Small and medium-sized enterprises (SMEs) that are not inherently digital-centric face significant challenges in digital transformation. Despite some progress in areas such as marketing and communication, these efforts often result in superficial digitalization, leaving core business activities underdeveloped. SMEs tend to focus on visible aspects, such as websites, social media, or regulatory compliance, while neglecting the structuring of internal processes and data management. This patchwork of specialized tools creates fragmented information systems, limiting the potential for meaningful integration of Artificial Intelligence (AI). Moreover, core business processes remain under-documented and reliant on tacit knowledge embedded in employees’ routines. The lack of formalization and unified data infrastructures hinders the ability to adopt AI solutions beyond secondary functions, such as content creation or social media management. While marketing and communication are easier to digitalize due to their tangible nature, true transformation demands a deeper focus on internal systems and data structuring. This study highlights the gap between superficial digital efforts and the prerequisites for leveraging AI within SMEs’ core activities. It emphasizes the need for a comprehensive approach to digital maturity, including the formalization of know-how, integration of coherent information systems, and centralized data management. Addressing these challenges is critical for SMEs to move beyond façade-level digitalization and unlock the transformative potential of AI.
