Claudio Saes, a partner and telecom practice leader at Nokia Bell Labs Consulting, emphasizes the importance of integrating artificial intelligence (AI) in the telecommunications industry. AI can help firms in improving operations, enhancing customer experiences, and driving revenue growth. Saes shares his insights on strategically implementing AI, focusing on AIOps and generative AI and their impact on the telecom sector.
AIOps, which combines big data and machine learning, can automate and enhance IT operations processes. Telcos can benefit from proactive and predictive maintenance, reducing time-to-resolution for issues and optimizing network performance. By integrating AIOps, telcos can achieve autonomy in operations, leading to enhanced service reliability and reduced operational costs. Statistics show that telcos with autonomous networks have achieved improved operational efficiency and reduced OPEX over the past two years.
Generative AI and large language models like OpenAI’s GPT are gaining attention for creating new and realistic content. Telecom operators are utilizing this technology to enhance human-machine interactions and drive creativity and efficiency. AI tools can increase employee productivity by automating tasks, enhance customer care operations, and create new services like personalized customer experiences and automated chatbots. In network and service design, AI can provide actionable insights, streamline processes, and offer predictive insights for network management.
Telcos globally are leveraging AI to transform operations and service offerings. Companies like SK Telecom and Deutsche Telekom are developing telco-specific LLMs to protect intellectual property, reduce costs, and accelerate time-to-market for new services. These models cater to the telecom industry’s unique needs, ensuring higher relevance and effectiveness compared to generic AI solutions. Despite the benefits, implementing AI in telcos can be challenging due to concerns like data privacy, ethical considerations, and high energy consumption.
To address these challenges and maximize benefits, Saes recommends a structured approach focusing on executive alignment, building AI capabilities through a Center of Excellence, and prioritizing “Clear Win” use cases for initial implementation. Successful AI adoption requires a multidisciplinary approach, combining expertise from network operations, IT, and business units. As AI technologies evolve, their impact on the telecommunications industry is expected to grow, enhancing network autonomy, improving customer experiences, and driving innovation in service offerings. Continuous investment in AI capabilities, strategic partnerships, and a commitment to innovation are essential to staying ahead in the AI-driven telecom landscape.
