1.
Nico Kling
– Faculty Of Economics And Management, Leipzig University, Leipzig, Germany.
2.
Emelie Schwill
– Faculty Of Economics And Management, Leipzig University, Leipzig, Germany.
3.
Sajal Kabiraj
– Faculty Of Economics And Management, Leipzig University, Leipzig, Germany.
Abstract
This study investigates Artificial Intelligence (AI) adoption patterns, employee perceptions, and the influence of organisational size within Chinese enterprises. Methodologically, it employs 20 unstructured qualitative interviews with employees in Hangzhou, China, which are analysed using qualitative content analysis. Key findings indicate overwhelmingly positive sentiments towards AI across all organisational sizes. Adoption strategies vary: large enterprises implement complex optimization systems, medium-sized firms focus on decision support, and small enterprises prioritise customer-facing applications. The study’s original contribution is a novel flywheel model that explains China’s high AI adoption rates despite significant implementation barriers. This model details how four organisational mechanisms (positive perception, barrier tolerance, training/competency, future planning), accelerated by China’s unique cultural context and supportive policy environment, create self-reinforcing momentum against size-dependent friction. Managerial implications suggest large firms should leverage scale and policy alignment, investing in comprehensive training and long-term planning, while SMEs should strategically adapt to resource constraints and seek niche policy support, navigating the interplay of cultural optimism and practical challenges.
Keywords Artificial Intelligence, China, Innovation Management, Organisational Size, Sentiments, Technology Adoption
