Unverified60% confidenceFactExact time
According to Gartner statistics, more than 85% of ML projects fail to transition from the experimental stage to production, with the main bottleneck being a lack of engineering capabilities.
2
Sources
60%
Confidence
Medium-term (~90 days)
Relevance
8/7/2026
First Seen
Valid until: 11/5/2026
Sources
Related Claims
UnverifiedEnvironment inconsistency, lack of version management, and absence of monitoring are common engineering gaps when ML models go from experimentation to production launch.77% similarUnverifiedML系统的调试和优化需要从数学层追溯到工程层，这种跨层依赖性在传统软件开发中极为罕见66% similarUnverified一项技术的演示效果与规模化落地之间往往隔着难以逾越的工程鸿沟，被称为从实验室到生产环境的最后一英里问题64% similar
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