Transformational Leadership, Followership, and Agentic AI Adoption: A Moderated Mediation Model of Team Learning and Project Efficiency in Bamenda, Cameroon

Purpose: This study examines how transformational leadership and followership dynamics shape the adoption of agentic artificial intelligence (AI) and its influence on the efficiency of agribusiness projects in Bamenda, Cameroon. 
Research Methodology: An explanatory sequential mixed methods design combined survey data from 278 agribusiness project leaders and team members with semi structured interviews with 12 organizational leaders. Quantitative data were analyzed with hierarchical regression and bootstrapping in SPSS version 27 and the PROCESS macro, and qualitative data were analyzed thematically following the six phase procedure of Braun and Clarke. 
Results: Agentic AI adoption significantly enhanced project efficiency (β=0.248, p<0.001). Transformational leadership positively moderated this relationship (β=0.147, p=0.007), with the strongest effect at high leadership levels (β=0.342). Followership enacted team learning behavior partially mediated the relationship (indirect effect = 0.086, 95% CI [0.032, 0.148]), and moderated mediation analysis confirmed that the indirect effect was conditional on transformational leadership. 
Conclusions: Technological adoption alone is insufficient. The relational synergy between transformational leaders and engaged followers is essential for optimizing agribusiness outcomes in resource constrained environments. 
Limitations: The study is confined to Bamenda in the Northwest Region of Cameroon, which limits generalizability, and its cross sectional data preclude definitive causal inferences. 
Contributions: The study advances leadership and followership theory by showing that follower enacted learning is the mechanism through which leader facilitated technology adoption translates into performance, and it offers guidance for leader and follower development and context sensitive AI implementation.