A General Theory of Growth, Employment, and Technological Change: Experiential Matrix Theory and the Transition from GDP to Humanist Experiential Growth in the Age of Artificial Intelligence

This paper introduces Experiential Matrix Theory (EMT), a general theory of growth, employment, and technological change for the age of artificial intelligence (AI). EMT redefines utility as the alignment between production and an evolving, infinite-dimensional matrix of human experiential needs, thereby extending classical utility frameworks and integrating ideas from the capabilities approach of Sen and Nussbaum into formal economic optimisation modelling. We model the economy as a dynamic control system in which AI collapses ideation and coordination costs, transforming production into a real-time vector of experience-aligned outputs. Under this structure, the production function becomes a continuously learning map from goods to experiential utility, and economic success is redefined as convergence toward an asymptotic utility frontier. Using Pontryagin's Maximum Principle in an infinite-dimensional setting, we derive conditions under which AI-aligned output paths are asymptotically optimal, and prove that unemployment is Pareto-inefficient wherever unmet needs and idle human capacities persist. On this foundation, we establish Alignment Economics as a new research field dedicated to understanding and designing economic systems in which technological, institutional, and ethical architectures co-evolve. EMT thereby reframes policy, welfare, and coordination as problems of dynamic alignment, not static allocation, and provides a mathematically defensible framework for realigning economic production with human flourishing. As ideation costs collapse and new experiential needs become addressable, EMT shows that economic growth can evolve into an inclusive, meaning-centred process -- formally grounded, ethically structured, and AI-enabled.