Jio Platforms has announced an AI telecom network alliance with AMD, Cisco, and Nokia, unveiled at Mobile World Congress. The partnership aims to build an Open Telecom AI Platform that embeds artificial intelligence across network operations to help telecommunications providers manage increasingly complex infrastructure, security concerns, and cost pressures.
The initiative is presented as a solutions-oriented, multi-domain intelligence framework that combines automation, analytics, and adaptive intelligence to improve network performance and security while opening new service and revenue opportunities. Mathew Oommen, Group CEO of Reliance Jio, described the effort as extending beyond automation toward AI-driven, autonomous networks that adapt in real time to improve user experience and enable fresh commercial models.
The platform will be LLM-agnostic and built on open APIs to ensure flexibility and extensibility. It plans to incorporate a range of AI approaches, including agentic AI, large language models, domain-specific small language models, and established machine learning techniques, so operators can deploy the most appropriate models for each domain and workload.
Each partner brings defined capabilities to the collaboration. AMD contributes compute and accelerator architecture—its high-performance CPUs, GPUs, and adaptive computing solutions will support the platform’s demanding workloads and help deliver secure, efficient, and scalable processing for AI-enabled network functions, according to AMD leadership.
Cisco will provide integrated stack elements spanning networking, compute, AI defense, and analytics to connect the platform to operational workflows and security controls. Cisco’s contribution focuses on embedding telemetry, policy, and threat protection into AI-driven network management so operators can realize faster detection and coordinated response across domains.
Nokia will supply radio access network (RAN), core network, fixed broadband, and IP and optical transport capabilities to ensure the platform integrates with existing carrier-grade infrastructure. Nokia emphasizes that the collaboration aims to enhance performance, security, automation, and operational efficiency, helping service providers optimise and monetise network investments while improving customer experience.
Initially, the platform will be implemented with Jio’s networks in India, with plans to refine a replicable reference architecture and a deployable solution that can be offered to the global service provider market. This phased approach allows practical validation at scale before broader rollouts.
Industry analysts note several potential benefits from applying AI across telecom networks:
- Enhanced threat detection and automated security responses, reducing dwell time for attacks and improving incident response consistency.
- Predictive maintenance and anomaly detection to reduce unplanned outages and lower mean time to repair.
- More efficient resource allocation and energy management, enabling dynamic radio and transport optimization that cuts operational costs.
- Improved customer experience through anticipatory service adjustments, personalized policies, and faster issue resolution.
Despite the potential upsides, the project faces notable challenges. Standardisation and interoperability with legacy systems will be essential to avoid vendor lock-in and to enable multi-vendor deployments across diverse operator environments. Data governance, privacy, and the secure handling of telemetry and customer information remain critical concerns that operators and vendors must address. The partners have not provided a specific timetable for when the platform will be fully operational; implementation complexity and regulatory considerations will influence rollout schedules.
The alliance reflects a broader industry shift toward treating AI as a foundational component of future telecommunications networks rather than an optional enhancement. As work on 6G and beyond progresses, AI-native network capabilities—such as continuous optimization, autonomous fault recovery, and intelligent service orchestration—are likely to be central to supporting highly demanding, data-intensive applications.
For service providers worldwide, the Open Telecom AI Platform could serve as a blueprint for tackling common operational challenges and accelerating the path to automated, secure, and efficient networks. Ultimately, its value will depend on successful integration, measurable improvements in network performance and cost structure, and clear business outcomes that justify investment across multiple operator environments.
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