Скачать или смотреть The Real Reason 95% of AI Projects FAIL

MIT recently found that 95% of AI projects are failing but not for the reasons you might think. The usual explanations like model quality and change management only scratch the surface. The real issue is much deeper: employees aren’t rejecting AI itself… they’re rejecting enterprise AI tools that don’t learn, adapt, or improve over time.

In this video, I break down:
• Why employees are using Shadow AI (personal ChatGPT accounts) instead of company tools
• The feedback gap that makes enterprise AI adoption collapse
• Key findings from MIT on where AI succeeds vs. fails in the workplace
• The product design gap every enterprise AI leader needs to address

If we want enterprise AI adoption to rise, it’s building systems that:
1. Remember user preferences and corrections
2. Learn and adapt over time
3. Handle complex workflows with autonomy

This is where the future of enterprise AI is heading and why today’s failures point directly toward Agentic AI as the next frontier.

SOURCES:
https://www.artificialintelligence-ne...
https://www.bcg.com/press/26june2025-...
https://mlq.ai/media/quarterly_decks/...

Chapters:
0:00 End User Unwillingness to Adopt AI
0:30 Shadow AI Economy
1:33 Current AI Adoption Gap
2:23 AI Learning Gap
2:54 What can we do?