There are too many pitfalls in enterprise intelligence deployment! Amazon Cloud Technology releases a “Pitfall Prevention Guide”

Zhidongxi Author | ZeR0 Editor | Mo Ying Zhidongxi reported on July 14 that at the recently held Amazon Cloud Technology 2026 China Summit, Chu Ruisong, Amazon Global Vice President and Co-President of Amazon Cloud Technology Asia Pacific, said that Agentic AI has reached an explosive turning point, and AI is transforming from an auxiliary tool to a productivity that directly delivers measurable business results. In order to help enterprises promote agents from prototypes to actual production, Amazon Cloud Technology released the "Enterprise Production-Level Agent Development and Deployment Guide" at the summit, providing enterprises with system engineering guidance from theory to practice. According to predictions by industry research institutions, more than 40% of Agentic AI projects will be at risk of being canceled by the end of 2027; MIT research shows that only about 5% of organizations report that generative AI projects have achieved high returns. These data all point to the difficulty of implementing Agent. Challenges such as rising costs, unclear business value, and insufficient risk management and control have resulted in a large number of projects failing to move into the actual production stage. Enterprise-level Agent development and deployment requires new evaluation and testing methods. In his speech at the summit, Chu Ruisong mentioned that when companies build AI Agents, the underlying technology platform can be obtained through procurement, but the evaluation criteria must be independently controlled by the company. A company's core competitive barrier lies in its own golden data sets and scoring standards. Only by mastering evaluation can we truly grasp the core of the Agent life cycle. In the view of the Amazon Cloud Technology Team, only by establishing assessment as the starting point for all engineering practices can we provide key support for the implementation and large-scale deployment of Agents, and ensure that Agents can safely, stably, and reliably deliver measurable business value in complex and ever-changing business scenarios. To this end, Amazon Cloud Technology's "Enterprise Production-Level Agent Development and Deployment Guide" systematically provides enterprises with implementable engineering paths through four core sections to help enterprises accelerate the transformation of Agentic business. 1. Why are traditional software evaluation methods ineffective for Agents? Agent systems in real business environments are full of uncertainties. User intentions may be vague, tool calls may fail, and business rules may not be consistent with each other.