In modern organizations, the integration of artificial intelligence is revolutionizing how knowledge is created, shared, and utilized, while also altering the dynamics of organizational learning, skill enhancement, and governance frameworks. Generative AI is pivotal in making explicit knowledge more accessible and in optimizing both automation and decision-making processes. Nevertheless, it introduces challenges, such as the risk of diminishing tacit knowledge and an increasing reliance on algorithm-driven insights. Thus, AI is gradually becoming both a technological foundation and an active player in organizational knowledge environments. The effectiveness of AI in enhancing knowledge creation and innovation, or conversely, in causing skill mismatches and deskilling, is largely influenced by organizational learning capabilities, culture, and governance mechanisms. Although there is increasing academic interest, there remains a lack of empirical evidence on the influence of AI on organizational knowledge ecosystems beyond individual companies. This study addresses this gap by examining how various AI adoption configurations affect organizational knowledge ecosystems and learning dynamics at the sectoral level. The research employs secondary data from the 2025 Survey on Information and Communication Technologies in Enterprises by ISTAT, concentrating on Italian companies with at least 10 employees. Data at the firm level is aggregated by economic sector, allowing for a meso-level analysis of AI adoption patterns. From a capability-based viewpoint, the study distinguishes between AI technologies that are cognitively oriented, aiding in knowledge creation, and those that are automation-oriented, primarily focused on task substitution. A sector-level cluster analysis is conducted to pinpoint distinct AI adoption patterns and their integration within organizations. This research aims to reveal various organizational knowledge ecosystems, each defined by a unique balance between AI applications focused on learning and those centered on automation. By employing a configurational and sector-specific approach, the study enhances the knowledge management literature by clarifying the circumstances under which AI adoption promotes organizational learning and the development of sustainable capabilities, rather than leading to a reduction in skills.