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Leveraging Artificial Intelligence (AI) to Build SMEs’ Resilience Amid the Global Covid-19 Pandemic

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Research and Innovation Forum 2022 (RIIFORUM 2022)

Abstract

As a result of Covid-19 and the ensuing sharp decline in economic activity, business leaders had to quickly adapt to a disruptive marketplace, changing consumer behaviour, and new internal processes. The crisis accelerated adoption of new technologies such as Artificial Intelligence (AI) which could help to improve business processes and evolve new business models, products and services. This exploratory research reports on a preliminary survey with 81 SME owners from various sectors who undertook a seven-week programme to build foundational knowledge on the opportunities of AI for their business and sector. Of those surveyed, 49% turned to AI due to the impact of Covid-19 on their business, sector, and economy. Our results demonstrate the extent of changes small businesses have made as a result of the pandemic, for example, 64% expanded existing services and developed new products and services, with 45% expanding existing product lines. We anticipate the research will directly contribute to existing knowledge by challenging prevailing beliefs about productivity and the role of digital technology adoption. We show that by contributing to the limited literature on micro-enterprise digital technology adoption and demonstrating how a dual approach of implementation of cutting-edge technologies and new management practices can help overcome repercussions of global crises. Our findings suggest that SMEs are currently facing a wide variety of business challenges. However, the integration of a newly developed AI innovation may enable them to overcome these challenges, if adopted with the right level of support.

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Parkinson, M., Carter, J., Nawaz, R. (2023). Leveraging Artificial Intelligence (AI) to Build SMEs’ Resilience Amid the Global Covid-19 Pandemic. In: Visvizi, A., Troisi, O., Grimaldi, M. (eds) Research and Innovation Forum 2022. RIIFORUM 2022. Springer Proceedings in Complexity. Springer, Cham. https://doi.org/10.1007/978-3-031-19560-0_46

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  • DOI: https://doi.org/10.1007/978-3-031-19560-0_46

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