Integrating AI in Organizational Management: Implications for Communication Strategies and Social Dynamics

Abstract

Communication strategies, decision making, and social dynamics have alike been changed by the integration of Artificial Intelligence (AI) to organizational management. The intent of this research is to examine how AI driven technologies, particularly machine learning, natural language processing (NLP), social network analysis (SNA), predictive analytics influences workplace efficiency and leadership effectiveness. The study analyzed AI’s role in optimization of customer relationship management (CRM), human resource management (HRM) and knowledge collaboration through the use of four AI algorithms, Random Forest, Long Short-Term Memory (LSTM), Graph Neural Networks (GNNs) and Reinforcement Learning (RL). Experimental results show that 60% reduction in communication errors, 35 percent increase in customer satisfaction and 50 percent improvement in employee performance are achieved by the use of AI based decision support systems. Also, Social network analysis powered by AI reduces the time for project completion by 30%, while Team collaboration is improved by 40% through AI powered social network analysis. But there are challenges in the adoption of the ethical AI like the job and mental health concerns caused by the AI, so that an ethical AI adoption strategy is required. The analysis is confirmed in terms of AI and its capability to increase organizational agility, leadership decision making and market competitiveness with existing literature. These findings imply that a beneficial balance of interaction between the AI and the human will be necessary for the sustainable use of AI. Future research should be directed towards hybrid AI frameworks that enable ethical governance to compensate for employee well being in corporate environments.