Unleashing potential of Artificial Intelligence and Digital Servitization: Investigating the role of Dynamic Capabilities on Finnish Small and Medium Sized Enterprises.

Abstract

A unique and interesting fact about small and medium-sized enterprises (SMEs) that adopt artificial intelligence (AI) and become fully servitized is that they can significantly shift from product-based revenue models to outcome-based ones. In this transition, rather than simply selling products or one-off services, SMEs using AI can offer continuous, predictive services that directly enhance customer outcomes. When there is this potential to move from transactional to relational and outcome-based services, SMEs can build long-term customer relationships as well as generate recurring revenues and leverage AI-driven insights to continuously improve their offerings. In Finland, where sustainability and innovation are key priorities, SMEs that adopt AI can integrate environmental monitoring and optimization services into their offerings. If, for instance, a company develops wearable devices that monitor patients’ vital signs, such as heart rate, oxygen levels, and glucose levels, and then simply transmits this data to healthcare providers in real-time. However, instead of simply selling the wearable devices, this company uses AI-driven analytics to offer “Health Efficiency as a Service.” This thesis investigates the potential of AI on the digital servitization journey of Finnish SMEs within the healthcare industry. The findings reveal a disparity among three Finnish SMEs, which shows a spectrum of AI adoption. Some SMEs depend heavily on AI for their product offerings, while others are only starting to explore the capabilities of this new technology. Notably, none of the SMEs included AI in their administrative tasks. Drawing on dynamic capability theory (DCT), this thesis delineates three factors: sensing, seizing, and reconfiguring. Under these factors, specific steps are outlined for Finnish SMEs to achieve digital servitization. Additionally, the concept of AI maturity level is introduced. The interviewed companies were ranked according to Microsoft's AI maturity model. Level 4 is identified as the optimal level for SMEs to leverage AI effectively for digital servitization. Given the scarcity of research on the impact of AI on digital servitization, this study employs a qualitative, multiple case study, mono-method approach, utilizing cross-sectional data from structured interviews. The observations indicate a general hesitation among Finnish SMEs regarding the full adoption of AI in their journey towards digital servitization.