Digital transformation or digital divide? Smes' use of AI during global crisis

Syed Sardar Muhammad, Bidit Lal Dey, Muhammad Mustafa Kamal, Lalnunpuia Samuel and Ebtesam Abdullah Alzeiby

Technological Forecasting and Social Change, 2025, vol. 217, issue C

Abstract: There is a notable deficiency in empirical research examining how digital transformation, particularly through the adoption of technologies such as Artificial Intelligence (AI), can empower SMEs to navigate the challenges posed by global crises. While new technologies are frequently regarded as solutions, they can coexist with existing systems and potentially exacerbate the digital divide. This paper aims to investigate the factors that either facilitate or hinder digital transformation among SMEs and their impact on either bridging or widening the digital divide. To explore this issue, we employed a maximum variation sampling method and conducted 15 in-depth interviews with SMEs in the restaurant sector – encompassing small, medium, and large establishments – in London. Our findings indicate that technological factors (such as digital inertia), organisational aspects (including perceptions and collaboration), and external environmental influences (like lockdown measures) are critical in determining the extent of digital transformation or the continuation of the digital divide among SMEs during the pandemic. This paper contributes to understanding the interrelationships among innovative technologies, including AI, SMEs, and their external environments in the context of rapid digital transformation. It underscores the adverse effects of technology adoption on the equitable distribution of innovative practices and provides insights into promoting inclusive digital transformation to mitigate the digital divide among SMEs.

Keywords: Digital transformation; Digital divide; SMEs; Artificial intelligence; COVID-19 (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:eee:tefoso:v:217:y:2025:i:c:s004016252500215x

DOI: 10.1016/j.techfore.2025.124184

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