Convenor
Convenor's affiliation
Diego Matricano
Università degli Studi della Campania
Co-convenors
Francesco Schiavone, Ioana Stefan, Mariangela Vecchiarini
Abstract
Scholars interested in innovation have a clear overview of hypothetical innovation processes, their main phases and activities. They can begin with ideation and analysis, continue with applied research and product design, then move on to development and testing, before moving on to review and refinement. If the results are satisfactory, new products, services, or methods are released to market.
In this era of technological revolution, where AI is rapidly advancing and asserting its role, it is crucial to ask: when and how does AI replace researchers in innovation processes? How does this replacement occur?
This track calls for papers that can contribute to the field both empirically, identifying potential and risks, enablers and constraints, gaps and biases that may emerge when AI replaces researchers based on specific sectors, contexts, and researcher profiles, and theoretically, defining a theoretical framework capable of revealing the fundamental logic for further research.
Description
Scholars conducting research on innovation have a clear overview of hypothetical innovation processes, their main phases and activities (Ciarli et al., 2021; Stefan & Bengtsson, 2017). These processes can begin with the ideation and analysis phase (when problems are defined, initial state-of-the-art research is conducted, and the idea is generated), continue with applied research and product design (when data are collected and new products, services, or methods are designed), then move on to development and testing (when prototypes are developed and validated), before moving on to review and refinement (when final modifications/adaptations are made). If the results are satisfactory, new products, services, or methods are brought to market.
In this era of technological disruption (Pietronudo et al., 2022), when AI is rapidly advancing and asserting its role, it is crucial to ask: when and how will AI replace researchers in innovation processes? How does this replacement occur?
Unlike other streams of research, interested in when and how human-AI collaboration (HAIC) evolves (Jiang et al., 2023; Sowa et al., 2021), the focus here is on when and how the replacement of researchers by AI is conceived and implemented. It is interesting to investigate and clarify how managers identify and evaluate potential and risks, enablers and constraints, gaps and biases that can emerge depending on specific sectors, contexts, and research profiles. This is the type of empirical contributions this track evokes.
At the same time, this track also calls for papers that can contribute to the field from a theoretical perspective. If scholars already possess relevant evidence from specific fields, contexts, and research profiles, then new theoretical frameworks could be provided that reveal the fundamental logic for further research.
Overall, this track aims to contribute to the study of AI in innovation processes, starting with a focus on what comes before its implementation. This is a fundamental aspect that needs to be clarified to enable a more robust approach in the future.