The advent of digitalization and artificial intelligence (AI) has revolutionized living on a global scale. According to online statistics, in 2019, 4.13 billion people were online, more than half the world's population.

The internet has grown increasingly significant for both ordinary consumers and large corporations. Even though Internet users are increasing in many regions of the world, internet access and availability can vary significantly by region. As a result, the internet has accelerated globalization, digitalization, and AI.

According to Oxford Learner's Dictionaries, data is digitalized to make it computer-readable. However, this phrase should be viewed more broadly as the application of digital technologies to transform a company model and create new income and value-generating opportunities. 

Objective

Numerous industrialized nations have benefited from introducing twenty-first-century technology, particularly automation, which has profoundly altered manufacturing and industrial production processes. The next phase in the progression of automation is the creation of artificial intelligence (AI), which is intelligence exhibited by machines and systems that can accomplish jobs and collaborate with humans and nature. Intelligent systems that can see, analyze situations, and respond sensitively to real-time cues, such as human gestures and facial expressions, as well as pedestrians crossing a busy street, will reshape transportation, precision agriculture, biodiversity conservation, environmental modelling, public health, construction, and manufacturing, as well as global prosperity-promoting initiatives.

The Manchester Metropolitan University research study investigates the relationships between AI systems and sustainable development (SD) research. Using a literature analysis, a global survey, and case studies, it is determined how AI may help SD research and, among other things, contribute to a more sustainable and equitable world.

Research contribution

This paper investigates the links between AI systems and SD research. The methodologies utilized, including an expert-driven literature review, bibliometric analysis, and a global survey, show how AI has aided SD research.

The study's findings reveal several trends that inform its primary conclusions. During the past 15 years, there has been an average yearly increase of 59% in the amount of literature addressing AI, digitization, and SD, which is the first and most prominent characteristic. It demonstrates how quickly this field is evolving. In addition, the research has determined that, within AI, machine learning is best positioned to contribute to SD research, as proven by the literary analysis of gathered case studies. Over two-thirds of the participants felt that a lack of defined AI strategy and misunderstanding posed a barrier to adopting AI in SD research, followed by data privacy concerns. 

Conclusion

The study also found that digitalization in SD research improves gathering, analyzing, modifying, and finding patterns, allowing for scenario modelling and prediction.

Furthermore, this paper has a few restrictions. The first, related to the expert-driven literature evaluation, is that 2,432 articles concentrated on the connections between digitalization, AI, and SD but needed to account for non-technical aspects fully. In addition, the survey and 172 completed replies, despite representing a substantial number of nations, may need to be revised to enable meaningful implications to be drawn from the study due to the variability of situations included.

Despite these limitations, this study, which includes data from 48 nations, provides a complete analysis of the current relationship between AI systems and SD research, focusing on both directions for future AI research, application, and governance. Furthermore, it contributes substantially to the body of knowledge since it combines rigorous approaches, which lend credibility to the produced results.

In terms of academic ramifications, what is truly innovative about this study is that the analysis also examined the role of AI in achieving the SDGs. There is no question that AI can contribute to a more sustainable and fair world, and there is significant potential for AI to promote the accomplishment of the SDGs.

As a research agenda, it is advised that additional research be conducted on how AI might promote the links between environmental and social sustainability. How AI can assist in monitoring the impacts of SD technology is a second topic of study. In addition, additional research is required to determine how to maximize the potential of AI as a tool for promoting SD-related awareness.

Since digitalization and AI are already a part of our lives, their application in SD may bring the potential for efficiency and innovation enhancements that were previously unimaginable.