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Decision Aware Human AI Collaboration for Industrial Digital Products

Reference number
Coordinator Mittuniversitetet - Institutionen för kommunikation, kvalitetsteknik och informationssystem (KKI)
Funding from Vinnova SEK 3 162 000
Project duration April 2026 - April 2028
Status Ongoing
Venture Advanced digitalization - Industrial needs-driven innovation
Call Industrial applied AI by advanced digitalization 2026

Purpose and goal

The project investigates how AI-supported work environments can support decision awareness and decision quality in industrial software development. In collaboration with Volvo Group, the project studies how micro-decisions and hidden decisions emerge when different professional roles work with generative and agentic AI. The aim is to build empirically grounded knowledge and design principles that support transparent and traceable human-AI collaboration in complex software-based products.

Expected effects and result

The project is expected to deliver empirical insights into how micro-decisions and hidden decisions emerge in AI-supported workflows, along with design principles for role-adaptive decision support. The results may strengthen Swedish industry’s ability to use AI in a traceable, trustworthy, and responsible way, particularly in complex industrial development environments. Academic publications and practitioner-oriented guidelines are planned to be openly available.

Planned approach and implementation

The project follows a design science approach in four phases: empirical understanding of the problem, iterative artifact development, evaluation in an industrial context, and knowledge synthesis and dissemination. An initial qualitative study with Volvo Group examines challenges and opportunities as different professional roles begin working with generative and agentic AI. Findings from each phase are refined through workshops, field studies, and co-design with practitioners.

The project description has been provided by the project members themselves and the text has not been looked at by our editors.

Last updated 28 May 2026

Reference number 2026-00111