Self-assessment tool for AI implementation in SMEs

Small and medium-sized enterprises (SMEs) face growing challenges, including geopolitical uncertainty, skills shortages, climate-related transformation, and structural change. At the same time, artificial intelligence (AI) offers considerable potential to improve efficiency, competitiveness, and resilience. However, many SMEs lack a systematic basis for identifying and evaluating suitable AI use cases along their value chain. Potential benefits are often accompanied by risks, such as dependence on external technology providers and limited transparency of AI-based decisions. This creates a need for practical decision- support tools that enable a holistic, process-oriented AI transformation. This study aims to design and evaluate an AI-based self-assessment tool that supports SMEs in analyzing organizational challenges, identifying AI potential, and deriving actionable recommendations. Following a design science research approach, the study draws on a problem and needs analysis as well as a review of existing maturity and AI adoption models for SMEs. The developed artifact integrates qualitative and quantitative dimensions such as process maturity, data availability, organizational capabilities, and strategic objectives. It is evaluated iteratively through expert feedback and pilot applications. The expected contribution is a validated, easily accessible tool for innovation management in SMEs that links strategy and implementation and extends existing AI maturity models through a process-oriented, recommendation-based perspective.