Making sense of artificial intelligence : how International IDEA built an electoral assistance initiative in response to a novel external shock

Abstract

This research examines how an intergubernmental organization made sense of artificial intelligence as an emerging challenge to its mandate. The organization's team responsible for digitalization and democracy faced fundamental uncertainty: what did AI mean for electoral management, what role should the organization play, and what responses would align with its democratic mandate?

The study applied three sensemaking frameworks simultaneously: Weick's (1995) seven properties describing foundational conditions, Jeong and Brower's (2008) Noticing-Interpretation-Action model tracking episodic awareness to response processes, and Weick et al.'s (2005) Enactment-Selection-Retention cycle capturing organizational level accumulation over time. Semi structured interviews with team members were coded, assigning passages to thirteen analytical nodes representing the three theoretical layers, and processed through a general inductive approach content analysis.

The analysis reveals that these frameworks, while conceptually distinct, operated as an empirically integrated system. Multiple coding patterns showed 47 instances where the same passage received codes from different frameworks simultaneously, demonstrating that they describe the same sensemaking reality from different analytical levels.

The findings extend sensemaking theory by demonstrating empirically that researchers need analytical tools operating at multiple levels simultaneously, which come from a single team within one organization addressing one external challenge over a specific period.