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Abstract

Background: The sudden emergence of Generative Artificial Intelligence (GenAI) is transforming IT management and software engineering, but its organizational implications have not been examined comprehensively. Objective: The purpose of this research was to analyze how the integration of GenAI into software development processes affects developer productivity, software quality, process effectiveness, and managerial decision-making, as well as determine organizational factors that contribute to successful implementation. Methodology: A mixed-method approach was used with 200 IT managers from 50 firms. Quantitative measures of productivity, code quality, workflow quality, and decision speed were gathered pre- and post-GenAI integration and examined with paired t-tests and multiple regression. To gain qualitative data pertaining to the barriers and facilitators of adoption, the interviews were conducted in a semi-structured manner and 20 managers were thematically coded. Results: Along with GenAI for the first time, integration resulted in impressive performance improvements including 49.7% increase in productivity, 52.1% decrease in code errors, and 50% enhancement in workflow efficiency (p < .001). Regression analysis found that productivity, code quality, and decision speed in aggregate accounted for 68% of the variance in workflow efficiency. Thematic analysis focused on managerial support, scheduled training, and change management as fundamental to the resolutionof the skill and resistance gaps. Conclusion: The results indicate that GenAI can dramatically improve the productivity of software engineering when combined with appropriate IT management. The case of GenAI makes the point that when advanced technology is paired with skilled personnel, balanced governance, and clear-sighted management, the result is effective increase in productivity and quality from software development systems