The Human-AI Interface: Socio-Technical Challenges in Implementing Generative AI for Project Documentation and Governance

Abstract

The advent of Generative Artificial Intelligence (GenAI) is reshaping the landscape of project documentation and governance, offering benefits in automation, knowledge management, and decision support. But, the success of organizational adoption is not just about technology, it is also about collaboration between humans and AI, organizational governance, and socio-technical integration. This paper offers an exploratory literature review of the socio-technical issues involved in the adoption of GenAI tools in project documentation and governance. The relevant, peer-reviewed studies were identified in a structured search of the Scopus database, then screened with predetermined inclusion and exclusion criteria and assessed by means of a structured quality assessment framework. The selected studies were then analysed inductively to synthesise common challenges in implementation, prevailing research themes and conceptual links. The review synthesizes the literature into three interdependent pillars of responsible use of GenAI: technological trust and transparency, Human-AI collaboration and organizational governance. GenAI has great promise in enhancing the efficiency of documentation processes, organizational knowledge management, and decision-making support, but, there are significant challenges related to the reliability of output, explainability, data quality, accountability, ethical governance, regulatory adherence, cybersecurity, and user trust. The study builds on these insights and suggests a socio-technical conceptual framework that integrates these aspects into a unified view to inform people's understanding of responsible Human-AI collaboration in project settings. This work adds to the growing amount of literature by offering an interdisciplinary synthesis, bringing together technological, organizational, governance and human perspectives in a single conceptual framework. The results provide practical advice for project managers, organizational leaders, and policymakers aiming for the responsible implementation of GenAI and give direction for further empirical studies. Although the review was limited to peer-reviewed literature available in Scopus, the proposed framework offers a theoretically based grounding for empirical testing and refinement in a variety of organizational and industrial settings