arXiv:2611.14154v1 Announce Type: new Abstract: This paper presents a descriptive, embedded single-case study examining self-reported AI use within a software organization. The study draws on 98 structured interview records collected across 11 teams, using ten standardized team-level instruments (n = 65) and one instrument with distinct response anchors (n = 33). Among respondents assessed using standardized instruments, 36 of 65 (55.4%) reported AI-use frequency scores of 4 or 5 on a five-point scale. Team-level proportions varied from 20.0% (1/5) to 71.4% (5/7). A record-level cross-tabulation revealed limited awareness or understanding of organizational AI policies across both frequency groups: 86.1% (31/36) of respondents scoring 4-5 and 96.6% (28/29) of those scoring 0-3 reported either no policy awareness or uncertainty about policy details. In the group assessed using the distinct instrument, 31 of 33 respondents (93.9%) scored 4 or 5. Although the pooled proportion reached 68.4% (67/98), differences in response anchors limit direct comparability, making the standardized-instrument results the primary analytical reference. Interviewer-recorded observations provide qualitative context on reported practices and constraints but do not support estimates of their prevalence or causal explanations for differences in AI-use frequency. The findings characterize AI-use patterns and policy awareness within the interviewed sample, without supporting inferences about organization-wide adoption, policy compliance, or the effectiveness of AI use. The study contributes an empirically grounded organizational case and an explicit account of the methodological boundaries of cross-team comparisons using heterogeneous interview instruments.