This new report reveals how AI leaders are achieving superior business outcomes, including:

• • 81% reported better financial performance
  
• • 78% improved customer satisfaction
  
• • 76% boosted revenue gains
  
• • 73% increased market share growth  

Learn how to build a platform engineering strategy that supports GenAI workloads, scales LLMOps efficiently, and delivers low-latency performance at the edge.

Download the whitepaper to see how leading teams are:

• • Running multiple purpose-built LLMs across business units
  
• • Using edge infrastructure to serve inference closer to users
  
• • Simplifying model operations with automation and self-service tools
  
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Generative and agentic AI are spawning a new, edge-based infrastructure operating paradigm

• Over 80% of AI and IT professionals expect to grow their AI edge operations in the coming year
• The emergence of agentic AI multiplies the magnitude of the architectural and operational shift organizations are already making in pursuit of scaling inference at the edge

Serverless inference is the only path forward as AI innovation accelerates

• The demand for compute resources to support edge-based inference to execute transactions by the immense number of AI agents is increasing exponentially
• The vast majority of enterprises cannot afford the cost of procuring and maintaining the array of GPU and CPU resources needed to support GenAI and agentic AI at scale

Agentic AI will grow exponentially in the next few years, bringing major disruption – and opportunity

• While only 10% of organizations currently use AI agents, over 50% plan to adopt them in the next year; within 3 years, 82% of enterprises plan to have them incorporated (Source: Capgemini) 
• The number of AI agents will surpass the number of humans on Earth in the next 2-3 years (Source: Jeremiah Owang – Former Forrester analyst turned venture capitalist)