Don't Worry About the Vase Podcast Reports Of AI Not Progressing Or Offering Mundane Utility Are Often Greatly Exaggerated
Aug 26, 2025
This discussion tackles common myths about AI's progress, highlighting the gap between experimental technology and real-world applications. It delves into the high failure rates of AI in enterprises, emphasizing the need for adaptable systems. The chat addresses job displacement fears, challenging perceptions of AI's impact on employment. Limitations in current AI capabilities are scrutinized, alongside societal expectations and the potential of Artificial General Intelligence on the economy. Overall, it's a thought-provoking take on AI's evolving role in business.
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Chatbots And Coding Agents Deliver Real Productivity
- Chatbots and coding agents are widely adopted and deliver clear productivity wins today.
- These tools enhance individual work even if they don't immediately show up as P&L line items.
Most Enterprise AI Fails From Skill And Integration Gaps
- Enterprise pilots often fail because firms treat AI as static tools rather than learning systems.
- External vendor solutions succeed more often than custom internal builds, suggesting skill and integration gaps.
Prioritize Learning Systems And External Partners
- Do prioritize learning-capable systems that integrate with workflows instead of one-off static pilots.
- Test external solutions before building internally to reduce failure risk and accelerate value capture.