Imagine a network that can think, adapt, and heal itself — all without human intervention. Autonomous networks are the future of telecom: intelligent, self-managing, and capable of delivering seamless, reliable connectivity at scale. We seek AI-driven solutions enabling real-time adaptation, self-healing, intent-based orchestration, and edge intelligence to push network autonomy forward.

Key Questions

• How could autonomous systems detect, diagnose, and resolve network faults including hardware failures or degraded performance without human intervention?
• How would AI-driven networks auto-provision, scale, and adjust 5G slices based on real-time usage patterns and service demands?
• How might networks interpret high-level business or user intents and translate them into autonomous, adaptive network configurations without manual interventions?
• How might autonomous systems allocate spectrum, compute, and transport resources dynamically across multiple services or tenants?
• How could networks autonomously decide whether to process data at the edge or cloud depending on latency, load balancing, or privacy concerns?
• How can networks autonomously plan, test, and validate new infrastructure rollout with minimal human intervention?
• How can tool-augmented AI agents understand operator intent and enable closed-loop automation for optimal network configuration while ensuring policy and security?

Explore more key questions and further details!

Telecom networks are under pressure to handle ever-growing data traffic while reducing environmental impact. This focus area seeks AI-powered innovations that minimize energy use across the entire network lifecycle, from design to daily operations. The vision is “Zero Bit Zero Watt” — a network that consumes energy only when data is actively transmitted. We are interested in scalable, vendor-agnostic solutions that can optimize power dynamically, enable deep-sleep modes, or improve facility management without compromising performance. Submissions should clearly demonstrate measurable impact, practical integration, and alignment with international standards.

Key Questions

• How can AI reduce network power consumption at scale while maintaining quality of service?
• How could AI optimize real-time energy use, adapting dynamically to traffic loads?
• How might AI enable deep-sleep modes or near-zero idle power consumption?
• How could AI-driven predictive maintenance reduce energy waste and improve uptime?
• How might AI optimize data center and facility energy management?
• How can green coding or “green AI” approaches reduce the energy footprint of AI itself?
• How can solutions integrate seamlessly into existing networks across multiple vendors and countries?

Explore more key questions and further details!

Resilient supply chains are vital for the AI-Native Telco in a world of constant disruption from geopolitical, economic, or climate events. This focus area seeks AI-first solutions that increase transparency, provide early risk detection, and enable more adaptive responses across supplier networks. We are interested in innovations that uncover hidden risks, forecast disruptions, and propose alternative sourcing options while keeping costs under control. Strong approaches may also include predictive maintenance, refurbishment, or circular economy strategies that reduce dependencies and strengthen autonomy. Solutions should demonstrate scalability, sustainability, and practical integration into existing supply processes.

Key Questions

• How can AI increase transparency across supplier networks and uncover hidden risks?
• How might AI provide early warnings for risks caused by conflicts, volatility, or climate events?
• How could AI identify alternative sourcing options to secure critical components?
• How can AI improve forecasting and ordering to reduce disruptions and optimize costs?
• How might AI predict hardware failures and recommend spare parts strategies?
• How can AI support refurbishment, remanufacturing, and repair to strengthen autonomy?
• How could sustainable AI-driven approaches ensure resilience across the full supply lifecycle?

Explore more key questions and further details!

As we build the AI-Native Telco, cybersecurity must evolve to match new levels of complexity. We are looking for AI solutions that strengthen defenses across networks, systems, and AI applications themselves. From detecting zero-day exploits and insider threats to enabling self-healing environments, the focus is on making security more intelligent, adaptive, and proactive. Innovations may also include AI-driven advisory systems, deception technologies, or governance frameworks that protect both organizations and deployed AI. Solutions should demonstrate scalability, practicality, and the ability to secure the telecom ecosystem against today’s and tomorrow’s threats.

Key Questions

• How can AI detect zero-day vulnerabilities or insider threats before they cause damage?
• How might AI predict and prevent supply chain or device compromise attacks?
• How can adaptive AI-driven playbooks and self-healing systems transform incident response?
• How could AI-powered advisors or agents support CISOs and Security Operations Centers?
• How might generative honeypots or deception networks mislead and trap attackers?
• How can AI continuously assess security posture and detect shadow IT or unauthorized AI tools?
• How could synthetic data help train and test security systems against novel attacks?

Explore more key questions and further details!