Human-AI Collaboration in Small Enterprises: Balancing Automation and Human Input

Azzahra, Adelia
Ridzki, Mohamad Maulana

Return : Study of Management, Economic and Bussines
Vol. 4 No. 12 (2025): Return: Study of Management, Economic and Business

Industry 5.0 emphasizes human-centric collaboration between artificial intelligence and human workers, yet small enterprises face unique challenges in AI adoption due to limited resources and technical expertise. This research examines the dynamics of human-AI collaboration in small enterprises, identifying implementation challenges, success strategies, and measurable impacts on productivity and employee satisfaction. A qualitative case study approach was employed, involving semi-structured interviews with 10 AI integration specialists and small enterprise owners (10-50 employees), analysis of 7 organizational case studies, and document reviews of industry reports (2020-2024). Data were analyzed using NVivo 12 software following Braun and Clarke’s thematic analysis framework. Analysis revealed five major themes: skill gaps affecting 68% of interviewed enterprises, employee resistance driven by job security concerns (54%), technical infrastructure barriers (72%), productivity improvements ranging from 15-35% with average 34.3%, and critical importance of human oversight in decision-making (92% consensus). Small enterprises implementing AI with gradual integration strategies reported 28% average productivity increase, 17.8% revenue growth, and 22% improvement in employee satisfaction within 12 months. The 3-year cumulative ROI reached 184% despite initial implementation costs averaging 3-5x software licensing fees. Effective human-AI collaboration in small enterprises requires balanced integration strategies emphasizing employee training (15-20% of budget), transparent policies, gradual implementation (6-12 months), and maintaining human judgment in critical decisions (80-95% of strategic tasks). AI serves most effectively as a complementary tool handling 70-85% of routine, data-intensive tasks while humans retain control over strategic, creative, and interpersonal functions. The research validates Industry 5.0’s human-centric paradigm and provides quantified benchmarks for small enterprise AI adoption.