Agentic AI and autonomy: CSPs set out their strategies
What are the key opportunities for operators adopting agentic AI and how can they overcome the many challenges to deploying it at scale?
Mark Newman, TM ForumDownload Report
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Agentic AI and autonomy: CSPs set out their strategies
Agentic AI is now front and center of many operators' strategies and promises to be a key enabler to greater network autonomy. But what do communications service providers (CSPs) think of the new opportunities it presents and the extent to which it is changing their thinking about the impact of AI? Which use cases are they prioritizing and what are the challenges they need to address to deploy the technology at scale? Our new Benchmark report, Agentic AI and autonomy: CSPs set out their strategies, addresses these key questions and provides some guidance for operators facing some difficult decisions.
Read it to learn:
- How CSPs have very differing levels of ambition for AI transformation
- The different financial and operational metrics that CSPs are applying to the performance of their AI-centered initiatives
- How the most AI-mature CSPs are looking to add agentic AI to their predictive and AI programs
- Where CSPs see most potential for autonomous systems in their organizations
- Where CSPs are playing in the AI value chain
- The impact of standards such as Model Context Protocol (MCP) and Agent2Agent Protocol (A2A) on CSPs’ abilities to leverage agentic AI
- The new requirements that agentic AI is putting on CSP strategies for providing better access to high-quality data
- The challenges that CSPs will face as they consider how to deploy GenAI at scale
- How TM Forum is adopting agentic AI into its different programs and initiatives.
