Advancing Human‐AI Collaboration in Small and Medium‐Sized Enterprises: A Systems Engineering Approach

Abstract

The integration of Artificial Intelligence (AI) into organizational processes presents unique challenges for Small and Medium‐sized Enterprises (SMEs), particularly in fostering effective human‐AI collaboration. Unlike large corporations with extensive resources for AI adoption, SMEs require adaptable frameworks tailored to their specific constraints and operational needs. This paper introduces the novel Human‐AI Collaboration Maturity Model (HAIC‐MM), which is a systems engineering framework designed to assess, guide, and enhance AI integration within SMEs. Developed through the synthesis of AI maturity models, digital transformation frameworks, and human‐machine teaming research, HAIC‐MM identifies seven dimensions and 32 capabilities across five maturity levels that are essential for successful AI adoption in SME contexts. Empirical validation through survey analysis (N = 100) confirmed the model's robustness. Subsequent focus group analyses (N = 10, repeated across five sessions) further validated HAIC‐MM's practical utility and alignment with the operational realities of SMEs, emphasizing its relevance to everyday challenges faced by these organizations. Pilot testing with industry practitioners (N = 3) confirmed the usability and usefulness of the final HAIC‐MM tool. HAIC‐MM provides SME leaders with a structured, human‐centered, and systematic approach to evaluate and cultivate human‐AI collaboration, addressing key areas such as resource optimization, workforce empowerment, ethical AI oversight, and adaptive organizational culture. This research contributes to AI‐enabled systems engineering by offering a practical framework for harmonizing human and AI capabilities within resource‐constrained environments, ultimately supporting SMEs in achieving sustainable and ethically grounded AI integration across the organization.