Journal of Marketing Analytics· 2026Q1
AI-enabled marketing analytics for SMEs: multimethod evidence on application potential and adoption conditions
- 0citations
- Q1SCImago
- 2026year
Short summary
A hybrid study of 49 papers and 100+ SMEs reveals organizational, technological, and user conditions, plus AI application potential, shape AI adoption in SMEs.
AI-generated from the title and abstract; the full text is not read.
Key points
- AI adoption in SMEs is shaped by organizational, technological, and user-related conditions.
- The study integrates a systematic literature review (49 studies) with an empirical survey (100+ SMEs).
- A conceptual framework is proposed, distinguishing between opportunistic, operational, strategic readiness, and strategic AI use.
- The framework translates AI application potential and adoption conditions into practical strategies for SMEs.
AI-generated from the title and abstract; the full text is not read.
Abstract
Abstract Artificial Intelligence (AI) is transforming marketing analytics by enabling advanced data processing, predictions, and decision support. However, small and medium-sized enterprises (SMEs) often face substantial barriers to AI adoption due to limited organizational, technological, and human resources. To bridge theoretical and practical perspectives, this study employs a hybrid approach combining a systematic literature review of 49 studies with an empirical survey of more than 100 SMEs. The findings identify organizational, technological, and user-related conditions, as well as AI application potential, that shape AI adoption in SMEs. Based on these insights, a conceptual framework is proposed that differentiates between opportunistic, operational, strategic readiness, and strategic AI use. The framework translates SMEs’ AI application potential and adoption conditions into practice, thus structuring AI-enabled marketing analytics, which provides SMEs with new opportunities for data-driven operations despite resource constraints.
The authors' abstract, as published at the source. Journal of Marketing Analytics, 2026 · DOI ↗
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