AI in Medicine is a rapidly evolving field, with many medical universities, pharmaceutical companies, insurance companies, hospitals and healthcare providers investigating profits. These include the faster diagnosis of specific diseases, imaging analysis, and the creation of particularly highly personalized care plans.
According to Grand View Research, global AI on the healthcare market size is estimated at US$265.7 billion in 2024 and is projected to reach $1876.9 billion by 2030, growing at a stunning CAGR of 38.62% from 2025 to 2030.
“The key factors driving market growth are the increased demand for the health sector for improved efficiency and improved patient outcomes,” their recent report suggests.
- North American AI in the healthcare industry dominates the global market, accounting for the largest revenue share in 2024, exceeding 54%.
- Based on components, the Software Solutions segment dominated the market with its largest revenue share of over 46% in 2024
- Based on the application, the robot-assisted surgical segment dominated the market in 2024 with revenue sharing of over 13%.
- Based on technology, the Machine Learning segment held its largest market share in 2024, exceeding 35%.
According to Oncology and Orthopedic Surgeon James C. Wittig, Maryland Orthopedic Surgeon, the possibility of AI to increase the accuracy and efficiency of tumor diagnosis is just one way patients and providers can benefit.
“We've been using images to detect and define tumors for a long time,” Wittig says. “AI systems allow you to analyze large datasets to identify patterns and abnormalities in medical images within minutes. This includes reviews of basic scans before cancer is usually detected. Also, early detection is key before removing malignant tumors and causing irreversible harm to the body.”
Wittig also noted that once the diagnosis is reached, AI systems can perform an automated “second opinion.”
“Once tumors are understood and options are clarified, AI applications can analyze individual patient information and allow care teams to quickly develop and track personalized treatment plans by combining multiple actions including surgery, chemotherapy, radiation, and lifespans of preventive and recovery care,” he said.
Such applications demonstrate the potential for AI transformation in oncology, Wittig noted. Beyond patient-centered individualized cell and molecular care that enhances the likelihood of full recovery, “large datasets can be analyzed using AI platforms, which inform future research and investments, and ultimately invest in new preventive and normative modalities that will lead to global treatment of cancers that we want to identify lives.”
Arti Loftus is an experienced information technology specialist who has demonstrated his history of working in the research, writing and editing industry under her belt, with many published articles.
Edited by Erik Linask
