Rapidly increasing applications of Digitalization and Artificial Intelligence (D&AI) are already impacting our day-to-day life substantially, along with social and economic prospects worldwide. The accelerating utilization of D&AI has stirred the discussion concerning the responsible application of technologies for assisting the implementation of the Sustainable Development Goals (SDGs). D&AI can raise productivity, lower costs, reduce resource intensity, and enable efficient public services. However, there are also risks and downsides that we all must identify and tackle to address any potential short-/long-term undesired impact. Notably, there exists a gap in knowledge about the mutual relationships between D&AI and the 17 SDGs. To address this gap and gather broader perspectives of experts on the potential uses and pitfalls of D&AI for SDGs and their respective indicators, we propose a participatory research approach: the Digitalization–Sustainability Matrix (DSM). The DSM serves as a means for collaborative methods, such as participatory action research (PAR), for the knowledge production process. We exercised the DSM in the Digitainable Thinkathon event, a gathering of experts from diverse sectors and backgrounds for capturing the action-oriented dialogues concerning the use of D&AI technologies for the indicators of SDGs 4 (Education) and 13 (Climate Action). As a tool, the DSM aided in the discussion by systematically capturing transdisciplinary knowledge generated on several aspects, such as: (1) the need for research–practice nexus action; (2) data-capturing efforts and social considerations; (3) collaborative planning for utilizing the power of D&AI; (4) lessons from the diverse community to encourage the purposeful use of technologies. Overall, the proposed approach effectively triggered a discussion on the crucial aspects that need to be considered for D&AI’s practices, a step towards deep-rooting the transdisciplinary perspectives for meaningful use of D&AI for SDGs.

Serious Games (SG) have shown potential as transformative tools in sustainability research. Despite the diverse and widespread adoption of SG as multifunctional tools within collaborative forms of knowledge production, their contribution to transformative research processes is underexplored. Likewise, the selection, alignment, and integration of appropriate SG tailored to specific stages of a transformative research process lacks clear guidelines. To fill this gap, we aim to map the potential of SG in transformative research. We propose to facilitate the assessment of SG alignment and to guide their integration within a transformative research process based on three dimensions: SG complexity levels, SG collaborative engagement levels, and generic stages of transformative research processes. This study explores and organizes the space of potential uses of SG in transformative research based on the three aforementioned dimensions. It provides guidelines to facilitate the assessment of each SG's suitability and its integration within the transformative research process. It operationalizes the proposed conceptual mapping and guidelines with the help of two SG examples. Future work should empirically validate the approach across diverse contexts and address scalability, long-term impacts, and ethical considerations in resource-constrained settings.