Artificial Intelligence in Telecommunications 2025

1 Intra-industry partnerships CSPs face the challenge of finding the delicate balance between overinvesting in AI opportunities before use cases mature and under-investing and risking competitive disadvantage. While collaboration between CSPs requires clear scoping and guardrails to maintain competitive positioning, intra-industry partnerships can help reduce investment overheads and strengthen their negotiating power in ecosystem collaborations. For example, the Global Telco Alliance, a partnership of five global CSPs, aims to accelerate the AI transformation in existing businesses and create new AI-driven business opportunities. It will co-develop a new “telco AI platform”, which will serve as the foundation for new AI services48 and launch a joint venture to create a multilingual LLM tailored to industry needs.49 Collaboration with global industry groups like GSMA and TM Forum enables CSPs to help define responsible AI boundaries, share best practices and align on strategies to educate customers about new AI capabilities. 2 New telecommunications infrastructure partners To support their transformation and capitalize on AI-enabled opportunities to offer infrastructure, AIaaS SMB products and industry solutions, CSPs are developing their tech architecture to include the cloud, edge compute and connectivity. Infrastructure collaborations can accelerate this evolution and enable tailored implementations in each layer. For connectivity, traditional vendors are helping CSPs develop automated network solutions through “off-the-shelf” solutions and offering access to innovation labs. At the edge, partnerships with GPU providers enhance compute capabilities, enabling CSPs to offer “infrastructure as a service” and securely store and process sovereign data. Cloud providers can support sovereign cloud implementations by deploying within data centres. This facilitates data modernization and inferencing capabilities such as ML frameworks, natural language processing and predictive analytics, enabling scalable and tailored AI models while minimizing infrastructure investments for CSPs transformation and AIaaS offerings. Given the complexity of a multimodal, multi- application ecosystem, CSPs require a vendor- neutral cybersecurity layer, which can be developed in collaboration with infrastructure and application partners. 3 Application partners To capitalize on enabling infrastructure, CSPs require data models, algorithms and integration with transactional components to embed modernization and AI implementation into their operational processes. Application partners can accelerate value realization by providing end-to-end solutions within specific domains. However, this approach risks creating isolated AI systems, which can be mitigated by building centralized capabilities. 4 Transformation partners Enterprise reinvention requires a clear value realization strategy, effective ways of working (operating models, processes and skill sets), robust data foundations and technology architecture, responsible AI and new processes and systems for continuous monitoring and adjustment. Transformation partners act as orchestrators, aligning these components into a cohesive “to-be” blueprint and phased implementation roadmap. Their expertise also enables CSPs with end-to-end implementation, while managing complexities and nuance at every stage. Ideal partners bring experience in enterprise-wide AI implementation and competencies across all transformation components. 5 Private/public/academia Partnerships with governments and regulatory bodies can help CSPs play a role in regulation and policy development, support public infrastructure projects and access or influence public development funds. Collaboration with academic institutions promotes innovation, provides resources for upskilling and develops future talent. CSPs can also shape academic pathways with tailored learning materials to meet industry-specific needs. Climate & Natural Disasters Platform BOX 10 The Climate & Natural Disasters Platform (CNDP), developed by e& in partnership with the United Nations Development Programme (UNDP), uses AI to respond to climate change and natural disasters. It processes live and historical public data from over 85 languages, including social media, UNDP data and media outlets, to generate actionable insights. By enhancing situational awareness and supporting timely interventions, the platform empowers authorities to respond rapidly to crises, address infrastructure issues and improve disaster relief efforts. CNDP ensures comprehensive monitoring, proactive insights, and coordination to save lives and drive sustainable development. Artificial Intelligence in Telecommunications 23