A scoping review mapping the role of Husserlian phenomenology in artificial intelligence research

AI research increasingly attributes perception, understanding, agency, and consciousness to artificial systems. Husserlian phenomenology offers distinctions through which to examine these claims. This scoping review maps explicit Husserlian uptake in AI and robotics and asks how conceptual engagement relates to methodological and design contributions. Eight primary queries and one overlapping name-variant query were executed through the Semantic Scholar Academic Graph API on 5 December 2025. English-language publications within a 1989–2026 search window were screened for substantive AI or robotics relevance and an explicit Husserlian anchor. Of 5,594 retrieved records, 32 publications from 1990 to 2025 were included. Nine publications recovered by a post hoc PhilPapers check were charted separately using the existing codebook; they were not added to the formal corpus. The corpus clusters around embodied AI, AI epistemology, cognitive architectures, and machine consciousness, with a newer generative-AI cluster. Constitution, intentionality, horizonality, and the lifeworld recur prominently. Conceptual translation, critique, and agenda setting predominate within this sample. Methodological import or design guidance occurs in seven of the 32 publications and three of the nine external publications. That difference qualifies generalization of the quantitative balance. Across both sets, Husserlian uptake spans conceptual interpretation, methodological transfer, and architectural proposals. The synthesis shows how distinctions concerning temporality, embodiment, and evidence can structure design and evaluation questions, while separating the authors’ research proposals from the mapped findings.