Organizational Learning Strategies in Artificial Intelligence-Based Environments
Keywords:
Organizational learning, artificial intelligence, technological infrastructure, learning processes, innovation, digital leadershipAbstract
Objective: This study aimed to identify and elucidate organizational learning strategies in AI-based organizations, focusing on key infrastructures, processes, and outcomes.
Methods and Materials: A qualitative review was conducted based on the analysis of 12 peer-reviewed international articles. Data were collected exclusively through systematic literature review, and thematic analysis was performed using Nvivo 14. Theoretical saturation was employed to ensure validity, and main themes were extracted and categorized.
Findings: Results indicated that organizational learning in AI-based environments consists of three main dimensions: (1) technological, cultural, and managerial infrastructures; (2) learning processes including acquisition, sharing, storage, application, and feedback of knowledge; and (3) outcomes and development strategies encompassing data-driven decision-making, innovation, and ethical learning. Findings highlighted that effective human–machine interaction, organizational learning culture, and digital leadership are critical for enhancing learning and innovation.
Conclusion: The study demonstrates that organizational learning in the AI era extends beyond traditional processes to a dynamic, self-reinforcing, and data-driven ecosystem. Organizations that establish appropriate technological and cultural infrastructures and optimize human–machine interaction can achieve sustainable competitive advantage, continuous innovation, and precise decision-making. This research provides a conceptual framework for future studies and organizational policy-making in intelligent learning.
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