Claudio Saes, a partner and telecom practice leader at Bell Labs Consulting, part of Nokia Bell Labs, shares insights on the integration of artificial intelligence (AI) in the telecommunications industry. AI is proving to be a strategic tool for improving operations, enhancing customer experiences, and driving revenue growth in the fast-evolving telco sector. Saes highlights the importance of understanding how AI, particularly in areas such as AIOps and generative AI, is reshaping the future of telcos.
AIOps, a framework combining big data and machine learning, automates and enhances IT operations processes in telcos. The TM Forum has expanded AIOps to include network IT, service, and business operations, leading to increased operational efficiency and reduced operational expenditures for telcos implementing autonomous networks. Saes emphasizes the potential of AIOps to provide proactive and predictive maintenance, ultimately optimizing network performance and service reliability for telcos seeking an edge in the market.
Generative AI and large language models like OpenAI’s GPT are proving beneficial for enhanced human-machine interactions and creativity in telecom operators. Saes discusses the various applications of generative AI in telcos, including improving employee productivity, enhancing customer care operations, creating personalized experiences, targeted marketing, and automated chatbots. He further highlights how AI tools can streamline network and service design processes by providing actionable insights, testing, performance optimization, anomaly detection, and predictive insights for network management.
Globally, telcos are leveraging AI to revolutionize operations and service offerings. Companies like SK Telecom and Deutsche Telekom are developing telco-specific large language models to protect intellectual property, reduce costs, and accelerate new service launches. By tailoring AI solutions to the telecom industry’s unique needs, these companies aim to achieve higher relevance and effectiveness compared to generic AI systems. Saes underscores the significance of addressing challenges such as data privacy, ethical considerations, and energy consumption in AI implementation for telcos to maximize benefits.
To address these challenges effectively, Saes recommends a structured approach encompassing a comprehensive AI strategy with executive alignment, investments in building AI capabilities through a Center of Excellence, and prioritizing “Clear Win” use cases for initial implementation. By dedicating resources, investing in talent, and focusing on areas with immediate impact, telcos can kickstart their AI journey and demonstrate tangible value across customer-facing applications and internal operations. Saes highlights the importance of a multidisciplinary approach in successful AI adoption, combining expertise from IT, network operations, and business units.
Looking ahead, Saes predicts a continued growth in the impact of AI technologies on the telecommunications industry, with advancements likely to enhance network autonomy, improve customer experiences, and drive innovation in service offerings. To navigate this AI-driven landscape, Saes advises telcos to focus on continuous investment in AI capabilities, strategic partnerships with technology vendors, and a strong commitment to innovation. As the telecommunications industry evolves, embracing AI strategically will be crucial for telcos looking to stay competitive and meet the demands of a rapidly changing digital landscape.
