In an insightful interview with TimesTech, Mr. Pinkesh Kotecha, MD and Chairman of Ishan Technologies, delves into the strategic integration of Artificial Intelligence (AI) and Machine Learning (ML) in the telecom sector. He shares perspectives on optimizing network performance, predictive maintenance, customer interactions, cybersecurity, and the pivotal role of AI in the successful implementation of 5G networks.
Read the full interview here:
TimesTech: How do you envision AI and ML being strategically integrated into telecom operations for enhanced efficiency?
Mr Pinkesh: The strategic integration of Artificial Intelligence (AI) and Machine Learning (ML) into telecom operations is poised to revolutionize efficiency in various dimensions. AI and ML algorithms can be strategically employed to optimize network performance, automate routine tasks, and predict potential issues, leading to enhanced operational efficiency. By leveraging predictive maintenance through these technologies, telecom operators can minimize downtime, improve network reliability, and streamline maintenance processes. This proactive approach ensures that network resources are efficiently utilized, contributing to an overall improvement in service quality.
Moreover, AI and ML-driven analytics play a pivotal role in understanding customer behavior. Telecom operators can harness these insights to tailor services, allocate resources more effectively, and enhance the overall customer experience. The ability to make data-driven decisions empowers operators to respond more agilely to dynamic industry demands, fostering a competitive edge. The anticipated market value of $10.4 billion by 2030, as projected by SkyQuest, underscores the transformative potential of these technologies in the telecom sector. In essence, the strategic integration of AI and ML is a cornerstone for unlocking operational efficiency, ensuring robust network management, and delivering tailored services to meet the evolving needs of the telecommunications landscape.
TimesTech: How can AI and ML contribute to network optimization and predictive maintenance for reliable telecom infrastructure?
Mr Pinkesh: In the ever-evolving landscape of the telecommunications industry, the challenges posed by factors like data collection complexities, technology immaturity, scalability issues, budget constraints, and a shortage of specialized skillsets highlight the pressing need for innovative solutions. AI and ML emerge as technologies that effectively address these challenges, revolutionizing the way telecom operators manage and optimize their networks.
AI and ML play a pivotal role in optimizing networks by leveraging data-driven projections. Through the analysis of historical data, these technologies predict future network demands and facilitate optimized resource allocation based on traffic patterns. In predictive maintenance, AI and ML anticipate and prevent potential network failures by implementing proactive measures, utilizing both historical data and real-time performance metrics. The sophisticated analytics identify potential faults, such as minor signal fluctuations in fiber networks, allowing for preemptive actions to prevent major service disruptions. Additionally, the segmentation of data by industry or geographic region enables targeted enhancements, predicting peak data usage in specific industries during peak hours and identifying regions experiencing recurrent network issues.
TimesTech: What transformations do you anticipate in customer interactions and service delivery through AI and ML in the telecom sector?
Mr Pinkesh: The integration of AI and ML in the telecom sector is poised to usher in transformative changes in customer interactions and service delivery. Beyond conventional chatbot applications, these technologies are revolutionizing user experiences through enhanced personalization. By analyzing extensive customer data, AI and ML algorithms anticipate preferences and behaviors, allowing telecom companies to offer tailored services, ensuring a more engaging and relevant customer experience. Moreover, predictive issue resolution is a key aspect, where these technologies proactively address potential service issues before they impact customers, minimizing downtime and disruptions.
AI-powered chatbots and virtual assistants are providing smart recommendations and real-time assistance, improving self-service options and accelerating issue resolution. This not only enhances customer satisfaction but also streamlines support processes. The data-driven insights derived from AI and ML analysis of customer feedback and usage patterns are instrumental in continuously improving services. Telecom companies can adapt their offerings based on these insights, ensuring a proactive approach to service enhancement.
