As organizations navigate an increasingly dynamic market, the integration of Artificial Intelligence (AI) has shifted from being a technological advancement to a strategic imperative.
Generative AI and Multifactor Productivity in Business (ISBN: 9798369311981) explores the transformative potential of OpenAI in redefining business operations, accelerating innovation, and driving productivity. However, alongside its promise comes critical challenges, including ethical considerations, sector-specific applications, and safe implementation practices. The book delves into these complexities, bridging scholarly research and real-world business applications to provide a comprehensive understanding of OpenAI’s role across industries. With insights spanning global economic dynamics, labor market adaptation, and environmental sustainability, it serves as a vital resource for business leaders, academics, and policymakers alike. One of its key contributions includes a chapter by Dr. Ali Sorour, an expert in AI-driven performance management, who examines the integration of transformer models like ChatGPT into Business Intelligence (BI) within Higher Education. His research highlights how AI can enhance decision-making, streamline data handling, and improve quality assurance processes. Through such explorations, this book not only informs but equips readers with the knowledge to harness AI for efficiency, growth, and competitive advantage. Be sure to check out his Q&A below.
Dr. Ali Sorour Answers Our Questions
What is your professional background that gives you the knowledge needed to work on this publication?
Dr. Ali Sorour: As I held Lecturing and consultancy roles in several higher education institutions, I was directly dealing with quality assurance issues in higher education institutions. Higher education institutions struggle in monitoring quality. However, higher education institutions are required for several purposes to comply with national and international quality standards. For example, institutions are required by the higher education councils to comply with national standards in order to assure that minimum level of quality of services are provided by these institutions. Additionally, many higher education institutions tend to obtain international accreditation that assure excellence in quality of education they provide.
What inspired you to write your chapter?
Dr. Ali Sorour: Higher education institutions are facing challenges while complying with quality requirements. The nature of these requirements does not allow institutions to be able to trace them through simple Key Performance Indicators (KPIs) calculations. The fact that the institution’s management desire to determine non-compliance issues in the real time put more pressure toward measurement of quality-related activities. A major part of quality assurance processes is the assessment of learning outcomes. Learning outcomes are subjective and require quantification through the use of rubrics. The quantification process is complex and time consuming. Natural Language Processing (NLP) through the use of transformers may have potential in assisting in automating this quantification process and achieving advantages for higher education institutions.
What is your mission for the chapter?
Dr. Ali Sorour: I wanted to propose a solution through the utilization of transformers to provide AI-analytics which assist in monitoring learning outcomes and improve quality in higher education institutions.
How is your research going to impact your field and how does it relate to current trends and social matters?
Dr. Ali Sorour: The use of AI-driven analytics should never be limited to higher education quality. In the context of higher education, it can assist in adopting continuous monitoring concepts in terms of sustainability management, cybersecurity threats, or health and safety. The integration between AI and Business Intelligence (BI) systems lack theoretical underpinning. Future research should focus on building theoretical background for AI-BI systems to strengthen the base that IT professionals will rely on while adopting new inventions in technology.
Who is the publication intended for? Who ultimately will benefit from this title?
Dr. Ali Sorour: This publication is intended for higher education institutions and quality assurance specialists, highlighting AI's critical role in higher education quality and how quality assurance has evolved beyond annual audits and peer reviews, with Business Intelligence reshaping monitoring processes.
How does this publication stand out from others like it?
Dr. Ali Sorour: This is the first published material on the utilization of AI-analytics in assessing learning outcomes in higher education institutions. The proposed concepts in the chapter should open the doors for further research on continuous monitoring of performance in higher education to achieve higher transparency and better utilization of resources.
What are some future directions for your research?
Dr. Ali Sorour: Future projects encompass the utilization of AI-driven analytics in audit firms. This allows audit firms to identifying the patterns in the very large data sets and deal with big data. It will assist in extending the scope of audit to include 100% of the population instead of relying on sampling techniques, which will improve the reliability of audit reporting.
Disclaimer: The opinions expressed in this article are the author’s own and do not reflect the views of IGI Global Scientific Publishing.
About the Contributor
Ali Sorour BSc, MBA, MSc (Computing), PhD, SOCPA, CIA, CISA, CPA, MBCS. He received the M.Sc. degree in Computing in 2017 and the Ph.D in Computer Science in 2022, both from Staffordshire University, United Kingdom. He have more than 10 years of academic and professional experience. Sorour is acting as an independent consultant for several public and private institutions in the field of performance management using AI-Driven technologies. He developed several BI dashboards for purposes such as monitoring risks and detection of money laundering transactions in audit firms. His research interests include artificial intelligence, business intelligence & analytics, and FinTech.