Top AI Analyst Unpacks Today's AI Hype Cycle

AI's current trajectory mirrors past platform shifts like mobile and the internet, yet its ultimate impact remains difficult to quantify due to the lack of clear physical limits and the "jagged" nature of model capabilities. While foundation models currently excel in software development, their broader enterprise adoption faces significant hurdles, including the difficulty of isolating repetitive tasks and the necessity for deep domain expertise. Value accrual in the AI stack likely will not mirror the monolithic dominance of past platforms, as competitive dynamics shift across layers. Rather than predicting job displacement through simplistic exposure charts, focus should shift toward how AI functions as an enabling technology that automates complex back-office processes and creates new demand. Ultimately, the most transformative AI applications will emerge from specific, invented use cases rather than generic, grassroots consumer behavior.