Open Access

Lukas Weiss, Michael MöhringORCiD, Patrick Kübler, Keshav Dahal

• Artificial intelligence is a key driver of the Fourth Industrial Revolution, with significant business implications and immense potential for small and medium-sized enterprises (SMEs). In Germany, where SMEs account for 99.6% of companies and drive economic output, Artificial Intelligence (AI) adoption is critical for maintaining global competitiveness. However, SMEs face financial, technical, and organizational challenges that hinder AI adoption. This study evaluates the feasibility of AI maturity models for SMEs in Germany’s manufacturing sector. We apply a case-study approach to two manufacturing SMEs through a comparative analysis of a theoretical framework and a model from practitioners. Findings reveal that while the theoretical model offers granular insights, its complexity limits usability, whereas the practitioner framework provides accessible benchmarking but lacks actionable guidance. The study identifies gaps in SME-specific AI Maturity Models (AIMMs) and proposes hybrid frameworks and modular self-assessment tools, ensuring that SMEs remain competitive in a rapidly evolving landscape.