Prospective Sensemaking in the Front End of Innovation of AI Projects

Journal article, 2024

Overview: Using artificial intelligence (AI) to help develop new complex systems poses challenges for less tech-savvy organizations and may prolong the front end of innovation phase. Complications arise from diverging understandings of AI functionality and requirements among involved actors and the difficulties of determining the usefulness of AI in such a complex setting. This article explores a cross-industry project that entailed developing a functional prototype of an AI tool for planning (complex) energy systems in new city districts, engaging both system (domain) actors and AI developers. By analyzing prospective collective sensemaking processes in two episodes from the project, we discovered misaligned sensemaking processes between system actors and AI developers. During the project these actors alternated between "seeking" and "disengaging" sensemaking behavior. We highlight how various prototypes supported alignment in sensemaking processes concerning AI and progress in the project. Practitioners can use the managerial implications to better understand sensemaking dynamics in AI projects and implement suitable measures, like education or support at various stages of the project duration, to mitigate the problems that can arise due to misaligned sensemaking processes.
PRACTITIONER TAKEAWAYS: Recognize that the diverse actors in AI projects have different sensemaking needs and that gaps in knowledge may exist. Actively monitor for signs of seeking and disengaging among actors, and support behaviors that facilitate prospective collective sensemaking. Use boundary objects to facilitate prospective collective sensemaking, keeping in mind that the level of detail can support actors in different ways.