Generative AI and Firm Productivity: Field Experiments in Online Retail

2025-10-13

AI Summary

This study quantifies the impact of generative AI (GenAI) on total factor productivity (TFP) in online retail firms. To address the lack of causal evidence on GenAI’s real-world economic effects, we conducted a large-scale randomized field experiment across seven consumer-facing business processes on a cross-border e-commerce platform. Leveraging granular consumer behavior data and rigorous causal inference methods—while holding prices and inputs constant—we identify the primary mechanisms: reduced market frictions, improved conversion rates, and enhanced consumer experience. Results show that GenAI increases sales by 0–16.3% and generates approximately $5 in incremental value per consumer annually. Gains are disproportionately larger for small sellers and novice users. This work provides the first causal evidence of GenAI-driven productivity gains in live commercial settings, bridging a critical empirical gap. It offers actionable insights for platform governance design and informs policy on SME digital transformation.

Technology Category

• Natural Language Processing: Generation
• Machine Learning: Causal Learning
• Humans and AI: Learning Human Values and Preferences

Application Category

• Economics, Online Markets and Human Computation: Economic ramifications for generative AI infrastructure and applications
• Social Networks and Social Media: Generative AI / large language models and their impact on social systems
• Search and Retrieval-Augmented AI: Ad search and search for Web retail

Abstract

We quantify the impact of Generative Artificial Intelligence (GenAI) on firm productivity through a series of large-scale randomized field experiments involving millions of users and products at a leading cross-border online retail platform. Over six months in 2023-2024, GenAI-based enhancements were integrated into seven consumer-facing business workflows. We find that GenAI adoption significantly increases sales, with treatment effects ranging from 0% to 16.3%, depending on GenAI's marginal contribution relative to existing firm practices. Because inputs and prices were held constant across experimental arms, these gains map directly into total factor productivity improvements. Across the four GenAI applications with positive effects, the implied annual incremental value is approximately $5 per consumer-an economically meaningful impact given the retailer's scale and the early stage of GenAI adoption. The primary mechanism operates through higher conversion rates, consistent with GenAI reducing frictions in the marketplace and improving consumer experience. We also document substantial heterogeneity: smaller and newer sellers, as well as less experienced consumers, exhibit disproportionately larger gains. Our findings provide novel, large-scale causal evidence on the productivity effects of GenAI in online retail, highlighting both its immediate value and broader potential.

Problem

• Quantifying GenAI's impact on firm productivity
• Measuring sales increases through randomized field experiments
• Analyzing productivity gains across diverse seller and consumer segments

Innovation

• GenAI integrated into seven consumer workflows
• Higher conversion rates reduce marketplace frictions
• Substantial productivity gains for smaller sellers