This Journal of Enterprise Information Management special issue seeks to develop a theoretical and practical understanding of how Generative AI (GenAI) is relevant in promoting digital transformation, knowledge management in organizations, resilience, and entrepreneurial ecosystems, such as start-ups and SMEs. It bridges key gaps in current literature, e.g., the implementation of GenAI to the theory of entrepreneurship (e.g., effectuation, action, creation), models of digital transformation, and strategies to capitalize on the technology, and its effect on the knowledge processes, including creation, acquisition, and dissemination.
The technical side of GenAI has been discussed in the scholarly literature, but not the critical consideration of how AI can be used as an entrepreneurial tool, such as effectuation (Sarasvathy, 2001), action (McMullen and Shepherd, 2006), and creation (Alvarez and Barney, 2007). Digital transformation guidelines have not been developed yet (Bawack et al., 2021), nor have approaches to utilize GenAI (Prasad Agrawal, 2023) and its restructuring of knowledge management theories (Sahibzada et al., 2021). The urgency is emphasized by the fact that ChatGPT has registered the largest number of users per month (200 million) in record time (Hu, 2023) and that McKinsey forecasts an increase of 3.3% per year in productivity (Chui et al., 2023). GenAI can address the productivity paradox (Ettling, 2023), organizational resilience in dynamic times (Muneeb et al., 2022), entrepreneurial creativity (Norbback and Persson, 2023), and sustainable innovation with new start-ups and SMEs (Mangla et al., 2020) so that these gaps can be addressed in the future through targeted and dedicated research.
This special issue will also address such issues of society as the productivity paradox, in which the expected economic benefits of technological progress are not realized, and the vulnerability of entrepreneurial ecosystems to uncertain markets. Its frameworks of organizational resilience and agility enable start-ups and SMEs to remain innovative so that the chances of job displacement are reduced, and worker productivity is enhanced in such industries as call centers. It also fills knowledge gaps in dynamic environments, which encourages fair access to creativity and decision-making tools.
List of Topic Areas
How is GenAI steering the transformation of digital platforms in organisations? In this context, we invite the researchers to (not limited to) address the following:
- Studies specifically investigating the transformative value of GenAI for digital platforms, such as facilitating interactions in organisations that were non-existent before.
- How does it create value for different stakeholders, for example, the creation of unprecedented forms of personalisation, called hyper-personalisation, for individual users?
- Investigating different digital transformation strategies and best practices that firms can adopt to leverage GenAI in the context of organisations.
- How is technology revolutionising the entrepreneurial ecosystem and facilitating the creation of startups? What business sectors are the most affected? What are the critical success factors? What factors are crucial to support the sustainability of these startups?
- How is GenAI resolving the knowledge problem inherent in entrepreneurial ecosystems and other issues? For example, how does it affect management and individual entrepreneurship orientation (Townsend & Hunt, 2019; Yadav et al., 2021).
- Is GenAI technology revamping the seminal theories and working on entrepreneurial ecosystems and startups, such as developing new models of innovation specifically applicable in the context of GenAI?
- Organisational roadmaps.
- How will it build organisational resilience? Suggesting frameworks to aid in building resilience and overcoming the risks associated with the use of this technology.
How can it be used to predict organisational agility? How will it contribute to organisational agility? - Research works exploring how GenAI will affect the process of organisational knowledge management, viz., creation, acquisition, storage, and dissemination of organisational data.
- Will GenAI impact the different types of knowledge managed in enterprises, such as tacit, implicit, and explicit knowledge? What would be the challenges associated with each category? For example, typically, tacit knowledge is the most difficult to capture; however, will GenAI overcome this limitation?
- How is GenAI enhancing worker productivity? How will it reshape the way workers learn in firms? Will the process of acquiring knowledge in organisations become easier through this technology?
- How do GenAI tools and adoption for knowledge management affect the popular/seminal works and management theories of knowledge management (for example, Nonaka and Takeuchi’s theory of knowledge multiplication, Kolb’s learning model, Social capital theory, etc.)?
Journal Information: Scopus Journal Q1, H-Index 89
Submission Information
Submissions are made using ScholarOne Manuscripts. Registration and access are available here:
Author guidelines must be strictly followed. Please see:
Authors should select (from the drop-down menu) the special issue title at the appropriate step in the submission process, i.e. in response to “Please select the issue you are submitting to”.
Submitted articles must not have been previously published, nor should they be under consideration for publication anywhere else, while under review for this journal.
Key Dates
Opening date for manuscript submissions: 17 November 2025
Closing date for manuscript submissions: 1 May 2026
For more details refer here