Automation, driven by AI, is transforming service delivery processes, from activation to billing and beyond. This acceleration of service provisioning reduces manual intervention and enhances overall efficiency. Additionally, predictive analytics for network optimization is a crucial application, where AI analyzes network traffic and usage patterns to predict peak times and adjust network capacity. This proactive approach ensures network stability and better service delivery during high-demand periods. As the global telecommunications industry witnesses a surge in the adoption of AI, its projected growth from $1.2 billion in 2021 to an estimated $38.8 billion by 2031 reflects its pivotal role in shaping the future of customer interactions and service delivery in the telecom sector.
TimesTech: How can AI and ML technologies bolster security and prevent fraud in telecom networks?
Mr Pinkesh: With the increasing cyber frauds in India, particularly involving spam calls, messages, and other malicious activities, ensuring robust cybersecurity has become a concern for telecom operators. India, being the second biggest source of spam bots after China, faces a significant threat landscape. According to Spamhaus Project, as of 29 March, there were nearly a million active spam bots in the country. These bots are predominantly utilized for phishing, click fraud, DDoS attacks, and various other malicious activities.
In this challenging scenario, AI and ML technologies play a pivotal role in fortifying security measures. These advanced algorithms empower telecom networks to swiftly identify patterns indicative of fraud, allowing for proactive measures such as blocking access to potential hackers and safeguarding sensitive user data. Companies, recognizing the severity of the threat landscape, must consider specialized ICT providers like Ishan Technologies, which excel in both cybersecurity and telecom services. The comprehensive solutions leverage AI and ML to effectively combat emerging threats, offering telecom companies robust tools to counteract fraud and create a secure communication environment for their users.
TimesTech: What role will AI play in the successful implementation and management of 5G networks, and what benefits can businesses expect?
Mr Pinkesh: With 5G serving as a catalyst for enhanced connectivity and reduced latency, the synergy with AI promises an elevated customer experience by minimizing the time required to deliver services promptly. Moreover, AI contributes significantly to operational improvements, particularly in the context of automation.
Automation, a core aspect facilitated by AI, plays a crucial role in streamlining the instantiation of services that span multiple technology domains within the Communication Service Provider (CSP) landscape. As wireless and wireline convergence becomes indispensable, AI-driven automation extends across various CSP domains, including Radio Access Network (RAN), transport, 5G Core and CS domain. Observability and automated service repairs are further bolstered by AI/ML capabilities, enhancing the overall reliability and performance of 5G networks. In essence, AI emerges as a cornerstone for the seamless deployment, management, and optimization of 5G networks, offering businesses unprecedented efficiency, reliability, and adaptability in the evolving digital landscape
TimesTech: What challenges and opportunities do you foresee in integrating AI and ML in the telecom sector, and how can businesses proactively address them?
Mr Pinkesh: Indian telecom companies are at the threshold of integrating AI and ML into their operations. While there is progress, a significant number of telcos, around 87%, have initiated the implementation of AI into their network operations, primarily in proof of concepts or production. However, only 57% have fully deployed telco AI use cases to the point of production, highlighting that there’s room for more extensive adoption. This situation presents both challenges and opportunities for the sector.
As the industry faces increasing cost pressures and strives to keep pace with evolving technologies like 5G, IoT, and cloud computing, the financial commitment required for the adoption of AI and ML can be a hurdle. Infrastructure challenges also loom large, with the sector already grappling with labor shortages, staffing difficulties, and the increasing complexity associated with the 5G rollout.
Despite these challenges, there are significant opportunities for telecom businesses in leveraging AI and ML. These technologies can enhance operational efficiency, streamline network management, and contribute to a better customer experience. The advent of 6G, with its heightened capabilities, further underscores the potential benefits of AI/ML integration. Proactive measures involve strategic planning for investments, addressing infrastructure needs, and fostering a skilled workforce to manage AI and ML implementations effectively. Establishing an independent statutory authority, as suggested by TRAI, can play a crucial role in ensuring responsible AI development and regulation of use cases in India, providing a structured framework for telecom companies to navigate the challenges and harness the opportunities presented by AI and ML integration.
