Transformative AI and the Evolution of Growth Models: Extending the Solow and Endogenous Growth Frameworks for the Age of Machine Intelligence

This paper extends classical and endogenous growth models to incorporate transformative artificial intelligence (TAI) — AI systems capable of driving structural economic change comparable to the industrial revolution. Building on Solow’s (1956) exogenous model and Romer’s (1990) endogenous innovation framework, we develop a dynamic model integrating AI as both a productivity amplifier and an autonomous driver of capital accumulation. We argue that TAI introduces recursive feedback loops between technology, knowledge, and output that redefine long-term growth trajectories and the equilibrium conditions of economies.