AI and Data Platforms

Overview

This programme analyses the AI and data platform vendor landscape and tracks changes in the emerging generative AI (GenAI) value chain that affect vendors’ competitive positioning. It also monitors operators’ progress towards adopting AI and data management technologies that support AI-enabled use cases. Our findings are based on extensive research, including interviews with product and professional services vendors and operators.

Themes

• Operator AI/GenAI deployment strategies for networks. Comparing operators’ RAN AI and AIOps implementation strategies.
• Telecoms vendors’ strategies for implementing GenAI. Analysing the level of maturity of telecoms vendors’ adoption of GenAI and understanding the implications of this for open and closed horizontal GenAI platform providers.
• Data architecture revolution. Establishing how data architectures will evolve to meet the requirements of GenAI.

Questions answered

• Operator AI/GenAI deployment strategies for networks. How do operators plan to implement AI technologies (GenAI and non GenAI) within their RAN environments and how do they plan to use AIOps to manage existing networks?
• Telecoms vendors’ strategies for implementing GenAI. How do telecoms application providers plan to adopt GenAI within their applications and how do they plan to engage with GenAI platform providers to fulfil operators’ core requirements for GenAI?
• Data architecture revolution. How will operators adapt their existing data strategies, architectures and practices to address the unique needs of GenAI technologies. How will these strategies scale to support future AI and data needs?
• Integrated data and AI platform strategies. What are the opportunities and challenges associated with using integrated data and AI platforms to drive AI-related developments?
• Forecasts. How will operators’ investments in the core segments evolve between 2024 and 2029?