AI to Follow Traditional Tech Adoption Cycles, Says Analysis

In a new framework, researchers challenge the view that AI is unprecedented, arguing it will follow standard technology adoption stages akin to electrification and the internet. They outline four phases of AI adoption: invention, product development, diffusion, and adaptation, highlighting that human behavior, business model innovation, infrastructure, and regulation—rather than rapid algorithmic improvements—dictate the tempo of AI adoption. Princeton’s Arvind Narayanan emphasizes that most organizations deploying AI, not just AI vendors, will navigate these stages, requiring new abstractions and workflows to integrate AI into deterministic software environments. Behavioral barriers, such as user resistance to AI personality changes, and physical constraints like GPU availability and power infrastructure, further slow diffusion. Viewing AI as a normal technology suggests that fears of an AI singularity are overstated; market and regulatory measures can manage AI safety. Crypto traders can apply this realistic adoption timeline to gauge demand for infrastructure tokens and to assess investment opportunities in companies building scalable AI-driven platforms.