The strategic use of artificial intelligence in the digital era: Systematic literature review and future research directions

Borges, Aline de Fátima Soares; Laurindo, Fernando José Barbin; Spínola, Mauro de Mesquita; Gonçalves, Rodrigo Franco; Mattos, Cláudia Aparecida de

doi:10.1016/j.ijinfomgt.2020.102225

Cited by 400 publications

(219 citation statements)

References 100 publications

Supporting

Mentioning

203

Contrasting

Unclassified

Order By: Relevance

“…Table 1 displays an outline of the current literature review papers in this area. [44] implemented a literature review to analyze the correlation between AI and strategy to make business value. In this view, this article planned to bridge this gap by: conducting a significant literature review identified with the combination of AI with business strategy; combining the current approaches with models, featuring the expected advantages, difficulties and opportunities; introducing a conversation for further research avenues.…”

Section: Previous Literature Reviewsmentioning

confidence: 99%

“…Notwithstanding the technological advancement in the most recent decade, researchers and practitioners have taken about that technology is not the principle difficulty embracing AI, yet cultural impediments, process and individuals [3,36,44,69]. To address them, strategy is important that appropriately incorporates knowledge, technology features, individuals, management change and aspirations to change the endeavor and the organization.…”

Section: Aligning Ai Tools and It With Business Strategymentioning

confidence: 99%

See 1 more Smart Citation

Artificial Intelligence and Business Strategy towards Digital Transformation: A Research Agenda

2021

View full text Add to dashboard Cite

In the past decade, current literature and businesses have drawn attention to Artificial Intelligence (AI) tools and in particular to the advances in machine learning techniques. Nevertheless, while the AI technology offers great potential to solve difficulties, challenges remain implicated in practical implementation and lack of expertise in the strategic usage of AI to create business value. This paper aims to implement a systematic literature review analyzing convergence of the AI and corporate strategy and develop a theoretical model incorporating issues based on the existing research in this field. Eighty-one peer-reviewed articles were discussed on the basis of research methodology from Webster and Watson (2002). In addition to gaps in future research, a theoretical model is developed, discussing the four sources of value creation: AI and Machine Learning in organizations; alignment of AI tools and Information Technology (IT) with organizational strategy; AI, knowledge management and decision-making process; and AI, service innovation and value. These outcomes lead to both theoretical and managerial viewpoints, with extensive possibilities to generate new methods and types of management practices.

show abstract

Section: Previous Literature Reviewsmentioning

confidence: 99%

Section: Aligning Ai Tools and It With Business Strategymentioning

confidence: 99%

Artificial Intelligence and Business Strategy towards Digital Transformation: A Research Agenda

2021

View full text Add to dashboard Cite

show abstract

“…However, due to the complexity of the interaction between humans and AI (e.g. [100]- [102]), some aspects of AI application still need a human expert to reflect on the problem domain [103]. Therefore, the study finds that the conjoint use of ANNs and CSFs obtained through the expert judgment method contribute to performance improvements in terms of decision-making in software projects.…”

Section: Advantages Of the Methodsmentioning

confidence: 99%

Systems Thinking in Software Projects-an Artificial Neural Network Approach

et al. 2020

View full text Add to dashboard Cite

The authors discuss why the current conceptual base of project management research and practice continues to attract criticism since it does not adequately address the complexity that leads to software-project failure. To do so, the study explores systems thinking and artificial neural networks to shed light on complexity in software-project behavior using nonlinear functional relationships between critical success factors and project success to utilize their connectedness as an approach in order to create projectoutcome prediction models. The artificial neural networks were used to create two project-outcome prediction models: one for a binary classification task to discriminate failed from successful projects using a multi-input-single-output configuration and one for a multi-task binary classification to discriminate success from failure in multiple project-success dimensions using a multi-input multi-output configuration. The results yielded high-performance values for a binary classification task, performed to predict overall project success, and slightly lower performance values for the multi-task binary classification, which was also performed to predict success in project-success dimensions. It was found that the nonlinear behavior of critical success factors may be used to create prediction models, by embedding equifinality and connectedness constructs that prove to be useful to understand projects as complex, multi-loop, and nonlinear systems. Further research is needed to investigate the causality between critical success factors in order to explore the possible propagation of critical success factors within a project system network and its implications on project success. INDEX TERMS Artificial neural networks, critical success factors, project success, prediction models, systems thinking.

show abstract

“…The best evidence from young technology workers states that from now on, the world can see many businesses using technology that is capable of producing artificial intelligence in producing products to help management support. (Borges et al, 2020). Production in their specialized company uses a technology called artificial technology.…”

Section: Introductionmentioning

confidence: 99%

The Future of Human Resources and Digital Trend Phenomenon in Indonesian Business Practices: Review Literature

Sosrowidigdo¹,

Arifin²,

Pranogyo³

et al. 2021

cibg

View full text Add to dashboard Cite

Efforts to understand the increasing business progress by increasing human resources with digital technology through a systematic review were made. We have carried out with the results, among others, that we have systematically reviewed publications confirming that efforts to increase the capacity of human business resources and public service organizations through optimization of digitalization are the right steps and very reasonable. This is because the effectiveness and superiority of technology to this day are unmatched. We seek to find this understanding with a descriptive qualitative approach review design. We searched secondary sources of data through the Google search engine for two data sources; Google Scholar and ERIC publications. For our data to be updated, we choose between the 2010 to 2020 issues except fundamental theory data. Thus these findings become input for business people, academics, and policymaking.

show abstract

The strategic use of artificial intelligence in the digital era: Systematic literature review and future research directions

Cited by 400 publications

References 100 publications

Artificial Intelligence and Business Strategy towards Digital Transformation: A Research Agenda

Artificial Intelligence and Business Strategy towards Digital Transformation: A Research Agenda

Systems Thinking in Software Projects-an Artificial Neural Network Approach

The Future of Human Resources and Digital Trend Phenomenon in Indonesian Business Practices: Review Literature

Contact Info

Product

Resources

About