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The architecture, engineering, and construction (AEC) industry accounts for approximately 39% of global CO₂ emissions and 40% of worldwide energy consumption, positioning it as a primary target for decarbonization. Artificial intelligence (AI) has emerged as a transformative enabler for net-zero construction strategies; however, no comprehensive bibliometric mapping of the intersection of AI, net-zero construction, and the full AEC industry has yet been published. This study addresses that gap through a bibliometric and science mapping analysis based on a systematic, transparent document identification and selection protocol inspired by PRISMA reporting principles. A corpus of 517 peer-reviewed articles and reviews was assembled from Scopus and Web of Science (2017–2026) following PRISMA guidelines, with data retrieved on 26 May 2026. Results reveal an annual growth rate of 54.45%, with 87.4% of all publications concentrated in 2023–2026, reflecting a research explosion driven primarily by the maturation of machine learning and deep learning applications for net-zero targets, within which the emergence of large language models (LLMs) and generative AI from 2023 onwards constitutes a fast-growing but still peripheral thread. China, the USA, and the UK lead scientific output. Two densely connected thematic clusters were identified — materials, optimisation, and carbon quantification; and AI, sustainability, and digital integration — alongside a long tail of peripheral, still-emerging themes and a clear three-phase paradigmatic evolution. The Thematic Map identifies generative AI and digital twins as high-priority emerging fronts. Building on prior reviews, this study presents a bibliometric review covering the entire AEC industry for net-zero construction using dual databases and proposes a research agenda for the field.