A Framework for the Implementation of Artificial Intelligence in Business Enterprises: A Readiness Model

Nortje, Morne Andries; Grobbelaar, Sara S.

doi:10.1109/ice/itmc49519.2020.9198436

Cited by 17 publications

(7 citation statements)

References 24 publications

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“…Unfortunately, research on AI adoption is in its infancy (Jöhnk et al, 2020), and there is a lack of a common perspective in the literature (Hamm and Klesel, 2021). However, recent literature presents models and frameworks that underscore various dimensions like culture to determine the AI readiness of organisations (Jöhnk et al, 2020;Nortje and Grobbelaar, 2020). These dimensions resonate with Ericsson's report (2020), concluding that adopting AI in organisations relies heavily on cultural dimensions and people.…”

Section: Introductionmentioning

confidence: 93%

“…New information technology like the Internet of Things (IoT) and Artificial Intelligence (AI) present promising (and concerning) capabilities that can transform and bring innovation into the future of work (Wang and Siau, 2019), specifically in organisations of the educational and healthcare sector (World Economic Forum, 2020). AI has developed dramatically over the last decades, and such developments "will have a transformational impact" on organisations (Nortje and Grobbelaar, 2020); however, most of these opportunities are yet to be exploited due to the level of readiness in the organisations (Nortje and Grobbelaar, 2020). This rapid development also leads people to new concerns as technology develops faster than people can understand and be ready for it.…”

Section: Introductionmentioning

confidence: 99%

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Co-Designing Technological Explorations in Developing Futures Literacy Through Speculative Design and an Artistic Intervention

2023

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Futures Literacy is the capability to imagine and understand potential futures to prepare ourselves to act and innovate in the present. This pilot study aims to understand how artistic methodologies and speculative design can support the collaborative exploration of futures in the context of work and contribute to developing peoples’ capability of futures literacy. Our premise is that technologies such as Artificial Intelligence and the Internet of things can augment people and support their needs at work. To illustrate this process, we have presented a collaborative method that integrates an artistic intervention with speculative design activities. We tested the method in a full-day workshop with seventeen (17) participants from a Swedish academy responsible for enabling learning and competence development at work in the healthcare sector. The results indicate that the artistic intervention, combined with the speculative design activities, can challenge current participants’ perspectives and offer them new ways of seeing futures with technologies. These new ways of seeing reveal underlying premises crucial in developing the capability of futures literacy.

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Section: Introductionmentioning

confidence: 93%

Section: Introductionmentioning

confidence: 99%

Co-Designing Technological Explorations in Developing Futures Literacy Through Speculative Design and an Artistic Intervention

2023

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“…In industry 4.0, AI is recognized as the key driver behind the technological advancements. AI is transforming various industries, which is causing the existing industry to grow very swiftly (Cioffi et al 2020;Mohammed et al 2021;Nortje and Grobbelaar 2020). Many companies invest in AI because they perceive it as an opportunity in the current industrial competition.…”

Section: Artificial Intelligencementioning

confidence: 99%

Analyst’s Perception on the Use of AI-based Tools in the Software Development Life Cycle

Giffari,

Ridho,

Indra Sensuse

et al. 2024

J. Sistem Inf. (J. Inf. Sys.)

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Artificial Intelligence (AI) integration has been the goal in many industries, including in the software development industry. One example of this integration comes in the form of integrating AI in the Software Development Lifecycle (SDLC). To date, the difficulties of incorporating AI-based tools into particular phases of SDLC have not received much attention in research. Using qualitative approach, this study aims to discover the perception on the use of AI-based tools and challenges in integrating them in the analysis phase of SDLC. The study finds out that analyst have positive perception about integrating this technology in their field of work but there are some challenges while integrating this technology such as data security and reliability concern, dependency, and adapting to this technology. This study also discovers some key factors of why some analysts adopt or refuse this technology namely time, urgency, budget, and insecurities of the users.

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“…22 For organizations ready for AI implementation, the AI readiness is defined by variables organization culture and employee, management of technology artefacts in the organization, the leadership support for AI projects and project governance, organization strategy, support of AI-specific infrastructure, information management, and knowledge dissemination and security of AI implementations. 23 For organizations planning to leverage AI for competitive advantage, support from leadership, clarity on using AI technology as differentiator, availability of technical resources, culture in the organization, and availability of use cases where AI can be applied were found to be important. 24 Machine learning, a sub-field of AI, was studied from adoption perspective in organization in USA and Germany and organization size and structure were found to be an adoption factors other than leadership, availability of resources, compatibility of machine learning technology with existing technology, advantage over existing processes and complexity.…”

Section: Research Questionmentioning

confidence: 99%

Factors Influencing the AI Adoption in Organizations

Kurup

Gupta

2022

Metamorphosis: A Journal of Management Research

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Adoption of Artificial Intelligence (AI) in organizations is getting popular due to the impact it is creating in business and society. While AI as a technology has made progress due to advances in various research areas, there is limited study on the adoption of AI in organizations. This article intends to develop a model for identifying the factors influencing AI adoption in organizations. We developed the model using Diffusion of Innovation and Technology-Organization-Environment theories, adopted from the field of Information Systems. In this article, we provide an analysis of application of theories toward AI adoption and provide a model at organization level. We collected data by designing a survey on 7-point Likert scale to validate our proposed model using regression-based approach and structural equation modelling. The results suggest that the change capability of an organization and leadership positively impact the AI adoption in organizations. Further, our study reflects that AI readiness by the organizations and AI adoption by trading partners of an organization also impact AI adoption positively.

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A Framework for the Implementation of Artificial Intelligence in Business Enterprises: A Readiness Model

Cited by 17 publications

References 24 publications

Co-Designing Technological Explorations in Developing Futures Literacy Through Speculative Design and an Artistic Intervention

Co-Designing Technological Explorations in Developing Futures Literacy Through Speculative Design and an Artistic Intervention

Analyst’s Perception on the Use of AI-based Tools in the Software Development Life Cycle

Factors Influencing the AI Adoption in Organizations

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