Artificial intelligence (AI) offers substantial benefits across the industries. It drastically reduces repetitive tasks, cost optimization, risk reduction, and great precision and accuracy in work. The healthcare industry utilizes new edge-cutting technology in various subdomains, including early disease diagnosis, robotic surgery, drug discovery, telemedicine, prognosis, medication management, and health monitoring. The augmentation of technology in human life eases tedious tasks requiring more mental and physical work. As a result, the lifestyle becomes sedentary. It leads to many health problems, but neurodegenerative disease is one of the most affecting diseases. Parkinson’s disease (PD) is rapidly spreading in India, especially among elders. Early prevention, diagnosis, and forecasting of PD is a crucial task. Various researchers have come up with the idea of identifying biomarkers that can help with early prognosis and the prevention of PD. Moreover, biomarkers play a vital role in drug response and target discovery. This research article proposes the bibliometric analysis of different biomarkers identified by numerous authors related to Parkinson’s disease. This paper reviews the AI-assisted biomarker identification research carried out in India between 2015 and 2024 using the PubMed database. It has been established that PD research has advanced significantly in the last few years. The analysis of keywords, author-co-author, author-organization, year-wise number of paper contributions, and citations shows the strength of this field of study. It will help to understand the impact of various Parkinson’s disease biomarkers and the research potential of the application of artificial intelligence in Parkinson’s disease. The bibliometric analysis suggests several key biomarkers for AI-based diagnosis and forecasting of PD, including proteinase-activated receptor-2, surfactant protein D, surfactant protein A, dipeptidyl peptidase-4, and small heterodimer partner. Recent studies have also focused on α-synuclein markers, neurotransmitter markers, oxidative stress, mitochondrial dysfunction, and lipid peroxidation. Active research areas include blood-based, imaging, and genetic biomarkers for PD.