At the 18th edition of the Telecom Review Leaders’ Summit, the panel titled, ‘Artificial Intelligence: What it Means for Telcos and Consumers,’ explored the transformative role of artificial intelligence (AI) in reshaping the telecom industry and its impact on consumer experiences.
Industry experts explored how autonomous networks are enhancing business value, especially in the context of 5G-Advanced technologies.
Moderated by Olivier Leroy, Head of PMP Strategy Datalab, the discussion brought together prominent industry leaders, including Ned Taleb, CEO, Reailize; Mounir Ladki, President and CTO, MYCOM OSI; Paweł Workiewicz, VP and Head of Business Development Division APAC & MEA, Comarch; Monty Hamilton, Chief Product and Marketing Officer, TELUS; Benedetto Spaziani, GM and EMEA President, Netcracker Technology; Mohamed Bakry, Director of Solutions Engineer, Cisco; Samer Geissah, Customer Team Head and Client Executive for du, Nokia; and Dr. Mahmoud Sherif, Head of Innovation & Technico-Business Development, du.
Monetizing Telecom Services with AI
Dr. Sherif highlighted AI's significant role in monetizing telecom services, starting with marketing. By leveraging AI, telecom companies can create highly personalized customer experiences, understanding their customers’ needs more deeply. "Marketing is number one," the du Innovation Head emphasized, stressing that AI's ability to drive personalized engagement is critical in today's competitive landscape.
The panelists mentioned that another avenue for monetization is AI-as-a-Service (AIaaS). By leveraging robust cloud infrastructure and data repositories, telecom companies are well-positioned to offer AI services to other enterprises. "AI needs cloud and data. So, who better to handle AI-as-a-Service for enterprises against telecoms?" he asked, illustrating the unique advantage of telecom operators in this space.
The integration of edge AI is also becoming crucial. Dr. Sherif explained that, "AI is not only about running the AI engine on the cloud; It's [about] getting closer and closer to being within the device itself." This shift allows faster and more efficient data processing, enabling use cases such as image recognition directly on cameras without cloud dependency.
AI-Optimized Networks
Regarding network optimization, the panelists emphasized AI's growing importance in managing increasingly complex telecom networks. As networks scale and demand for higher reliability grows, AI will increasingly be used to automate network management and enhance performance.
Furthermore, AI is already revolutionizing customer service by utilizing virtual assistants. Sherif remarked, "I think we've heard, over two days, about the virtual assistant for call centers, agents, and so on. This is very valid."
AI for Autonomous Networks and Data Unification
As telecom companies aim to achieve autonomous networks, several experts provided insight into how AI is driving this transformation. Ladki discussed the challenges of 5G slicing—a technology that is yet to live up to its revenue potential, partly due to operational complexities. "The key challenge is the utter complexity [required] of the operations to deliver this kind of slicing, real-time, on-demand," he explained. He believes autonomous networks and generative AI (GenAI) are key to overcoming these challenges.
Geissah echoed this sentiment, emphasizing that AI agents are becoming critical in network planning and optimization. Their approach involves creating AI agents that simulate real-world scenarios to optimize network management. "We simulate it internally, and then we start to create, optimize, and plan," the Nokia representative shared.
Comarch also underscored the importance of data unification in enabling autonomous networks. Workiewicz stated, "Data consistency and high quality data are necessary if we want to make our network autonomous." Comarch’s MIRA module, which analyzes unified data for recommendations, exemplifies this approach. Comarch has already reached Level 4 autonomy and is working with clients to enhance their AI-driven decision-making processes further.
Spaziani also emphasized the role of AI in creating autonomous networks. Netcracker's AI-driven approach enables operators to streamline operations and make more informed, real-time decisions, improving efficiency and reducing costs. "AI allows us to transform operations, enabling autonomous network management and greater operational agility," Spaziani explained, highlighting Netcracker's focus on data-driven decision-making.
AI in Customer Experience and Public Safety
On the customer experience front, Taleb discussed the possibility of using AI to enhance training times for customer service agents. "We're reducing the training time from five or six weeks down to 2 or 3 weeks," he highlighted, showcasing how AI can improve efficiency and employee retention.
Meanwhile, Hamilton pointed out the significance of 5.5G’s low latency capabilities, which can be leveraged to enable AI-driven applications in autonomous vehicles and public safety. For instance, AI-powered traffic management and connected ambulances are being developed, which benefit from the ultra-low latency provided by 5.5G. The TELUS representative noted, "With 5.5G low latency, you can take a lot of the compute power in every vehicle and put it on the edge."
Ethics and Responsible AI
AI's ethical considerations were also examined. Bakry discussed Cisco’s commitment to ethical AI, having created a framework based on six principles: transparency, fairness, accountability, privacy, security, and availability. The company has even formed a committee involving various departments to ensure comprehensive governance of AI initiatives. "This is a holistic framework that talks about every single aspect of how to maintain and keep the ethics within the work of AI," Bakry emphasized.
Notably, TELUS’s Fuel iX platform became the first ISO-accredited AI platform, achieving privacy by design and setting standards for responsible AI practices. "We believe it's our role not just to build our backyard and drive these outcomes; we believe it's our role to lead the industry forward," Hamilton reiterated.
The Role of Gen Z in AI Innovation
The Gen Z workforce brought a fresh perspective to the discourse on innovation, particularly when the speakers highlighted the growing influence of younger employees in driving AI and automation projects. Their proficiency in programming languages like Python and their adept use of intuitive digital tools position them as pivotal drivers of innovation within telecom companies.
This emphasis on Gen Z's tech-savviness underscores a broader trend where younger generations are leading the charge in adopting and advancing AI. By harnessing their skills and enthusiasm, companies can accelerate AI integration and foster a culture of innovation.
Looking Ahead
In closing, Ladki shared his final thoughts on AI's transformative potential in the telecom industry. He emphasized the vast opportunities AI can unlock, particularly in terms of 5G slicing. Reflecting on the earlier discussion, he stated, "Forty minutes ago, I spoke about slicing... This is a big opportunity for the industry." He explained that AI could be a key enabler in monetizing 5G by optimizing data usage. "Today, data is a goldmine that is largely untapped."
Ladki shared that MYCOM OSI is working with customers and processing 100 billion data records per hour, as well as normalizing and correlating this massive data flow. With the application of generative AI, he sees "limitless possibilities" for extracting value from this data. "There is a massive untapped opportunity; it's available even now," he urged, calling for the industry to act swiftly and seize the moment to capitalize on these emerging opportunities.
In summary, AI is transforming the telecom industry by enabling monetization through innovative services, optimizing operations for greater efficiency, advancing network autonomy with self-healing capabilities, and enhancing customer experience through personalization and faster resolutions.
However, the industry is still in its nascent stages, with many companies focusing on foundational steps like data unification, AI ethics, and automation before moving to full autonomy.
