AI adoption in E-commerce enterprises: Insights into current practices and future directions from an interview study

Area of Science:

• Digital Commerce
• Artificial Intelligence
• Business Management

Background:

• E-commerce businesses are increasingly integrating artificial intelligence (AI) across various processes.
• AI adoption presents diverse application trends in marketing, operations, and customer services.
• Understanding AI implementation is crucial for digital transformation in e-commerce.

Purpose of the Study:

• To explore the practical implementation paths of AI technology in e-commerce enterprises.
• To analyze the effects and future plans of AI adoption based on the TOE and TAM frameworks.
• To provide theoretical perspectives and empirical evidence on AI adoption logic in the AI-driven e-commerce industry.

Main Methods:

• Utilized a multi-case qualitative interview approach.
• Conducted semi-structured interviews with diverse e-commerce enterprises in Anhui Province, China.
• Applied the Technology-Organization-Environment (TOE) model and Technology Acceptance Model (TAM) framework.

Main Results:

• AI applications span the entire e-commerce chain, but small enterprises face limitations in technical depth and customization.
• A human-machine collaboration model ('AI pre-processing + human fine-tuning') is prevalent.
• Organizational capabilities and employee AI literacy are key adoption factors, with limited external policy guidance.
• Enterprises exhibit stratified AI integration patterns: 'platform-bound,' 'tool-augmented,' and 'self-developed.'

Conclusions:

• AI adoption in e-commerce is multifaceted, influenced by internal organizational factors and external environments.
• Human-machine collaboration is essential for effective AI utilization in current e-commerce operations.
• Future AI integration strategies should consider organizational context and employee readiness for successful digital transformation.