An AI adoption model for SMEs: a conceptual framework

Bettoni, Andrea; Matteri, Davide; Montini, Elias; Gładysz, Bartłomiej; Carpanzano, Emanuele

doi:10.1016/j.ifacol.2021.08.082

Cited by 37 publications

(22 citation statements)

References 9 publications

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“…The transformation started by the industrial revolution has forced all companies-regardless of their size, industry, or location-to embark on the digitalization process. However, B Constantin Zopounidis kostas@dpem.tuc.gr; czopounidis@audencia.com Extended author information available on the last page of the article small and medium-sized enterprises (SMEs) have been especially slow to integrate digital technologies, with only one in five SMEs in the European Union currently running highly digitalized operations (Bettoni et al, 2021). As a result, these companies are under increasing pressure to implement complex growth plans that strengthen their competitiveness and help them stay abreast with constantly evolving technological and social innovations (De Marco et al, 2020;Falahat et al, 2020;Jung et al, 2018).…”

Section: Introductionmentioning

confidence: 99%

“…For example, SMEs need to adapt to advances based on artificial intelligence (AI), which, according to Magistretti et al (2019), is expected to become a complementary tool for SME decision-making processes. These firms' ability to adopt new technologies is, nevertheless, often restricted by SMEs' lack of resources and limited awareness of technological and social changes (Bettoni et al, 2021;Strotmann, 2007).…”

Section: Introductionmentioning

confidence: 99%

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Artificial intelligence and change management in small and medium-sized enterprises: an analysis of dynamics within adaptation initiatives

et al. 2022

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Given the increasingly significant role of small and medium-sized enterprises (SMEs) in the global economy and the ever more competitive markets in which these companies operate, SMEs' ability to adopt artificial intelligence (AI) technologies is of utmost importance. Due to constantly evolving social, environmental, and technological scenarios, the managers of these firms must increasingly focus on incorporating new tools such as AI into SME operations in order to enjoy their benefits. However, the subjectivity and complexity of this adaptation process makes integrated analyses of key factors challenging. The present study sought to develop a multi-criteria decision-support system that applies cognitive mapping and the decision-making trial and evaluation laboratory technique in a neutrosophic context. The main objective is to overcome the limitations of previous studies and models by structuring the decision problem and identifying and understanding which factors should be central to adaptation initiative analyses. A panel of experts in AI were recruited to facilitate the construction of an analysis system that takes into account indeterminacy in decision-making processes. The results were validated by both the panel members and project managers at COTEC Portugal-a leading think-and-action network that seeks to advance technology diffusion and business innovation cooperation. The proposed system's practical implications and benefits are also analyzed.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Artificial intelligence and change management in small and medium-sized enterprises: an analysis of dynamics within adaptation initiatives

et al. 2022

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Section: Literature Reviewmentioning

confidence: 99%

“…More specifically, Bettoni et al propose an AI adoption model to support data-driven transformations and the adoption of AI [9]. This model includes digitisation, data strategy, human resources, organisational structure, and organisational culture as the main elements [9]. This framework is helpful to identify elements that are required to be addressed but does not include prescriptive information of what can be used to enable the organisation.…”

Section: Literature Reviewmentioning

confidence: 99%

“…The study specifically highlighted social aspects that need to be considered when adopting AI in organisations. Even though other AI adoption frameworks exist, the socio-specific considerations or impact of adopting AI are not sufficiently addressed [23,9,34,37]. The expected contribution of the SAIAF artefact is two-fold.…”

Section: Implications For Research and Practicementioning

confidence: 99%

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Towards a socio-specific artificial intelligence adoption framework

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Organisations need to be able to adopt AI successfully, but also responsibly. This requirement is not trivial, as AI can deliver real value to adopters. However, can also result in serious impacts on humans. AI’s technical capabilities make AI powerful, still the implementation of AI in organisations is not limited to the technical elements and requires a more holistic approach. An AI implementation within an organisation is a socio-technical system, with the interplay between social and technical components. When AI makes decisions that impact people, the socio considerations in AI adoption frame- works are paramount. Although technical adoption challenges are well researched and can overlap with aspects associated with traditional IT implementations, artificial intelli- gence adoption often faces additional social implication. This study focuses on these social challenges, which is a problem frequently experienced by many organisations. The study investigates how an organisation can increase adoption of AI as part of its quest to become more data-driven. This study was conducted at an automotive manufacturer’s analytics competence centre, located in South Africa. This paper describes the first iteration of a larger research effort that follows the design science research methodology. A socio-specific artificial intelligence adoption framework was created and can be used by organisations to help them succeed with their AI adoption initiatives in a responsible manner.

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