| Sumario: | This paper presents management insights on how to develop knowledge-based culture with the integration of Artificial Intelligence (AI) and Internet of Things (IoT) with regards to their contribution to managing innovation and organizational governance under the digital transformation. The systematic secondary research design approach refines a systematic review of 5 major publications of 2025-2026 using thematic clustering of key terms such as knowledge agility, digital twins, and provisioning of edges and clouds. The literature mapping was carried out on 200 or more sources using web-based methods to search academic journals (e.g., Information, Systems, Scientific Reports) and perform bibliometric screening of results, as well as extracting quantitative evidence with frameworks of capabilities and model validations. The most important results include AI reconfiguration abilities leading to sustainable innovation (0.45, p<0.01; Cronbachs 0.9), and agility models providing 35 times quicker reaction to the market, and 92 times ML precision in learning societies. Digital twins based on IoT reduce fashion production time by 20 per cent, and KMS integrations simplified through Neural Networks and Case-Based Reasoning raise responsiveness by 35 per cent even with 85 per cent dependencies of data. The boundary-modeled architectures reduce latency by 70 (150ms to 45ms) to achieve 2 times throughput and 80 percent of governance automation. Altogether, they indicate that AI-IoT ecosystems can improve the knowledge flows, ethical decision-making, and resilience, but gaps in scalability still exist. This synthesis provides leaders with practical frameworks of competitive sustainable growth.
|
|---|