Integrating Artificial Intelligence into the Analysis of Organizational Politics in Academic Settings: Drivers and Effects on Staff Behavior

State Universities, organizational politics, snow ball sampling, replication logic, explanatory-qualitative analysis, pattern matching technique (matrix)

The study focuses at cultural aspects of organizational politics in Indian State Universities in order to place this institutional kinetics within broader conversations about meritocracy, transparency, and the evolving role of artificial intelligence in organizational research. Organizational politics are perceived as a response to ongoing resource limitations, ambiguous policy processes, and external political interference, all of which threaten cooperative and performance-oriented learning environments. To identify the fundamental factors that drive employees' political behavior, an explanatory qualitative study approach was utilized. In order to gain access to secret and politically sensitive networks, 41 academic and non-academic staff members from State Universities in Madhya Pradesh were chosen by snowball sampling for semi-structured interviews. The investigation methodically compared theoretically informed expectations with empirically occurring themes using replication logic and pattern matching. The results show that senior staff members are more involved in macro-level political maneuvering related to control over       resources, appointments, and policy implementation, whereas lower-ranked personnel are more involved in micro-level, daily politics. The lack of merit-based systems, restricted policy transparency, and national political parties' control over public finances and institutional governance all exacerbate political behaviors. According to the study, strong resource management techniques and open, consistently implemented laws can lessen the dysfunctional effects of organizational politics, even when political meddling and resource scarcity are enduring contextual elements. Future AI use in qualitative analysis: The paper also describes how AI-based methods for coding and pattern recognition can be used in organizational politics research in the future, although the results will still need to be interpreted and explained by the researchers.