The Changing Landscape of Academic Research in the Age of Artificial Intelligence (AI)
Publication Date
3-8-2025
Zoom Link for Presentation
Start Date
3-8-2025 12:45 PM
End Date
3-8-2025 1:15 PM
Presentation Type
Research Presentation
Showcase Track
Contemporary Issues in Higher Education (CIHE)
Abstract
This paper looks at the transformative power of AI integration in academic research, underscoring how AI tools and/or technologies are reshaping research landscape. The emergence of AI has introduced new tools and methodologies that enhance the execution of research. The paper examines the various applications of AI in academic research, such as conduct of comprehensive literature review and data analysis through the use of machine learning techniques and advanced algorithms among others. Additionally, the paper discusses the implications of AI application on research efficiency and accuracy as well as ethical considerations and challenges. Through this comprehensive overview of evolving AI integration and its future prospects, the paper expounds on the potential of AI in transforming academic research and drive innovation across disciplines. The paper concludes by underscoring the need for interdisciplinary collaboration, continuous education, and robust ethical frameworks to tap the full potential of AI while mitigating associated risks.
Recommended Citation
Chongwony, Lewis, "The Changing Landscape of Academic Research in the Age of Artificial Intelligence (AI)" (2025).
Franklin University Scholarship Showcase. Paper 31.
Available at: https://fuse.franklin.edu/showcase/2025/presentations/31
The Changing Landscape of Academic Research in the Age of Artificial Intelligence (AI)
This paper looks at the transformative power of AI integration in academic research, underscoring how AI tools and/or technologies are reshaping research landscape. The emergence of AI has introduced new tools and methodologies that enhance the execution of research. The paper examines the various applications of AI in academic research, such as conduct of comprehensive literature review and data analysis through the use of machine learning techniques and advanced algorithms among others. Additionally, the paper discusses the implications of AI application on research efficiency and accuracy as well as ethical considerations and challenges. Through this comprehensive overview of evolving AI integration and its future prospects, the paper expounds on the potential of AI in transforming academic research and drive innovation across disciplines. The paper concludes by underscoring the need for interdisciplinary collaboration, continuous education, and robust ethical frameworks to tap the full potential of AI while mitigating associated risks.