Convergence architecture: Serverless computing and AI integration in modern enterprise workflows

The convergence of serverless computing and artificial intelligence represents a transformative paradigm in enterprise modernization, addressing critical challenges in traditional IT infrastructure. This article analysis explores how the integration of serverless architectures with AI capabilities creates synergistic value across organizations. The article establishes a theoretical framework for cloud-native intelligence architectures, detailing implementation patterns including event-triggered intelligence models, microservice orchestration with embedded intelligence, serverless ETL pipelines, and infrastructure-as-code approaches. Through case analyses of real-time fraud detection, customer interaction transformation, and process automation, the research demonstrates substantial improvements in operational efficiency, cost reduction, and innovation velocity. A structured adoption framework outlines organizational readiness assessment methodologies, technical capability maturity models, governance considerations, and phased implementation roadmaps. The article concludes by examining emerging trends in serverless AI integration, identifying research gaps, and discussing the long-term strategic implications for enterprise competitiveness in rapidly evolving digital markets.