Leveraging AI to Enhance Innovation Efficiency in the MedTech Sector AI Applications and Strategies for Enhancing Innovation Efficiency: A Case Study in the MedTech Sector

Abstract

The MedTech industry is experiencing rapid technological change and facing evolving healthcare needs, which puts pressure on actors to innovate efficiently and stay competitive. At the same time, Artificial Intelligence (AI) is emerging as a transformative tool with the potential to enhance efficiency. However, despite its potential, the adoption of AI within the MedTech sector remains limited. The aim of the thesis is therefore to examine how MedTech companies can leverage AI to enhance innovation efficiency. The main research question is explored through the lens of an innovation process framework, consisting of the three phases: Idea, R&D, and Commercialization. Within this framework, four key areas have been identified with the potential to improve overall efficiency by the integration of AI, namely: Knowledge Management, Patent Analytics, Market and Customer Analysis, and Resource Allocation. In addition, the study addresses important aspects of implementing AI within organizations to optimize the possible outcomes. A single case study has been conducted analyzing a MedTech company, which was selected as it constitutes a suitable case to explore the research question. The methodology consists of a literature review followed by an interview study. The literature presents the current state of AI applications in the four focus areas defined and reviews opportunities and challenges regarding implementation. The interview study included participants both working at the company studied, to depict its current practices and needs, and individuals at other organizations who are at the forefront of AI adoption, to gain best-practice perspectives and expert insights. The results show that AI technologies have great potential in enhancing innovation efficiency in the MedTech industry. AI helps to improve the flow of information inside the organization, strengthen intellectual property strategies, enhance market and customer insight, and optimize resource allocation between projects. However, to achieve those benefits, a highly coordinated strategy with top-down support is necessary. Thus, the thesis concludes that a structured and human-centered approach to AI adoption is essential for companies in the complex and highly regulated MedTech landscape to remain competitive and achieve long-term innovation success.