Knowledge management (KM) is a systematic process through which organizational knowledge is identified, collected, organized, stored, and ultimately shared to enhance decision-making, increase productivity, and foster innovation. As a core concept of the information era, KM plays a vital role in improving organizational performance. A key pillar for advancing KM is artificial intelligence (AI)—yet it has often received insufficient attention from KM practitioners and theorists. Given the complexity of large, multilayered organizations such as Iran’s Social Security Organization, KM cannot rely solely on traditional approaches. The introduction of AI into KM has produced notable effects, including greater efficiency and improved organizational processes.
This study aims to design an AI-based KM framework for complex organizations. Adopting a qualitative design and a grounded theory approach, the research population comprised IT managers and specialists of the national Social Security Organization. Data were gathered through semi-structured interviews with 27 academic and executive experts in KM and information technology and continued until theoretical saturation was reached. Snowball and purposive sampling were employed. Data analysis identified 21 influential components grouped into causal and contextual conditions, intervening factors, strategies, and outcomes of AI-enabled KM. Trustworthiness was assessed and confirmed using the criteria of Lincoln and Guba (1985).
The findings center on the “intelligentization of knowledge management” as the model’s core phenomenon. Within the proposed framework, the causal conditions include six components: the need for organizational currency (up-to-dateness), transforming raw knowledge into actionable knowledge, responding to employee demands, cost reduction and loss prevention, the inefficiencies of the status quo, and customer-centricity. The contextual conditions include four components: availability of requisite infrastructures, strategic investment, excellence of internal systems, and improved organizational management. The intervening conditions comprise two components: extra-organizational and intra-organizational factors. The strategies dimension includes five components: implementing customer relationship management, executing strategic management, fostering motivation to increase employee participation, and outsourcing technological services. The outcomes include four components: sustainable organizational growth, enhanced corporate image, client (customer) satisfaction, and organizational survival.
In sum, applying this framework can help the Social Security Organization’s managers address existing KM challenges, improve the organization’s public image and client satisfaction, and achieve organizational growth culminating in sustained survival.