Reigniting Growth in the Telecom Industry with AI and Cloud

The telecom industry is at a crossroads. While demand for connectivity continues to surge, operators face stagnating revenues, rising costs, and increasing competition. In his keynote at the Brooklyn 6G Summit 2024, Manish Singh, CTO of Telecom Systems Business at Dell Technologies, outlined a compelling vision for how AI and cloud-native networks can reignite growth in the sector.

The Growth Challenge in Telecom

The traditional telecom business model is under pressure. Operators are struggling with:

• Revenue stagnation despite increasing data consumption.
• Rising operational costs driven by legacy infrastructure and inefficient processes.
• Intensifying competition from hyperscalers and alternative connectivity providers.

To overcome these challenges, Manish argues that telcos must embrace AI-native and cloud-native architectures as fundamental enablers of transformation.

AI: The Catalyst for Intelligent Networks

AI is not just an add-on; it must be at the core of future telecom networks. Manish highlighted several ways AI can drive growth:

• Automation of network operations: AI-driven predictive maintenance and self-optimising networks reduce downtime and operational expenses.
• Enhanced service delivery: AI enables hyper-personalised customer experiences and intelligent traffic management.
• Operational efficiency: AI optimises energy consumption, spectrum allocation, and overall network resource utilisation.

Manish emphasised that AI-native networks will be a defining feature of 6G, making networks more autonomous, efficient, and scalable.

Cloud-native Architectures: The Foundation for Scalability

Moving beyond traditional, hardware-centric networks is essential. Manish advocates for a cloud-first approach, where telecom networks are:

• Software-defined and virtualised, reducing dependence on costly proprietary hardware.
• Highly scalable, allowing operators to adjust capacity dynamically.
• Interoperable and open, fostering innovation through Open RAN and disaggregated networks.

By embracing cloud-native principles, telcos can accelerate service delivery, reduce costs, and stay competitive in an increasingly software-driven ecosystem.

AI Infrastructure: Scaling from Edge to Core

A key enabler of AI and cloud-native networks is the AI Factory approach, which provides scalable infrastructure from mega-scale data centres to the edge. Manish highlighted how AI workloads must be supported across different network layers—from on-premise enterprise deployments to far-edge, near-edge, and core data centres.

Dell Technologies' AI Factory is designed to:

• Support diverse AI edge use cases in telecom.
• Handle power and cooling constraints, crucial for efficient AI model training and inference.
• Leverage cloud-native architectures to ensure seamless scalability and automation across the entire network.

This modular infrastructure ensures that telecom networks can efficiently process AI workloads at every layer, enabling real-time decision-making and optimised operations.

Overcoming Challenges in AI and Cloud Adoption

Despite the clear benefits, Manish acknowledged key barriers:

• Legacy infrastructure: Transitioning from traditional networks requires significant investment.
• Security and privacy concerns: AI-driven automation raises questions about data integrity and network security.
• Industry mindset shift: Operators must adopt a culture of innovation and rapid iteration.

Addressing these challenges requires industry-wide collaboration, strong partnerships with cloud providers, and a commitment to open innovation.

Conclusion: The Time to Act is Now

Manish’s message to the industry was clear—AI and cloud are not future aspirations; they are essential for telecom survival and growth. By leveraging AI-native automation and cloud-native architectures, operators can reignite growth, drive efficiency, and prepare for the 6G era.

Watch Manish Singh’s full keynote embedded below:

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Beyond KPIs: The Role of Key Value Indicators (KVIs) in 6G

Key Performance Indicators (KPIs) have long been the primary benchmarks for evaluating mobile network performance. However, as 6G moves towards a broader societal and environmental impact, the European Hexa-X-II project and its partners advocate for integrating Key Values (KVs) and Key Value Indicators (KVIs) into network design and evaluation.

On 18 December 2024, Hexa-X-II hosted an insightful webinar to highlight the significance of KVIs in shaping the future of 6G. The session underscored how KVIs can complement KPIs by assessing technology’s impact on sustainability, digital inclusion, trust, and ethical considerations. 

While the video hasn't been shared, you can download the slides from here.

Why KVIs Matter in 6G Development

Traditionally, mobile network development has been driven by KPIs—throughput, latency, reliability, and spectrum efficiency. However, as 6G aims to support broader global goals such as the UN Sustainable Development Goals (SDGs), a shift towards value-based design is necessary. Hexa-X-II proposes a structured methodology where:

• Human and Planetary Goals are identified (e.g., sustainability, digital inclusion, trust).
• Key Values (KVs) are derived from these goals to reflect technology’s intended benefits and potential risks.
• Key Value Indicators (KVIs) provide qualitative or quantitative measures to assess whether these values are met.

