The paper is dedicated to the post-truth mini track. There are unprecedented challenges in terms of the reliability of data, knowledge, information that address important questions regarding traditional KM. The paper main goal was to investigate the systemic mechanics of organizational communication and strategic clarity, by isolating the behavioral patterns of the institutional “bullibility” and the cognitive exhaustion. From a methodological point of view, the paper uses mixed-methods that support an interdisciplinary approach. Psychometric scale evaluations demonstrated internal consistency for both the Corporate Bullshit Receptivity Score (CBRS; α = 0.935) and the Operational Clarity Baseline (OCB; α = 0.801). Pearson’s r correlations revealed a significant, positive relationship between jargon receptivity and operational data baselines (r = 0.433, p < 0.001), alongside a significant link between high reliance on operational clarity and heightened crisis-induced jargon exhaustion (r = 0.220, p = 0.011). The paper argues that, in order to navigate post-truth complexity knowledge-based organizations have to move further the pseudo-profound administrative jargon. We highly recommend that organizations have to apply a more human-oriented transformational leadership model, capable of driving cooperation and collaborative dialogue through decentralized networks of competent teams and communication frameworks rooted in empathy and transparency.
Municipal mergers are commonly examined through their effects on administrative efficiency, expenditure, and service delivery. Yet, their success also depends on the capacity to integrate the knowledge, competences, routines, and institutional memories embedded within previously autonomous organizations. This paper reconceptualizes municipal amalgamation as a knowledge-intensive organizational transformation and investigates how Knowledge Management (KM) can support organizational integration and Public Value co-creation. The study adopts a conceptual research design supported by an exploratory case study of Nuova Pescara, one of the largest municipal merger processes currently underway in Italy. Drawing on documentary and institutional evidence, the analysis interprets the merger’s as-is, to-be, and gap analysis phases through the lenses of Knowledge Management, Organizational Learning, and Public Value. The findings suggest that administrative integration should be understood as the outcome, rather than the starting point, of a progressive knowledge integration process. Building on these insights, the paper develops a Knowledge Integration Governance Framework in which knowledge transfer, combination, and creation, supported by organizational learning and Strategic Human Resource Governance, transform distributed knowledge into shared organizational capabilities. The study contributes to Knowledge Management research by positioning knowledge integration as a strategic governance capability enabling institutional transformation and creating the organizational conditions for Public Value co-creation.
Artificial intelligence (AI) is transforming digital knowledge systems (DKS), reshaping how organizations generate, interpret, and apply knowledge in support of organizational learning and strategic decision-making. While AI-enabled systems enhance analytical capability, predictive insight, and information processing speed, their implications for learning quality and epistemic judgment remain insufficiently understood. This study addresses this gap through a systematic literature review that synthesises research across knowledge management, information systems, and organizational learning. Adopting a concept-centric approach, the review analyses peer-reviewed studies published between 2000 and 2026, focusing on how AI-enabled digital knowledge systems are conceptualised and how they influence knowledge processes, organizational learning, and strategic decision-making. The findings indicate a shift from viewing digital knowledge systems as passive repositories toward conceptualising them as mediating infrastructures that augment, generate, and orchestrate knowledge. These systems expand knowledge creation through data-driven insights, enhance knowledge sharing through algorithmic mediation, and increasingly shape how knowledge is applied in decision contexts. However, the analysis also reveals a tension between informational efficiency and authentic learning. While AI-enabled systems support sensemaking and improve decision support under conditions of uncertainty, they may encourage overreliance on algorithmically generated outputs, reduce opportunities for critical reflection, and narrow interpretive perspectives. These dynamics highlight the importance of governance conditions, including epistemic transparency, trust calibration, and learning-oriented organizational practices. The study develops an integrative framework that positions AI-enabled digital knowledge systems as mediating infrastructures linking knowledge processes to organizational learning and strategic decision-making under specific governance and learning conditions. The findings contribute to knowledge management and information systems research by providing a coherent conceptualisation of how AI-enabled systems reshape the epistemic foundations of learning and decision-making in contemporary organizations.
This position paper argues that the integration of AI-generated information has the potential to disrupt existing human agencies in organizational routines. This disruption of agency is a result of displacement of judgement particularly when routine automation reduces human agency to higher dependencies on these AI outputs leading to lower sense-making. Reinforcement of agency requires conscious moves between different epistemic modes translated into Human Resource Management (HRM) and Knowledge Management (KMM) frameworks and processes. Such a robust epistemological framework epistemological framework relies on orchestrating coherence between high-level exploratory knowledge and low-level pragmatic knowledge that enables justifying, validating by human agents.
In the post-truth era, organisations face a critical vulnerability that we frame under epistemic permeability, a process through which external, radicalised digital regimes infiltrate organisational sensemaking and the workplace. These alternative truths, specifically those originating in the manosphere, challenge the foundations of institutional expertise and Equity, Diversity, and Inclusion frameworks. While traditional knowledge management focuses on internal flows, it often remains epistemically blind to the sophisticated architectures of digital subcultures that compete for authority in the minds of the employees. This study employs a netnographic analysis of the French manosphere on mainstream social media platforms Instagram and TikTok to explore the mechanisms through which ideological claims acquire their authority. Our preliminary findings reveal that these regimes are built through four interconnected mechanisms: the construction of experiential authority via embodied proof, the use of intellectual eloquence and the hijacking of academic rhetoric to provide a facade of analytical rigour, the framing of gender hierarchy as an objective biological fact, and the strategic penetration of organisational vocabularies using corporate palatable concepts. By mapping how these sanitised narratives migrate from the digital fringe into the workplace, we argue that organisations must move beyond conventional codification and compliance. Instead, they should develop resilient governance models centred on epistemic literacy and the critical evaluation of contested truths to safeguard institutional integrity.
