AI integration in business excellence award assessment: assessors’ perspective

Counts differ because each database indexes a different set of publications. We treat OpenAlex as the canonical count; Google Scholar is not shown (no API, and crawling it violates its ToS).

Purpose This study explores assessors’ and jury members’ perceptions of integrating artificial intelligence (AI) in Business Excellence (BE) award assessments. While AI can enhance efficiency, consistency and the quality of feedback, stakeholder acceptance remains underexplored. Understanding these perceptions is crucial, as trust is essential for effective AI implementation. Design/methodology/approach A sequential mixed-methods design was employed. First, survey data were collected from 248 assessors across different BE contexts to identify patterns of AI acceptance and use. This quantitative phase was followed by in-depth interviews with 24 assessors and jury members. The interview data were analyzed using thematic coding to explore participants’ concerns, expectations and preferences regarding the integration of AI into BE assessment processes. Findings Results show cautious optimism toward AI adoption. Participants recognized its potential to automate tasks and support decisions but expressed concerns about transparency, fairness and overreliance. Maintaining human oversight was viewed as critical to preserving the credibility of the assessment. Practical implications The study highlights key enablers and barriers to AI adoption and recommends hybrid models combining AI with human expertise. Findings support policymakers and practitioners in implementing AI responsibly within excellence frameworks. Originality/value This study contributes to AI and quality management literature by focusing on stakeholder perceptions rather than technical aspects, offering empirical insights into human acceptance in BE award evaluations.