Epäsuoran hankinnan ostokanavastrategioiden kehittäminen tekoälyä hyödyntävässä Source-to-Pay-transformaatiossa

This thesis examines how effective buying channel strategies for indirect procurement can be designed and implemented to improve governance, efficiency, and scalability, while enabling future AI-supported procurement capabilities. The study was conducted in the context of the case company’s ongoing Source-to-Pay transformation, which aims to improve digitalization, harmonize procurement processes, enhance compliance and transparency, and establish a foundation for more data-driven and intelligent procurement practices. The literature review explores indirect procurement, buying channel strategies, procurement digitalization, and emerging AI-enabled procurement models. The findings from the literature review are analyzed together with empirical qualitative data collected through semi-structured interviews. The empirical data consists of interviews with internal procurement stakeholders, external subject matter experts, and benchmark companies, providing insights into both current practices and future aspirations related to buying channel design and digitalization. The findings indicate that the core challenge in indirect procurement is not the lack of buying channels or policies, but their misalignment with actual purchasing contexts. Subcategories within the same procurement category differ significantly in terms of repeatability, risk, urgency, and specification variability, leading to process deviations and inefficiencies when uniform approaches are applied. To address this, the thesis proposes an archetype-based buying channel framework that aligns dominant channels and controlled exceptions with recurring purchasing situations. The study further highlights that buying channel strategies form a foundational prerequisite for procurement digitalization. While AI-enabled procurement offers significant potential, advanced solutions such as agentic AI require stable processes, data availability, and integrated systems to deliver value. Consequently, AI was found to be best positioned as a guiding and executing layer built on top of well-designed buying channel strategies and a modern S2P platform.