Measuring Collaborative Maturity in Human–AI Work: Development and Validation of the CIQ Scale

Abstract

Background: Collaboration has emerged as an essential capability because it helps us achieve effective collective performance  something we are now doing more often in digital and cross-functional organizations. Although the collaborative activities are becoming more intense, a variety of inconsistencies remain in terms of outcomes given the differences in shared cognition, interaction quality, and role integration between human beings and artificial intelligence (AI). This gap signifies the necessity of a holistic measurement tool that is able to quantify collaborative maturity in human–AI integrated workflows.

Objectives: This paper aims to develop and validate the collaborative intelligence quotient (CIQ) scale as a supporting diagnostic construct for measuring the collaborative maturity of human–AI integrated workflows in the diverse property development and integrated township sector in Indonesia.

Methods: A scale-development protocol was conducted using a purposive sample of 32 managerial practitioners in Indonesian property firms. Dimensionality, reliability, and convergent validity were examined sequentially using EFA followed by CFA.

Results: The EFA suggested a four-factor structure, and the CFAs conducted for further purification led to a relatively simple measurement model with three latent dimensions (Adaptive CoLearning; Cognitive Synchronization & Fluency Interaction; Human-AI Complementary Intelligence) and nine out of eleven indicators. The final model showed adequate internal consistency and convergent validity.

Conclusion: CIQ is a psychometrically reliable tool to systematically chart organizational collaborative maturity in utilizing AI for teamwork, and it could serve as an end-to-end foundation on which subsequent structural testing and capability scaling may be operationalized.