Скачать или смотреть The AI Scaling Trap: Why 92% of AI Startups Fail (And How to Avoid It)

92% of AI startups fail within three years, even after finding product-market fit. Why? In this video, we break down the "AI Scaling Trap"—the self-reinforcing failure loops that doom even the most promising AI ventures.

Based on a detailed industry analysis, we'll explore the real reasons behind the collapse, which go far beyond just technical problems. We'll cover:

🔴 The 3 Structural Patterns of Failure: The Commodity Trap, The Low Barrier to Entry Paradox, and The Founder Skill Gap.
🔴 The Failure Timeline: Navigating the "Valley of Death" from MVP to Series B.
🔴 The Core Conflict: Why the traditional Venture Capital model is fundamentally mismatched with AI economics.
🔴 A Diagnostic Framework: See where different AI startups (AI-as-a-feature vs. AI-native) face the biggest risks.
🔴 Survival Strategies: The essential mindset shift from "Technical Optimism" to "Business Realism" and how to build a defensible moat.

Perfect for students in: Computer Science, Data Science, MBA programs, Entrepreneurship, and anyone interested in the business side of technology and AI.

Timestamps:
0:00 The Shocking 92% Failure Rate
1:30 The Common Diagnosis (What People Think Fails)
2:45 The Real Cause: Self-Reinforcing Failure Loops
4:20 The 3 Structural Patterns of Failure
6:10 The AI vs. VC Mismatch
7:45 The Diagnostic Framework Map
9:00 How to Survive and Scale
10:30 The Necessary Mindset Shift

Keywords: AI Startup Failure, Scaling AI, Tech Startup Guide, Entrepreneurship for Students, AI Business Model, Unit Economics, Defensible Moat, Startup Pitch, VC Funding, Product Management, ML Ops, Data Strategy.

Join the Discussion:
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