The intersection of Knowledge Management (KM) and Artificial Intelligence (AI) is rapidly transforming how organizations create, share, and apply knowledge to pursue sustainability. In this context, 'intelligent knowledge' refers to the management of knowledge systems that dynamically combine human cognitive capacities with advanced AI-driven tools and models to facilitate ethical, inclusive, and purpose-driven innovation. This Special Issue examines how intelligent knowledge management systems can enhance organizations' innovation capacity and align their efforts with environmental, social, and governance (ESG) commitments and the Sustainable Development Goals (SDGs).
The convergence of Knowledge Management (KM) and Artificial Intelligence (AI) is increasingly recognized as a pivotal driver for advancing organizational sustainability in the digital era. In today's complex business landscape, organizations face challenges in developing intelligent knowledge systems—AI-augmented frameworks designed to support sustainable decision-making, foster innovation, and ensure strategic alignment with long-term value creation goals. The emergence of generative AI and large language models (LLMs) is transforming knowledge processes, enabling organizations to dynamically retrieve, synthesize, and apply knowledge to address complex sustainability challenges.
While traditional Knowledge Management (KM) has primarily focused on the systematic processes of creating, storing, sharing, and applying knowledge, the integration of Artificial Intelligence (AI) introduces new dimensions of computational intelligence that enhance and, in some cases, automate these foundational functions. AI-driven technologies are increasingly supporting knowledge-based decision-making, thereby fostering the emergence of intelligent knowledge systems that can reason, learn, and act based on context-aware insights to promote sustainable and purpose-driven outcomes. Within KM theory, the enduring distinction between tacit and explicit knowledge remains highly relevant: while AI excels in processing and managing explicit knowledge, the challenge of capturing and leveraging tacit knowledge persists, particularly in enabling meaningful and ethical human-AI collaboration. Recent studies emphasize that AI should be viewed as augmenting, rather than replacing, human expertise in sustainability-oriented knowledge work, thereby reaffirming the centrality of co-creation within contemporary knowledge management frameworks.
The evolution of KM in the AI era thus calls for new conceptual models and dynamic strategies that can support knowledge environments aligned with long-term sustainability objectives. As organizations strive to integrate human and AI cognition into their knowledge systems, the ability to flexibly interact with and adapt through AI-generated insights becomes a defining capability for intelligent knowledge management. The impact of AI on organizational learning and strategic knowledge flows must be critically assessed from a sustainability perspective, recognizing that AI technologies can either enhance or threaten knowledge-based resilience and responsible innovation. Generative AI and machine learning models are reshaping the landscape of KM, revolutionizing how organizations capture, synthesize, and apply knowledge to create sustainable value.
While large language models (LLMs) and AI-driven knowledge repositories significantly increase the speed and scope of knowledge retrieval and decision support, they also introduce critical risks related to epistemic validity, algorithmic bias, and the sustainability of automated knowledge production. These challenges are especially acute when AI-generated knowledge informs decisions with significant social or environmental implications, where the accuracy, contextual sensitivity, and ethical integrity of outputs are vital for maintaining organizational trust, legitimacy, and long-term innovation capacity.
This Special Issue aims to foster a deeper understanding of how intelligent knowledge systems, powered by the integration of AI technologies, human cognition, and contemporary KM practices, are transforming the pursuit of sustainability, innovation, and responsible governance within organizations. We invite contributions that critically explore how human-AI collaboration can be harnessed to develop resilient, ethical, and sustainability-oriented knowledge ecosystems. Beyond conceptual and theoretical contributions, we particularly encourage empirical studies that provide evidence-based insights into how intelligent knowledge processes enhance sustainability performance, strengthen ESG strategies, and promote adaptive, long-term value creation. Given the transformative impact of AI on knowledge flows and strategic decision-making, special attention will be devoted to research that examines the capabilities, limitations, and practical applications of AI-enabled knowledge systems, including generative AI tools and large language models (LLMs), in advancing sustainable organizational practices.