AI-enabled co-creation for evidence-based policymaking: A conceptual model

Nina Rizun; Noella Edelmann; Tomasz Janowski; Aleksandra Revina

doi:10.59490/dgo.2025.991

AI-enabled co-creation for evidence-based policymaking: A conceptual model

Abstract

This study focuses on developing and validating the key parameters of Artificial Intelligence (AI) -enabled co-creation integrated into evidence-based policymaking. We critically analyzed prior research to ensure a participatory, data-driven, and iterative policymaking process. We identified essential parameters shaping AI-enabled co-creation processes in public sector organizations (PSOs), including legal conformance, sustainability, and ethics. The parameters were validated and refined through a workshop with experts from academia and technology organizations, contributing to the development of a conceptual model structured around four interconnected co-creation phases: 1) co-commissioning; 2) co-designing; 3) co-delivering; and 4) co-assessing. Our study contributes to both theory and practice. Concerning theory, it positions AI-enabled co-creation as a core institutionalized process within evidence-based policymaking rather than a standalone participatory practice. It also introduces a key conceptual distinction between digital co-creation, where digital tools facilitate participatory processes, and digital public service co-creation, where digital solutions are the co-creation outcomes. Concerning practice, the study provides a structured framework for integrating co-creation into policymaking, aligning AI-enabled mechanisms with four identified policy co-creation phases. The framework offers policymakers and public administrators actionable guidance on designing adaptive, stakeholder-driven, AI-supported policy solutions