Bim and AI Adoption in Construction Project Planning: Evaluation, Challenges, and Strategic Recommendations for Design Consultants - Ida Bagus Ari Suya Jnana; I Gusti Agung Adnyana Putera; A.A. Gde Agung Yana (Enrichment: Journal of Multidisciplinary Research and Development, 2026)
BIM and AI are becoming increasingly important in construction planning, although their adoption among design consultants remains uneven, particularly in developing construction markets. This research examines BIM-AI adoption through a combined assessment of BIM-AI maturity, technology acceptance, organizational and environmental readiness, and importance-performance priorities. The research was carried out in three design-consultant organizations in Bali, Indonesia: PT MBJ, Formata.id, and PT KASS. Data were obtained from 30 respondents through a Likert-scale questionnaire. The instrument was supported by content validation, pilot testing, and qualitative clarification. The results indicate that the three organizations had a high level of BIM-AI maturity, with a score of 3.97 out of 5.00. The overall TAM score reached 4.16, while adoption readiness scored 4.11, both of which were also in the high category. Respondents gave positive ratings to the TOE/implementation factors. The performance score was slightly higher than the importance score, 4.20 compared with 4.10, which indicates that the current implementation is already performing slightly above what respondents considered important. The reliability results also support the consistency of the instrument, with Cronbach's alpha values between 0.905 and 0.975. IPA identified five indicators in the Concentrate Here quadrant, mainly related to management support, workflow compatibility, system integration, human resource competence, and regulatory support. The study provides a practical basis for design consultants to strengthen their BIM-AI adoption. Rather than treating digital tools as separate or partial applications, the proposed structure helps organizations move toward more integrated, data-driven, and organization-wide use in construction planning.