AI Briefing
KO

Aatish Nayak Outlines Strategy for the Spread of AI 'Intelligence Utility' and Presents a 7-Point Roadmap

·2026.08.26 09:00

Key point

AI intelligence is like a hydroelectric power plant rather than a flood, and the infrastructure that converts it into real-world outcomes is the core value.

Details

The Nature of AI Intelligence and Its Economic Implications

As AI labs break sales records and expand feature absorption, concerns are growing that a flood of intelligence will erode the economy. However, intelligence is a utility with infinite demand, and the core lies in systems that spread it across civilization and convert it into actual problem-solving and outcomes, rather than the raw models themselves. A premium will form for companies building this intelligence diffusion infrastructure.

Inertia of Reality and Time Lag

Even if one had seen GPT 5.5+ or Opus 4.5+ in 2019, one would have expected the economy to be completely transformed. But reality is complex, and a lack of intelligence is rarely the bottleneck in human-level work. Actual work involves context, exceptions, and historical data that are difficult to capture in prompts, and human factors such as incentives, approvals, and accountability are intricately intertwined. As with the examples of electricity and the internet, there is always a time lag between technology adoption and actual economic change. This gap is currently the largest arbitrage opportunity, but the window is short.

7-Point Roadmap for Intelligence Diffusion

To leverage this gap, products, services, and narratives must be transformed in an integrated manner. Both AI-native startups and existing companies must execute the following strategies.

  • Multiplayer Network Orchestration: Build collaborative workflows between humans and agents rather than maximizing individual productivity. Accumulate coordination graphs to secure an irreplaceable position.
  • Workflow Gravity Accumulation: Accumulate unique data not present in pre-training, such as internal documents, decision-making data, and exception handling records from customer companies, as trusted sources.
  • Customer-Led Transformation: Enable customers to own their own transformation.
  • Presenting a Future Narrative: Communicate your own vision of the future.
  • Raising the Level of Abstraction: Hide technical complexity and reveal value.
  • Selling the Impossible: Productize outcomes that were previously impossible.
  • Structural Essentialization: Become an indispensable presence for the business.

One of these strategies alone is not enough in a highly competitive market, and most must be executed over time.

This summary was generated automatically by AI. Check the original for the author's claims and context. Copyright belongs to the original author.

Our guide explains how the AI works. Report summary errors, attribution issues, or removal requests via Contact.