首页|Bucharest University of Economic Studies Researchers Report on Findings in Artif icial Intelligence (Implications of Artificial Intelligence on Organizational Ag ility: A PLS-SEM and PLS-POS Approach)
Bucharest University of Economic Studies Researchers Report on Findings in Artif icial Intelligence (Implications of Artificial Intelligence on Organizational Ag ility: A PLS-SEM and PLS-POS Approach)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Current study results on artificial in telligence have been published. According to news originating from Bucharest, Ro mania, by NewsRx editors, the research stated, “Artificial intelligence (AI) has radically changed companies’ vision of business development, based on its wides pread assimilation in key organisational processes. However, in organisational p ractice, the implementation of AI has generated major challenges, such as those related to the high need for investments in technologies, insufficient level of skill development, and resistance to change of personnel.” Our news journalists obtained a quote from the research from Bucharest Universit y of Economic Studies: “At the same time, under the conditions in which markets become increasingly dynamic, an increasingly emphasised requirement for companie s is to maintain increased organisational agility to quickly adapt to the challe nges of the external environment. Therefore, this study aims to analyse the role of AI in capitalising on an organisation’s digital capabilities as a means of a mplifying organisational agility in order to improve internal and external proce sses. The research conclusions were based on the application of a questionnaire to employees from various Romanian sectors of activity and for data analysis, st ructural equation modelling (PLS-SEM) and predictionoriented segmentation (PLS-P OS) were used. The main results indicate that the more digital capabilities orga nisations have, the more agile they become in relation to internal processes and changes in the external environment. This relationship is facilitated by the us e of AI tools. At the same time, prediction-oriented segmentation highlighted tw o distinct categories of organisations in terms of AI transformation: in those i n which this process is more advanced, the mediation effect is stronger.”
Bucharest University of Economic StudiesBucharestRomaniaEuropeArtificial IntelligenceEmerging TechnologiesMa chine Learning
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