Global Generative AI in Healthcare Market
The global Generative AI in Healthcare market is estimated to be worth over USD27.3Bn in 2033 and is expected to grow at CAGR of 32.0% during the forecast period (2024-2033).
The global generative AI in healthcare market is witnessingswift growth, fuelled by numerous key factors. One of the leading driving forces is the growing demand for personalized medicine, which generative AI can substantiallyimprove by evaluatingextensive amounts of patient data to personalize treatments to individual needs. In addition, the increasing prevalence of chronic diseases and the resulting need for accurate and efficient diagnostic tools are accelerating the adoption of AI technologies in the healthcare industry. The incorporation of AI with electronic health records (EHRs) is another essential factor, streamlining operations and enhancing patient outcomes through predictive analytics.
Significant opportunities in this market comprise the development of AI-powered drug discovery and development processes, which can dramaticallyminimize the cost and time related to bringing new medications to market. The automation of administrative tasks within healthcare institutions also offersconsiderable potential, enhancing operational efficiencies and enabling healthcare professionals to emphasis more on patient care. Additionally, advances in natural language processing (NLP) facilitate more effective patient interaction and data management, improving the overall healthcare experience.
Latest developments in the field underscore the augmentation of sophisticated AI models capable of diagnosing ailments with increased accuracy, such as AI algorithms designed for medical imaging analysis. These technologies are being increasingly amalgamated into routine medical practices, supporting radiologists and pathologists in determining abnormalities that might be overlooked by the human eye.
Novel technologies like deep learning and reinforcement learning are further extending the limits of what AI can achieve in healthcare. Deep learning models, specifically convolutional neural networks (CNNs), are surpassing in image recognition tasks, proving invaluable in radiology and oncology. Reinforcement learning, on the contrary, is exhibiting commitment in treatment planning and robotic surgery, optimizing decision-making processes and improving precision in surgical procedures.
All in all, the generative AI in healthcare market is poised for remarkable growth, fuelled by technological developments, growing healthcare demands, and major opportunities for innovation and efficiency improvements.
The market report presents an in-depth analysis, highlighting the capabilities of various stakeholders engaged in this industry, across different geographies. Amongst other elements, the market report includes:
A preface providing an introduction to the full report, Generative AI in Healthcare market, 2023-2033.
An outline of the systematic research methodology adopted to conduct the study on Generative AI in Healthcare market, providing insights on the various assumptions, methodologies, and quality control measures employed to ensure accuracy and reliability of our findings.
An overview of economic factors that impact the overall Generative AI in Healthcare market, including historical trends, currency fluctuation, foreign exchange impact, recession, and inflation measurement.
An executive summary of the insights captured during our research, offering a high-level view of the current state of the Generative AI in Healthcare market and its likely evolution in the mid-to-long term.
A brief introduction to the Generative AI in Healthcare , highlighting their historical background, as well as information on their types, key aspects, key challenges and the advantages of using Generative AI in Healthcare.
A detailed assessment of the market landscape of Generative AI in Healthcare that are either approved or being evaluated in different stages of development, based on several relevant parameters, such as By Application (Personalized Treatment, Patient Assistance, Patient Monitoring and Predictive Analytics, Medical Image Analysis and Diagnostics, Drug Discovery and Development), By End user (Hospitals, Specialty Clinics, Ambulatory Surgical Centres (ASCs), Research and Academic Institutes, Others). Further, the chapter features analysis on key niche market segments. In addition, the chapter features analysis of various Generative AI in Healthcare developers, based on their year of establishment, company size, location of headquarters and most active players.
An in-depth analysis of partnerships and collaborations that have been inked between various stakeholders, since 2019, based on several relevant parameters, such as the year of partnership, type of partnership, focus of partnership, purpose of partnership, therapeutic applications and most active players (in terms of number of partnerships). It also highlights the regional distribution of partnership activity in this market.
A detailed analysis of various investments made by companies engaged in this industry, since 2019, based on several relevant parameters, such as year of funding, type of funding (grants, seed, venture capital, initial public offering, secondary offerings, private equity and debt financing), type of HPAPIs, amount invested, geography, purpose of funding, stage of development, therapeutic area, most active players (in terms of number and amount of funding instances) and leading investors (in terms of number of funding instances).
An in-depth analysis of the various Generative AI in Healthcare focused initiatives undertaken by big market players, based on several relevant parameters, such as number of initiatives, year of initiative, type of initiative, purpose of initiative, focus of initiative and location of headquarters of the big pharma players.
One of the key objectives of this market report was to estimate the current market size and the future growth potential of the Generative AI in Healthcare over the forecast period. Based on several parameters, such as regional analysis as well as segmental analysis rates, we have developed informed estimates of the likely evolution of the Generative AI in Healthcare market over the forecast period 2023-2033. Our year-wise projections of the current and future opportunity have further been segmented based on relevant parameters, such as By Application (Personalized Treatment, Patient Assistance, Patient Monitoring and Predictive Analytics, Medical Image Analysis and Diagnostics, Drug Discovery and Development), By End user (Hospitals, Specialty Clinics, Ambulatory Surgical Centres (ASCs), Research and Academic Institutes, Others), by key geographical regions (North America, Europe, Asia-Pacific, Middle East and Africa, and South America) and leading players. In order to account for future uncertainties associated with some of the key parameters and to add robustness to our model, we have provided three market forecast scenarios, namely conservative, base, and optimistic scenarios, representing different tracks of the industry’s evolution.