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This study aims at the latest trends for disruptive technologies. With the emergence of machine learning and artificial intelligence, the very fabric of every system has been shaken, therefore, the study highlights the essential factors through extensive thematic analysis.  As it is qualitative research that employs content analysis to explore the impact of machine learning (ML) and artificial intelligence (AI) as enablers for disruptive technologies. This study has been done in three major phases: 1) data collection, 2) theme extraction, and 3) thematic analysis. A total of 570 articles encompassing industry reports, academic databases, and news sources, published between 2013 and 2023, were analyzed using content analysis. A coding scheme was developed, and key themes were extracted and categorized. The developed categories include efficiency, innovation, accessibility, network effects, scalability, and disintermediation. To substantiate the extracted themes, we also conducted interviews of 27 experts from the field of AI and ML to gain a deeper understanding. Thematic analysis was employed to analyze the interview data, and a set of findings and conclusions were developed based on the recurring themes that emerged from the data. The study provides valuable insights regarding the role of AI and ML as enablers of disruptive technologies and their impact on different sectors.

Article Details

Author Biography


Dr. Muhammad Zia-ur-Rehman

Post-Doc Fellow & Faculty Member, Universiti Malaya/NDU


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