Integrating Generative AI Into Organizational Workflows: Evidence From Practitioner Reports
TL;DR
The findings indicate that GenAI use is widespread in the sample, but integration into business processes is incremental and localized rather than deeply embedded and governance practices are evolving alongside its use.
Abstract
This study examines how organizations integrate generative artificial intelligence (GenAI) into everyday business processes and workflows, and how governance practices are emerging alongside such integration. While prior research has focused on task‐level performance effects or adoption intentions, less evidence examines how GenAI is embedded in organizational workflows and governed in practice. The study adopts an exploratory, descriptive research design based on survey data collected from 120 practitioners across organizations of varying sizes and sectors. The survey captures reported patterns of GenAI use, workflow integration, governance practices, safeguards, and outcomes, and the analysis relies on descriptive statistics and exploratory comparisons across organizational contexts. The findings indicate that GenAI use is widespread in the sample, but integration into business processes is incremental and localized rather than deeply embedded. Many organizations rely on third‐party tools and user‐driven experimentation, while deeper enterprise‐level integration and formal governance arrangements are less frequently reported. The results show uneven development between workflow‐level use, technical embedding, operational transformation, and governance formalization. Operational safeguards appear more common than enterprise‐wide governance structures. Respondents report improvements in efficiency, productivity, and decision‐making alongside concerns about privacy, security, bias, and explainability, indicating experimentation. This study provides cross‐organizational, practitioner‐reported descriptive evidence on how organizations are integrating GenAI into business processes and how governance practices are evolving alongside its use. The findings extend current empirical understanding of how organizations are reporting early GenAI use and governance in practice by moving beyond isolated tasks and adoption intentions to examine workflow‐level integration across organizations.