Survey for Landing Generative AI in Social and E-commerce Recsys -- the Industry Perspectives

TL;DR

This survey reviews the integration of generative AI into industrial social and e-commerce recommender systems, highlighting practical insights, challenges, and future research directions based on industry experiences.

Contribution

It provides a comprehensive overview of how GAI is being integrated into industrial Recsys, including system foundations, solution frameworks, and real-world challenges.

Findings

GAI integration is still in early stages in industry.

Practical challenges include system complexity and operational constraints.

Successful case studies demonstrate potential benefits.

Abstract

Recently, generative AI (GAI), with their emerging capabilities, have presented unique opportunities for augmenting and revolutionizing industrial recommender systems (Recsys). Despite growing research efforts at the intersection of these fields, the integration of GAI into industrial Recsys remains in its infancy, largely due to the intricate nature of modern industrial Recsys infrastructure, operations, and product sophistication. Drawing upon our experiences in successfully integrating GAI into several major social and e-commerce platforms, this survey aims to comprehensively examine the underlying system and AI foundations, solution frameworks, connections to key research advancements, as well as summarize the practical insights and challenges encountered in the endeavor to integrate GAI into industrial Recsys. As pioneering work in this domain, we hope outline the representative developments of relevant fields, shed lights on practical GAI adoptions in the industry, and motivate future research.