TL;DR
The study demonstrates that the successful deployment of AI Builder is contingent more on organizational readiness and accountability than technological maturity, and offers an informed blueprint to organizations adopting low-code AI platforms.
The study demonstrates that the successful deployment of AI Builder is contingent more on organizational readiness and accountability than technological maturity, and offers an informed blueprint to organizations adopting low-code AI platforms.
The study contributes to information systems research by reframing AI readiness from a static resource inventory to an evolving organisational capability and offers managers a diagnostic logic for sequencing AI investments and avoiding premature scaling.
The findings reveal that human - AI collaboration has a significant positive effect on project management performance, particularly in improving cost efficiency, schedule adherence, and quality delivery, indicating that organisations with strong digital infrastructure, skilled personnel, and supportive leadership derive greater benefits from AI integration.
The findings show that dynamic capabilities – sensing, seizing and transforming – are distributed across levels and shaped by bottom-up and top-down mechanisms, which advances dynamic capabilities theory by demonstrating its multilevel nature in the public sector.
An exploratory literature review of the socio-technical issues involved in the adoption of GenAI tools in project documentation and governance 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 study contributes a unified research model for stakeholder-specific AI adoption, demonstrates a mixed quantitative-qualitative approach, and establishes a scalable foundation beginning with engineers and extending to other stakeholders through future empirical validation.
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