RESEARCH ARCHIVE

Executive Research & Post-Mortems

Deep technical investigations bridging academic theoretical rigor with frontline engineering realities.

All Insights (3) Papers & Reports (1) Tech & MLOps (1) Strategy & Leadership (1) Case Post-mortems (0) Opinions & Columns (0)

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80%+ Enterprise AI projects discontinued prior to or immediately following production serving

Papers & Reports • Sep 8, 2026

[Executive Brief] RAND Corporation Analysis: Why Over 80% of Enterprise AI Initiatives Fail to Reach Production

A deep technical dissection of the landmark 2024 RAND Corporation research report. Unpacking the 5 structural failure modes and the fundamental communication gap between engineering and the C-suite.

정현 (Jeonghyun)

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95% vs 5% Ratio of infrastructure and pipeline code versus actual ML algorithmic code in enterprise systems

Tech & MLOps • Sep 7, 2026

[MLOps Architecture] Why 99% Benchmark Models Collapse in Production: Data Drift & Serving Skew

Dissecting the exact technical mechanisms behind silent model failure in high-throughput enterprise serving, and architecting resilient real-time drift mitigation pipelines.

Research Fellow: MLOps Lab

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13 Months Average time an enterprise AI pilot languishes in PoC phase before cancellation

Strategy & Leadership • Sep 6, 2026

[Product Leadership] The 4 Fatal Pitfalls of Enterprise AI Product Managers

Why traditional deterministic Agile roadmaps fail when applied to probabilistic machine learning systems, and how AI Product Leaders navigate PoC purgatory.

AI Product Strategy Practice

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