AI IN RESEARCH METHODOLOGY

Artificial Intelligence (AI) integration has become a revolutionary
force in the constantly changing field of research technique,
transforming inquiry and analytic paradigms. Artificial intelligence
(AI) has a significant influence on research procedures in a wide
range of disciplines, including the social sciences and natural
sciences. This is because AI breaks through conventional limits and
adds new dimensions to the investigative process. This introduction
aims to guide the reader through the rapidly developing field of
artificial intelligence (AI) and research, explaining the many ways
that AI technologies have developed into vital resources for
modern academics and researchers. The origins of artificial
intelligence (AI) in research methods may be found in the
extraordinary rise in data collection and accumulation, which was
fueled by information digitalization and technical breakthroughs.
Artificial Intelligence (AI), which offers unmatched skills in data
processing, pattern recognition, and predictive modelling, emerged
as a potent ally when conventional research tools and approaches
failed to handle the sheer amount and complexity of data. The
mutually beneficial association between artificial intelligence (AI)
and research methodology stems from machine learning
algorithms' capacity to identify significant patterns in large
datasets, which empowers researchers to derive useful insights and
arrive at well-informed conclusions. Furthermore, AI has an
impact on every step of the research process, not just data analysis.
Artificial Intelligence (AI) has become a crucial tool for
researchers, helping with anything from creating research
questions and planning experiments to automating literature
reviews and producing hypotheses. Since the development of
natural language processing (NLP), information can now be
extracted from a wide range of textual sources, allowing academics
to synthesise knowledge on a never-before-seen scale. This
paradigm change not only speeds up the research process but also
creates opportunities to investigate interdisciplinary relationships
and promote a more comprehensive comprehension of complicated
phenomena