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arXiv · 2504.04334

Artificial Intelligence for Software Architecture: Literature Review and the Road Ahead

Alessio Bucaioni·Martin Weyssow·Junda He·Yunbo Lyu·David Lo
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Abstract

Artificial intelligence is increasingly applied across software engineering, yet its explicit role in software architecture remains insufficiently understood. Architectural practices rely on complex trade-offs, documentation, and long-term evolution, all of which are traditionally manual, error-prone, and difficult to sustain. To clarify how artificial intelligence can address these challenges, we conducted a systematic literature review of 51 peer-reviewed primary studies and systematically mapped their contributions onto 17 practitioner-reported software architecture challenges derived from empirical interviews. This analysis identifies 14 topical areas where artificial intelligence has been applied to architectural tasks and identifies six artificial intelligence-specific challenges that expose fundamental gaps between current capabilities and practitioner needs. Building on these findings, we chart a research agenda for artificial intelligence-driven software architecture organized around five strategic pillars. By grounding the roadmap in both systematic evidence and practitioner insights, this work provides the first peer-reviewed comprehensive synthesis of artificial intelligence contributions to software architecture, establishes a foundation for future research, and outlines the conditions under which artificial intelligence can become a trustworthy partner in architectural design, evaluation, and evolution.

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Alessio Bucaioni, Martin Weyssow, Junda He, Yunbo Lyu, David Lo. 2026-06-30. Artificial Intelligence for Software Architecture: Literature Review and the Road Ahead. https://arxiv.org/abs/2504.04334

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