Technology development based on strategic alliances in the automotive industry has emerged as a significant strategy in recent decades. This study is descriptive-analytical in terms of data collection method and follows an inductive-deductive approach in terms of research methodology. The qualitative phase involved interviews with 17 experts in the Iranian automotive industry and academic professionals specializing in technology within strategic management. Participants were selected purposefully. The initial interview questions were developed based on a review of books, articles, and related studies. The interviews continued until theoretical saturation was achieved, which occurred at the 15th participant. After transcribing the participants’ responses, an analysis of the explicit and implicit content of the collected information began. The goal of this process was to extract the components required to propose a technology development model based on strategic alliances in the Iranian automotive industry using a grounded theory approach. For analyzing the text of the semi-structured interviews, Strauss and Corbin's (1998) method was employed using MAXQDA software. The findings revealed a total of 203 initial open codes. After removing duplicate codes and merging similar ones, 78 final open codes were identified. Following the analysis of the interview texts, 14 axial codes within six selective codes were extracted. The results indicate that identifying customer needs through data analysis and surveys leads to the design of products aligned with their preferences. Modern technologies such as artificial intelligence and data mining serve as powerful tools for identifying customer behavioral patterns. Aligning product design with customers' cultural and economic needs enhances their loyalty. The experience of successful global companies demonstrates that this approach contributes to increasing market share.