Collaborative Supply Chain and Sales Networks for Improved Customer Satisfaction and Market Responsiveness with AI Integration

Abstract

Background
In today’s volatile and competitive global market, industrial companies in Europe are under pressure to increase agility, customer responsiveness, and operational resilience. Traditional silos between supply chain and sales functions often result in misalignment, inefficiencies, and missed opportunities. This study investigates how artificial intelligence (AI) can support and enhance cross-functional collaboration between these two departments to improve customer satisfaction and business
performance.
Methods
The research adopts a mixed-methods design to ensure both depth and breadth of insight. Qualitative data were collected through 15 semi-structured interviews with supply chain and sales executives across various industrial sectors in Europe. A
complementary quantitative survey, distributed to 187 professionals, provided additional validation and scalability. Data were analyzed through thematic coding, descriptive statistics, regression, and chi-square testing using the software Jamovi.
Results
The study reveals that AI-supported collaboration significantly enhances forecasting accuracy, planning integration, and customer responsiveness. Firms with shared KPIs, cross-functional teams, and AI tools embedded in decision-making processes reported higher customer satisfaction and internal alignment. However, challenges persist: organizational silos, limited digital maturity, and resistance to change remain major barriers.
Discussion and Conclusion
The findings suggest that technological tools alone are insufficient without cultural readiness, strong leadership, and strategic alignment. A conceptual framework and practical roadmap are proposed to guide industrial firms in their AI-enabled
transformation. The research contributes to both academic understanding and practical implementation by addressing a critical gap in cross-functional digital integration within industrial supply chains.