Reshaping business models : the strategic challenges of digital transformation and AI in the global market

Abstract

This thesis explores the transformative impact of digitalization and AI-driven automation on key performance indicators (KPIs) within multinational corporations, focusing on the practical challenges and measurable outcomes of digital transformation initiatives. The central research question investigates how digitalization and AI influence operational efficiency, cost reduction, and business model evolution across distinct sectors. Using a qualitative case study methodology, two contrasting examples were analyzed: a largescale logistics automation project at Henkel, and a lean digital tracking initiative at Diamond Aircraft. Data was collected through expert interviews, internal documentation, and KPI tracking before and after implementation. Findings reveal that while financial investment and technological readiness are crucial enablers, success is equally dependent on employee engagement, leadership, and cross-functional collaboration. At Henkel, a €50 million investment in warehouse automation resulted in increased storage capacity, reduced manual handling, and a 40% decrease in rework, with an anticipated ROI within four years. In contrast, Diamond Aircraft achieved rapid ROI through a €15,000 digital waste-tracking system that led to a 37% reduction in scrap and rework costs, supported by a Six Sigma framework and people-centric change management. Both cases demonstrated that transparency, accountability, and cultural alignment are critical to overcoming resistance and sustaining improvements. This study concludes that digital transformation, when paired with strategic planning and ethical change management, not only enhances competitiveness but also fosters a culture of continuous improvement. Future research may expand on these findings by exploring digital maturity frameworks and scalable implementation models across industries.