Risk management considerations for artificial intelligence business applications

Abstract

The number of projects and the amount of investment into artificial intelligence (AI) based business process automation is increasing that is also due to research advancements in corresponding fields. To utilise its true power, business organisations shall identify and treat risks arising from AI, that must be reduced to an acceptable level to maintain fraud-free business operation in alignment with external legislative requirements. If risks are not assessed, then AI might cause greater headache resulting in expensive implementation without business benefit. The objective of the paper is to analyse the nature of risk elements that AI can bring to the life of corporations and the countermeasures that shall be implemented by analysing general IT risk assessment processes and the stages of intelligent system development. The article also examines frameworks for AI risk management approaching risks associated with intelligent decision making by providing guidelines of required business processes to be implemented.

Artificial Intelligence and Project Management: Empirical Overview, State of the Art, and Guidelines for Future Research

“…Studies on AI in project management have developed throughout the years-from specific applications of expert systems for decision-making (Currie & Drabble, 1992;Diekmann, 1992) to applications based on numerical data for processes (Cubric, 2020) such as effort estimation (Elish et al, 2013;Hosni et al, 2018;Song & Minku, 2023), cost management (Afzal et al, 2019;Cheng & Roy, 2011;Elmousalami, 2020), and scheduling (Bahroun et al, 2023;Faghihi et al, 2014;Wang et al, 2012;Wauters & Vanhoucke, 2016). An additional avenue of research was conducted on using AI applications for risk management (Barta & Görcsi, 2021;Costantino et al, 2015;Jin & Zhang, 2011), quality management (Nemati et al, 2002;Parra et al, 2015), and project selection (Costantino et al, 2015;Liu et al, 2019;Rad & Rowzan, 2018). Several scholars have examined how AI can support less quantitativebased processes such as procurement, supplier selection and contract negotiation (Attar et al, 2013;Chaphalkar et al, 2015;Kog & Yaman, 2016;Lewis et al, 2011), and knowledge management (Colomo-Palacios et al, 2014;Lin et al, 2015;Sacks et al, 2020).…”

Relationship between Occupational Pension, Corporate Social Responsibility (CSR), and Organizational Resilience: A Study on Listed Chinese Companies

“…The digital economy has generated new business models in areas such as the internet (Russell 2013), big data (Watts and Feltus 2017), cloud computing (Wu et al 2019), artificial intelligence (Barta and Görcsi 2021), and the Internet of Things (IoT) (Gao et al 2021). These technologies have become increasingly integrated into various sectors of the economy and society, playing an important role in creating employment, stimulating consumption, and driving investment (Pandey and Pal 2020).…”

The impact of artificial intelligence on human resource management systems - Applications and risks

“…The application of HR tech technology and the development of artificial intelligence systems contain internal and external issues regarding the organization's human resource management process [21]. The following issues regarding the risks are summarised through observations from the University of Melbourne's Open Course in Management.…”