The Slow and Fast Tracks of AI Adoption in Organizations

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AI adoption in organizations varies significantly across sectors, with faster integration in tech sectors like code generation and operational efficiencies, while industries such as legal lag behind. The potential for AI to transform productivity in labor-intensive fields like law is hindered by traditional billing models that prioritize billable hours, making it challenging to implement labor-saving technologies. Conversely, litigation-focused law firms, which utilize outcome-based billing, may be more inclined to adopt AI solutions due to their incentive structures. Historical shifts in pricing models in various industries illustrate that while organizations can adapt to new pricing strategies, these changes can also inhibit the adoption of efficiencies unless aligned with economic incentives. The broader implication suggests that various sectors may experience drastically different timelines for meaningful AI integration, influenced by existing practices and economic models that currently dictate how services are priced and valued.

This week, Byrne Hobart and Erik Torenberg are joined by Omar Shams, the founder of Mutable AI, for a deep dive into Omar’s great piece, The AI Organization. In this conversation, they explore the potential of AI to transform organizational productivity, the limitations of financial metrics in GDP, and AI's role in political processes and societal structures.

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LINKS:

Byrne’s writing: https://thediff.co

The AI Organization, part I: https://blog.mutable.ai/p/the-ai-organization-part-i

The First Org Chart Ever Made Is a Masterpiece of Data Design: https://www.wired.com/2014/03/stunningly-complex-organization-chart-19th-century/

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X / TWITTER:

https://x.com/smahsramo (Omar)

https://twitter.com/ByrneHobart (Byrne)

https://twitter.com/TurpentineMedia (Turpentine)

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