliable low-latency communication, smart cities, smart manufacturing, and autonomous driving.
- Evaluating the feasibility and profitability of each use case.
- Designing, optimizing, and managing the network slices and mobile edge applications necessary for implementation.
Expanding AI Utilization in Telecommunications
AI in telecommunications offers significant benefits, such as processing vast data for valuable customer insights and predicting future demand. It enhances efficiency by automating routine tasks, like customer service inquiries, leading to improved satisfaction and reduced workload for human agents. Additionally, AI-driven solutions like IFS Planning and Scheduling Optimization in IFS Cloud streamline resource scheduling, exemplifying the industry’s adoption of advanced AI-based software for real-time optimization.
Creating new revenues: B2B networks and industrial use cases
The innovative business possibilities, particularly in B2B and industrial mobile networks, facilitated by the sector’s integration of AI, are already emerging. For instance, according to Telecoms.com, Ericsson has established a dedicated 5G SA network capable of supporting data collection through connected robots, livestock monitoring, and agricultural automation. The 5G connectivity will link farms, enabling robots equipped with stereoscopic cameras to collect phenotyping data. The network coverage spans local crop and livestock farms as well as parts of the city of Ames.
In addition to the leading functionalities of ERP, EAM, FSM in IFS Cloud, the recent acquisition of Industrial AI software company Falkonry, Inc. introduces AI-powered anomaly detection capabilities to the IFS roadmap. This self-learning solution continually monitors extensive data for assets, machines, systems, and industrial processes, identifying and analyzing unusual behavior and causes of failures.
Cutting-edge technologies like network slicing and mobile edge computing serve as catalysts for novel business models and opportunities within the telecom sector. Employing AI-driven solutions like IFS Cloud to explore potential use cases empowers operators to distinguish themselves, providing more personalized, customized, and optimized services compared to their competitors. The crucial role of data harmonization ensures operators access high-quality, consistent, and comprehensive network data, feeding into their AI algorithms. The synergy of data harmonization and AI-enabled enterprise software, such as IFS Cloud, facilitates the transformation of operators’ networks into agile platforms, enabling the analysis of data for innovation and value creation.
Curious about unlocking the value of AI in the telecommunications industry? Discover how IFS Cloud empowers CSPs to establish a robust foundation for AI success here.