From Theory to Application: The Hexa-X-II Process

One of the core challenges in applying KVIs is the interdisciplinary nature of the assessment. Unlike KPIs, which are primarily technical, KVIs require social, economic, and environmental considerations. The Hexa-X-II approach includes:

• Defining Use Case KVIs, which assess the impact of a specific application.
• Defining Enabler KVIs, which measure how well a technical enabler (e.g., AI, NTN, RIS) contributes to key values.
• Mapping KVIs to existing KPIs where possible and identifying gaps where new indicators are needed.
• Iteratively refining KVIs based on real-world evaluations.

A Case Study: Cooperating Mobile Robots

One example discussed in the webinar was the use of cooperating mobile robots, a use case that benefits from 6G-enabled ultra-reliable low-latency communication (URLLC). While KPIs can measure performance (e.g., latency, reliability), KVIs help evaluate the broader impact, such as:

• Environmental KVIs: Energy efficiency, material usage, electronic waste reduction.
• Social KVIs: Job displacement vs. job creation, worker safety, accessibility.
• Economic KVIs: Business viability, affordability, and risk of monopolisation.

By systematically assessing these factors, the Hexa-X-II framework ensures that 6G technology is not just high-performing but also aligned with societal needs.

Lessons Learned and Future Outlook

The adoption of KVIs presents several challenges, including subjective assessments, measurement difficulties, and the need for multi-stakeholder collaboration. However, Hexa-X-II emphasises that:

• Technology impact should be continuously monitored using KVIs.
• Qualitative and quantitative assessments must be combined, rather than relying solely on measurable KPIs.
• A system-level approach is required, integrating perspectives from sustainability, business, and social sciences.

As 6G research advances, KVIs will play a crucial role in ensuring that next-generation networks contribute meaningfully to global sustainability and inclusivity. The Hexa-X-II initiative provides a foundational methodology for integrating values into the traditionally KPI-driven telecom landscape — an approach that could redefine how we measure success in the 6G era.

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Lessons from ANRW ’24: AI and Cloud in 5G/6G Systems

The ACM, IRTF & ISOC Applied Networking Research Workshops (ANRW) offer a vibrant forum for researchers, vendors, network operators, and the Internet standards community to exchange emerging results in applied networking research. To foster collaboration across these diverse groups, ANRW events are co-located with IETF standards meetings, typically held annually in July. These workshops prioritise interactive discussions and engagement, complementing traditional paper presentations.

ANRW '24, held on 23 July 2024 at the Hyatt Regency Vancouver, brought together industry leaders and academics to share insights on advancing networking technologies. Among the standout sessions was a keynote presentation by Sharad Agarwal, Senior Principal Researcher at Microsoft. His keynote titled, "Lessons I Learned in Leveraging AI+ML for 5G/6G Systems", highlighted pivotal themes influencing telecom and networking.

Sharad distilled his experiences into three key lessons, each underscored by examples of research and systems developed to address specific challenges in the telecom industry:

1. Leverage Cloud Scale to Overcome Limitations of Deployed Protocols: He emphasised that the scale of cloud computing is critical to managing the massive demands of modern telecom networks. For instance, systems like TIPSY (Traffic Ingress Prediction SYstem) demonstrate how AI and ML can predict traffic ingress points across thousands of peering links, helping to avoid bottlenecks and ensure optimal traffic distribution.
2. Custom Learning Algorithms vs. Off-the-Shelf Solutions: While bespoke algorithms offer higher precision for niche applications, their complexity and deployment challenges often outweigh their benefits. Sharad argued for balancing innovation with practicality, advocating for leveraging pre-built AI and ML models wherever possible to streamline integration.
3. Mitigate Risks of AI Hallucinations through Careful System Design: Acknowledging the risks posed by unreliable AI outputs, he stressed the importance of robust system design. Using LLexus, an AI-driven incident management system, as an example, Sharad highlighted techniques like iterative plan generation, validation rules, and human auditing as essential safeguards against AI errors.

The talk also delved into broader trends shaping the telecom landscape:

• Cloudification of Telecom Infrastructure: The shift from hardware-based to software-based network functions, underpinned by cloud-native principles, has revolutionised telco infrastructure. This transformation facilitates rapid upgrades, reduces costs, and introduces new opportunities for AI-driven analytics.
• Challenges in Performance and Reliability: Ensuring high throughput, low latency, and carrier-grade reliability in cloudified networks remains a significant hurdle. Innovations like PAINTER and LLexus demonstrate how AI and ML are being applied to optimise these aspects.
• Emerging Business Models and Private Deployments: The integration of new radio technologies and virtualised network functions is driving novel revenue streams, such as private 5G/6G networks for mission-critical applications like factory automation.

Finally, Sharad’s keynote underscored how AI, ML, and cloud computing are reshaping the telecom industry, particularly in the era of 5G and the forthcoming 6G. By leveraging the scale of cloud infrastructure, balancing algorithmic complexity, and designing systems with resilience against AI pitfalls, the industry is poised to meet its ambitious goals of high bandwidth, low latency, and unparalleled reliability.

The video of his talk is embedded below and the slides are available here:

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