The AI Great Leap Forward
Summary
The article warns that many organizations are rushing AI adoption with top-down mandates and little emphasis on data infrastructure, evaluation, or governance. It argues that no-code and drag-and-drop AI tools often produce impressive demos but unreliable results, creating technical debt and lost institutional knowledge. Through historical parallels, it cautions against misaligned incentives and superficial metrics, urging robust measurement pipelines and sustainable AI deployment.