AI for Productivity in the Age of Agentic AI

Throughout history, transformative technologies have repeatedly reshaped production systems and economic activity. In the current wave of AI development, Agentic AI systems are emerging as a new class of productive instruments capable of goal perception, multi-step planning, environmental interaction, and autonomous workflow coordination. Beyond automating routine tasks, these systems have the potential to augment knowledge work, reorganize decision-making, and reshape the relationship between human labor, organizational routines, and machine intelligence. This development gives rise to the emerging research direction of AI for Productivity (AI4Productivity), which examines how advanced AI systems affect productivity across economic and social contexts. In this paper, we conducts an in-depth investigation for explaining how Agentic AI creates productivity. We define AI4Productivity as the use of Agentic AI in real-world workflows to deliver economically valuable work with less human effort, and identify two core mechanisms of productivity gains: Efficiency, which reduces the time and labor required for existing tasks, and Expansion, which makes previously infeasible work economically viable. We further characterize the evolution of AI systems through four stages: conversational assistant, reactive operator, adaptive coordinator, and self-governing production system. Building on this framework, we review representative AI productivity tools and examine the sectoral diffusion of Agentic AI across three levels of adoption: early-stage exploration in manufacturing, agriculture, real estate, and government services; broader integration in trade, media, education, and legal services; deeper workflow orchestration in information technology, finance, and healthcare. Finally, we discuss key challenges including safety, long-horizon reliability, academia-industry gaps, adoption barriers, governance, and labor-market uncertainty. This paper provides a structured account of how Agentic AI is reshaping productivity and outlines future directions for reliable and socially beneficial AI-driven production systems. We hope this paper will serve as a foundation for advancing AI4Productivity research and guiding the design of AI systems that deliver reliable, scalable, and broadly beneficial productivity gains.