Hybrid decision architectures: exploring how facilitated AI access reconfigures startups' organizational structures and decision-making

Abstract

Purpose This study examines how facilitated access to Artificial Intelligence (AI), particularly following the release of ChatGPT, is transforming how startups organize and decide. It explores how AI becomes embedded in the very architecture of startups rather than merely serving as a task-automation tool. Design/methodology/approach The study draws on semi-structured interviews with entrepreneurs who founded startups both before and after ChatGPT's release and integrated AI into their post-release ventures. The analysis identifies how facilitated AI access reconfigures roles, structures and decision routines. Findings The results reveal the emergence of hybrid decision architectures – startup-specific configurations in which algorithmic reasoning and human judgment recursively interact to shape decisions, roles and organizational routines. These architectures are both process and outcome: they evolve through ongoing human-AI interplay while simultaneously stabilizing into structural and cultural patterns that embed such collaboration. Practical implications The findings offer guidance for entrepreneurs seeking to build adaptive, AI-integrated organizations – redefining hiring, decision processes and learning practices to leverage AI's analytical potential while maintaining human sensemaking and discretion. Originality/value The study introduces hybrid decision architectures as a dual-level construct explaining how AI triggers systematic organizational change in startups. It advances process-theoretical understandings of human–AI collaboration by showing how cultural, structural and decision-making elements co-evolve through recursive feedback loops.

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