The Real World of Digital Transformation

Mulder, Jeroen

doi:10.1007/978-1-4842-9066-8_3

“…Perpetual beta: The phrase "always in beta" aptly describes the state of AI tools and solutions [10]. Given their dynamic nature, they are perpetually undergoing testing, learning from new data, and evolving.…”

mentioning

confidence: 99%

AI-Powered Innovation in Digital Transformation: Key Pillars and Industry Impact

Aldoseri,

Al-Khalifa,

Hamouda

2024

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Digital transformation systems generate a substantial volume of data, creating opportunities for potential innovation, particularly those driven by artificial intelligence. This study focuses on the intricate relationship between artificial intelligence and innovation as foundational elements in the digital transformation framework for sustained growth and operational excellence. This study provides a holistic perspective on the cultivation and pillars of AI-powered innovation, highlighting their pivotal role in revolutionizing industries, including healthcare, education, finance, manufacturing, transportation, and agriculture. The work emphasizes the key pillars essential for fostering AI-powered innovation, including monitoring performance measurement to use the power of the present, continuous learning and innovation, data analytics and insights, predictive analytics, and innovative product development. This study investigates how these pillars serve as the foundation for groundbreaking advancements, driving efficiency, enhancing decision-making processes, and fostering creativity within organizations. This study explores the significance of continuous learning, interdisciplinary collaboration, and industry partnerships in nurturing a thriving AI-powered innovation ecosystem. By understanding and harnessing these fundamental elements, businesses can navigate the complexities of the digital age, fostering innovation that not only optimizes processes but also enhances the overall human experience, ushering in a new era of technological excellence and societal progress.

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AI-Powered Innovation in Digital Transformation: Key Pillars and Industry Impact

Aldoseri,

Al-Khalifa,

Hamouda

2024

Preprint

8

0

View full text Add to dashboard Cite

Digital transformation systems generate a substantial volume of data, creating opportunities for potential innovation, particularly those driven by artificial intelligence. This study focuses on the intricate relationship between artificial intelligence and innovation as foundational elements in the digital transformation framework for sustained growth and operational excellence. This study provides a holistic perspective on the cultivation and pillars of AI-powered innovation, highlighting their pivotal role in revolutionizing industries, including healthcare, education, finance, manufacturing, transportation, and agriculture. The work emphasizes the key pillars essential for fostering AI-powered innovation, including monitoring performance measurement to use the power of the present, continuous learning and innovation, data analytics and insights, predictive analytics, and innovative product development. This study investigates how these pillars serve as the foundation for groundbreaking advancements, driving efficiency, enhancing decision-making processes, and fostering creativity within organizations. This study explores the significance of continuous learning, interdisciplinary collaboration, and industry partnerships in nurturing a thriving AI-powered innovation ecosystem. By understanding and harnessing these fundamental elements, businesses can navigate the complexities of the digital age, fostering innovation that not only optimizes processes but also enhances the overall human experience, ushering in a new era of technological excellence and societal progress.

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Leveraging Digital Science for Improved QA Methodologies

Mothey

2022

Stallion J. Multidiscip. Assoc. Res. Stud.

1

0

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Products and processes are using digital technology to increase manufacturing efficiency and quality. The digital revolution of the industrial industry is primarily driven by intense competition and changing customer expectations. Manufacturers may improve customer experiences, save costs, and boost speed and efficiency by using digital technologies. The application of related individual digital technologies has not been thoroughly assessed and combined to achieve adequate QA in the building sector, and as a result, it has received limited attention, despite the expanding rich and fragmented literature focusing on Industry 4.0 and Quality Assurance (QA). Therefore, the purpose of this study was to collect, assess, and synthesize the existing literature on specific digital technology uses in quality assurance in the construction sector and suggest future lines of inquiry. Deming's cycle concept and a literature review methodology were used in this study to answer the following four research questions: (1) what is the literature's current state-of-the-art? (2) Which digital tools have been used in the construction sector for quality assurance? (3) Which QA process areas have seen the use of digital technology, and what are their uses? (4) What are the shortcomings of the current study and potential avenues for further investigation into digital technology for quality assurance in the construction sector? According to the data, since 2017, there has been a growing trend of study on digital technologies for quality assurance in the construction industry. Using six distinct study methodologies published throughout 18 different publishing sources, this spans 23 nations. Based on their functionality, four types of digital technologies were identified as having been used for quality assurance in the construction industry: data gathering technologies, decision-oriented technologies, collaboration technologies, and technologies linked to security and transparency. The use of digital technologies have a high degree of application during the "do" phase, enhancing the quality management procedure throughout construction towards reaching pre-stated quality standards, according to evaluation using Deming's cycle framework.

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The Real World of Digital Transformation

Cited by 3 publications

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AI-Powered Innovation in Digital Transformation: Key Pillars and Industry Impact

AI-Powered Innovation in Digital Transformation: Key Pillars and Industry Impact

AI-Powered Innovation in Digital Transformation: Key Pillars and Industry Impact

Leveraging Digital Science for Improved QA Methodologies

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