Corporate AI transformations in 2026 are being likened to China's Great Leap Forward due to top-down mandates lacking technical foundation.

The primary source details how employees without model training or evaluation experience are constructing LLM chains via n8n workflows and REST endpoints, producing outputs that satisfy internal dashboards but fail real-world tests; Klarna's 2024 announcement to replace Salesforce with internal AI-built solutions is cited directly (https://leehanchung.github.io/blogs/2026/04/05/the-ai-great-leap-forward/).

Klarna's February 2024 press release on AI automation and a 2025 Gartner report both document that 70-85% of enterprise AI projects stall at pilot stage due to absent data infrastructure, monitoring, and on-call protocols, patterns the blog connects to unmaintainable demoware that wins internal awards before collapsing (https://www.klarna.com/international/press/klarna-ai-to-replace-700-workers/).

Frank Dikötter's 2010 book Mao's Great Famine records how provincial grain-yield reports inflated by factors of five masked crop failure and caused famine; the blog maps this to current AI adoption metrics where pixel-perfect UIs and green checkmarks substitute for A/B-tested prompts or model-drift measurement (https://en.wikipedia.org/wiki/Great_Leap_Forward).