Software Agents as Information-Sharing Enhancers in Security-Sensitive Organizations

This study examines the influence of software agents on information-sharing behavior within security-sensitive organizations, where confidentiality and hierarchical culture often limit the flow of knowledge. While such organizations aim to collect, analyze, and disseminate information for security purposes, internal sharing dynamics are shaped by competing norms of secrecy and collaboration. To explore this tension, we developed a digital simulation game in which participants from security-sensitive organizations engaged in collaborative tasks over three rounds. In rounds two and three, software agents were introduced to interact with participants by sharing public and classified information. A total of 28 participants took part, generating 1626 text-based interactions. Findings indicate that (1) information-sharing patterns in security-sensitive contexts differ significantly from those in non-sensitive environments; (2) when software agents share classified information, participants are more likely to share sensitive data in return; (3) when participants are aware of the agents’ presence, they reduce classified sharing and increase public sharing; and (4) agents that share both public and classified information lead to decreased public and increased classified sharing. These results provide insight into the role of artificial agents in shaping communication behaviors in secure environments and inform strategies for training and design in knowledge-sensitive organizational settings.