Abstract
Abstract
Purpose:
This research explores the theme of leadership communication within an organizational context where employees are more likely to receive mediated and individualized informational realities through artificial intelligence systems. It also explores how algorithmic filtering affects collective sensemaking, leadership legitimacy, and collective maintenance of meaning.
Design/methodology/approach:
A qualitative research design was employed with an interpretivist philosophical approach and an inductive methodology. Interviews with 20-30 organizational participants, with a range of leadership and employee-based roles, within AI-integrated communication environments. Reflexive thematic analysis, with the aid of NVivo software, was employed to investigate recurring patterns within the experience of leadership communication and sensemaking within algorithmically filtered communication environments.
Findings:
The results suggest that algorithmic personalization significantly influences employees' understanding of organizational priorities and leadership intention through the curated selection of organizational communications. This leads to informational fragmentation, which makes it challenging for employees to understand and align with organizational goals. As such, leaders are encouraged to provide interpretive, explanatory, and sense- giving activities to reconcile algorithmic recommendations with organizational goals and values. Transparency in algorithmic decision-making and shared understanding are thus critical to maintaining trust and leadership legitimacy in algorithmic-mediated organizational communication.
Originality/value:
This research contributes to the increasing body of research on leadership in AI-enabled workplaces by conceptualizing algorithmic filtering as a structural factor of internal organizational communication instead of a technical tool. The research contributes to the understanding of the dynamics of leadership authority and organizational coherence in the context of information visibility facilitated by artificial intelligence technologies, offering an empirical perspective on leadership in algorithmically mediated organizational contexts.
Keywords:
Artificial intelligence, leadership communication, algorithmic filtering, organisational sensemaking, informational fragmentation