A Novel Enhanced Deep Generative AI Framework for Evoking Organizational Justice in an Educational Institutions

In the contemporary institutional landscape, maintaining the organizational justice for reshaping the traditional practices remains to be real challenge among the administrators. This hurdles the corporates and institutions for increasing their positive attitude of employees to move towards their commitments with the zero-false rates. As the Artificial Intelligence (AI) system has been integrated in the institutions, it engenders profound changes in organizational justice and work practices. These intelligent systems aids in analysing the employees performance data to provide the non-biased rewards and well establishes their work-life balances. This act as fair performance evaluation system in maintaining the organizational justice between the working employees and the authorities. But, incorporating these AI techniques in the organization needs to be recapped with the accuracy, robustness and reliability. To solve the aforementioned challenge, this research demonstrates the usage of fine-tuned generative AI framework for maintaining the organizational justice in the educational institutions. This AI system proposes the fine-tuned learning model with the Deep Seek R1 as the baseline architecture. The proposed framework consists of four important parts: 1) Data Collection Process 2) Data –Processing 3) Generative AI Framework 4) Recommendation System. In the first stage, 100 questionaries’ from the different educational institutions under Osmania University was collected. This data is used to design the fine-tuned Deep Seek R1model as the major core to recommend to maintain the organizational culture among the employees. The proposed framework was designed using Pytorch libraries. The suggested framework was evaluated and performance metrics such as accuracy, precision, recall, specificity and F1-score are calculated and compared with the traditional system. Experimental Outcomes demonstrates that this framework has outperformed the other existing methods and proved its vital role in deploying the broader lime light of AI entanglements on academic institutional structures.