In contemporary organizational theory, the capacity to share knowledge efficiently is increasingly recognized not merely as a good practice, but as one of the central levers of influence, innovation, and competitive advantage. Influence in the workplace is no longer determined solely by formal authority or proximity to decision-makers; it hinges instead on who opens up their ideas, disseminates outcomes, and builds collective awareness. Knowledge sharing, properly conceived, is a social process that undergirds learning, creativity, and organizational agility.

Why Sharing Still Matters
Even with advances in digital collaboration tools, hybrid work environments, and more explicit knowledge management policies, many organizations continue to wrestle with information silos, “knowledge hoarding,” and weak visibility of what colleagues are doing. These behaviors impose hidden costs: duplication of work, failure to capitalize on existing insights, slow adoption of innovations, and organizational inertia.

Empirical studies confirm that when organizational climate is supportive, when centralization and formalization are lower, knowledge sharing behavior (KSB) tends to increase. For example, a recent study of IT firms in Vietnam (n = 529) found that a positive organizational climate had a direct positive effect on KSB, while high degrees of centralization and formalization decreased knowledge‐sharing intentions.  

Moreover, knowledge sharing is strongly associated with improved performance outcomes. In technological companies in China, for instance, research shows that AI-augmented knowledge sharing, along with organizational learning and dynamic capabilities, positively affect job performance.  

Theoretical Foundations & Diffusion of Influence
A number of established frameworks help us understand both how knowledge spreads and why sharing can shift influence within organizations.
• Diffusion of Innovations (Everett Rogers et al.): This theory explains how new ideas are adopted across a social system over time via innovators, early adopters, early majority etc. Key variables include communication channels, time, social systems, and the characteristics of the innovation itself.
• Threshold Models & Critical Mass: Recent experiments suggest that when a certain proportion of individuals (often around 20-30%) behave in a particular way (e.g. adopting or sharing an innovation), that can tip the whole system into broader adoption. For example, one study found that social diffusion leading to change in norms becomes much more probable once a committed minority exceeds roughly 25% of the population.
• Organizational Climate & Intention/Behavior Models: Behavior intentions (e.g. willingness to share) are shaped by trust, perceived support, alignment of individual and organizational values, and perceived risk/benefit. These mediate whether knowledge is actually shared or hidden.  

Barriers & Enablers
Understanding why people don’t share is as important as understanding why they do.

Barriers include:
• Structural impediments like overly centralized decision frameworks, rigid hierarchy, heavy formalization. These reduce the avenues for informal sharing and flatten the perceived payoff for going outside established channels.
• Cognitive or psychological obstacles, such as fear of criticism, loss of advantage (“knowledge as power”), lack of trust, or simply not knowing who might benefit from what one knows.
• Technological and process deficiencies: poor documentation practices, weak knowledge management systems, lack of standard archiving, difficult to locate material, etc. These make sharing costly in terms of effort, risk of misunderstanding, or duplication.  

Enablers include:
• Cultivating a learning culture: where mistakes are not punished, where experimentation is supported, and where informal learning is valued. Studies in team climate show that the presence of an “organizational learning culture” correlates strongly with innovative work behavior.
• Leadership that is supportive of sharing: transformational, inclusive leadership, openness to new ideas even when they challenge orthodoxy. Leaders who make visible their support for sharing set norms.
• Recognition, incentive alignment, and reward systems that explicitly value sharing. When sharing contributes to promotions, performance evaluations, or peer recognition, people are more likely to invest effort in it.  

Influence through Sharing: A Refined Model
Putting this together, here is a refined model of how sharing translates into influence:
1. Visibility: Sharing makes one’s work visible across formal and informal networks. Visibility breeds recognition.
2. Peer Adoption & Critical Mass: Innovation often needs a threshold of peer adoption. Once enough people (often around 20-30%) accept or discuss an idea, it tends to propagate more broadly. Early informal sharing helps reach that threshold.
3. Legitimization & Institutionalization: When enough peers accept an idea, it begins to be noticed by formal leadership, which may then adopt it as part of official strategy or practice. What was once “radical” becomes “official.”
4. Influence & Reward: As an individual or team’s ideas get absorbed into the organizational narrative, their influence increases. They may be entrusted with leadership, provided more resources, or seen as agents of change.

Recent Considerations: Hybrid Work, Digital Tools, AI
Over the past few years, changes in how and where people work, plus the integration of AI into knowledge-sharing tools, add new dimensions:
• Remote and hybrid setups tend to magnify the problems of invisibility and isolation; informal corridor conversations or impromptu check-ins become less likely. Organizations must work harder to construct virtual equivalents (e.g. asynchronous documentation, digital forums, internal social networks).
• AI and knowledge-management platforms can help accelerate sharing, reduce friction (e.g. discovery of existing reports, automatic tagging, summarisation), but they also risk over-trust in automation or leaving behind tacit knowledge that is hard to codify.
• Given the increasing volume of information, selective sharing and curating become skills. Not every detail needs to be shared widely, but knowing what, when, and how to share is part of influence.

Implications for Practice
For individuals aiming to increase their influence via sharing:
• Embed documentation and archival processes into every project (e.g. phase reports, lessons learned).
• Use both formal and informal channels: internal blogs or newsletters, but also coffee chats, virtual social spaces.
• Be willing to experiment, share preliminary findings; feedback improves ideas and increases visibility.

For organizations:
• Build a culture that rewards sharing explicitly through performance systems.
• Reduce structural barriers like overly centralized control or onerous formalization.
• Provide tools and training to lower the effort of sharing; make knowledge easier to find and use.
• Encourage cross-team interactions, peer networks, communities of practice.

Final Word
Sharing is not just a morally good or nice thing to do, it is one of the most potent forms of influence in knowledge-based work. It transforms static assets into living processes, elevates visibility, enables innovation, and shapes organization culture. As the world of work continues to evolve, those who master the art and science of sharing will increasingly become the architects of change.

References:
Here are key sources that discuss the concepts above. You can draw on these for citations or further reading.
1. Xu, J., et al. (2023). A theoretical review on the role of knowledge sharing and … [PMC]
2. Peters, L.D.K., et al. (2024). “‘The more we share, the more we have’? Analyses of identification with the company positively influencing knowledge-sharing behaviour…”
3. Greenhalgh, T., et al. (2004). “Diffusion of Innovations in Service Organizations.” Milbank Quarterly – literature review on spreading and sustaining innovations.
4. Ye, M., et al. (2021). “Collective patterns of social diffusion are shaped by committed minorities …” Nature Communications
5. Bui, T. T., Nguyen, L. P., Tran, A. P., Nguyen, H. H., & Tran, T. T. (2023). “Organizational Factors and Knowledge Sharing Behavior: Mediating Model of Knowledge Sharing Intention.”
6. Abbasi, S. G., et al. (2021). “Impact of Organizational and Individual Factors on Knowledge Sharing Behavior.”
7. He, M., et al. (2024). “Sharing or Hiding? Exploring the Influence of Social … Knowledge sharing & knowledge hiding mechanisms.”
8. Sudibjo, N., et al. (2021). “The effects of knowledge sharing and person–organization fit on teachers’ innovative work …”
9. Academia preprint: Cui, J., et al. (2025). “The Explore of Knowledge Management Dynamic Capabilities, AI-Driven Knowledge Sharing, Knowledge-Based Organizational Support, and Organizational Learning on Job Performance: Evidence from Chinese Technological Companies.”
10. Koivisto, K., & Taipalus, T. (2023). “Pitfalls in Effective Knowledge Management: Insights from an International Information Technology Organization.”