Abstract

The digital and AI divide research conceptualizes three levels of inequality including access, capability, and outcomes, with prior research examining who can access AI tools and who has the skills to use them effectively (Carter et al., 2020). For small to medium enterprises (SMEs), who have historically been disadvantaged by both the digital and AI divide due to limited resources and technical capacity, these barriers have been significant (Sheldrick et al., 2023). Generative AI tools, however, are changing this landscape. Unlike earlier enterprise AI systems that required substantial investment and technical expertise, generative AI tools are increasingly inexpensive, widely available, and designed for non-technical users. This shift opens new possibilities for SMEs across a range of business activities. Marketing offers a prime example. SMEs can now produce content, engage customers, manage digital advertising, and conduct market research with tools that previously would have been out of reach. Yet despite closing of the access and capability AI divide, we lack understanding of how SMEs use these tools in practice and what shapes their ability to sustain value from them over time. This TREO talk presents early findings from a qualitative study of how SMEs use generative AI across business activities, with a particular focus on marketing tasks such as content creation, customer engagement, and digital advertising. Initial findings suggest that SMEs are actively experimenting with these tools and finding value in their ability to extend or provide access to labor and expertise for marketing tasks. However, as firms move beyond initial AI adoption, questions emerge about whether these early gains can be sustained. Some SMEs may hit a wall by continuing to use AI tools without a clear sense of whether their efforts are working or how to improve them over time. We use these early findings to open a discussion about what drives continued innovation and sustained value creation beyond initial adoption, and whether closing the AI access and capability divide reveals a deeper challenge for SMEs around organizational learning and long-term AI value.

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