AI In Healthcare Market Size & Trends
The size of the global AI in healthcare market was estimated at USD 19.27 billion in 2023 and is anticipated to register a CAGR of 38.5% during the period from 2024 to 2030. The major growth driver for the market is the growing need in the healthcare industry for increased efficiency, precision, and improved patient outcomes. A March 2024 Microsoft-IDC study reports that 79% of healthcare organizations are currently leveraging AI technology. Besides, the investment return on artificial intelligence (AI) is achieved within 14 months, returning USD 3.20 for each USD 1 invested in AI. Artificial intelligence technologies have the potential to revolutionize different fields such as medical image analysis, predictive analytics, treatment planning tailored to the individual, and drug discovery, with the potential to revolutionize traditional healthcare practice.
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Artificial Intelligence in Healthcare Market Trends
Innovations in big data analytics solutions have driven the growth of the AI in healthcare market extensively. These solutions allow healthcare professionals to effectively process and analyze huge volumes of medical information, such as patient history, genomic information, clinical trials, and others.
For example, in March 2024, Quibim introduced automated AI device QP-Liver for MR diagnosis of diffuse liver disorders using precise quantification of tissue fat and iron content. Likewise, DeepCare, an AI platform designed for end-to-end EMR data processing. It employs a deep dynamic memory neural network to read and retain experiences and in memory cells. Therefore, the arrival of sophisticated analytical tools coupled with growing applications of artificial intelligence in various fields of application is expected to drive the growth of artificial intelligence in the healthcare industry.
Additionally, applications of artificial intelligence and its expanding frontiers in research fields are further seen to fuel the market growth.
Artificial Intelligence in Healthcare Market Analysis
Discover more about the major segments influencing this market
On the basis of the offering, the market is segmented into software and services. The market was led by the software segment with a revenue of USD 11.7 billion in 2023.
Regular enhancements in machine learning algorithms allow for more precise predictions and insights into medical data. Moreover, natural language processing (NLP) improvements allow AI software to read and write human-like language, thus simplifying medical transcription, clinical documentation, and patient communication. All these benefits related to software segment are poised to drive the growth of the market.
In addition, AI-based software improves medical imaging analysis, facilitating early disease detection and precise diagnosis through methods such as computer vision and pattern recognition. These improvements improve patient compliance and satisfaction, thus strengthening the segmental growth.
Artificial Intelligence in Healthcare Market Share
The artificial intelligence in healthcare industry is highly competitive in nature with well-established pharmaceutical & healthcare IT companies producing AI-based healthcare products competing for market share. The key players are indulging in strategic activities like collaboration, service launch, investment, and partnerships to enhance their product portfolio. The firms are increasingly implementing a multi-pronged approach to respond to the growing demand for artificial intelligence in healthcare.
Artificial Intelligence in Healthcare Market Companies
Key players functioning in the artificial intelligence in healthcare market are as discussed below
Aidoc
AiCure
APIXIO, Inc.
Atomwise, Inc.
Butterfly Network
Dassault Systemes (Medidata)
Enlitic Inc.
Koninklijke Philips N.V.
IBM Corporation
iCarbonX
Insilico Medicine Inc
Itrex Group
IQVIA
NVIDIA Corporation
Sophia Genetics
Artificial Intelligence in Healthcare Industry News
In October 2023, ZS, launched the AI-driven ZAIDYN Connected Health solution. ZAIDYN Connected Health assists pharmaceutical firms, healthcare providers and payers to better engage with patients and enhance health outcomes. The launch strategy is likely to enable the company to grow its service offerings.
In August 2023, Softheon, revealed the creation of Artificial Intelligence Management for Enterprise (AIME) in its Softheon +AI platform. AIME is intended to assist Softheon customers with a variety of challenges, from improving call center employee knowledge to simplifying the understanding and analysis of health plan data. This approval was intended to expand the treatment availability, supplementing current services to analyze patient health.
Market, By Offering
- Software
- Machine learning
- Natural language processing
- Context-aware computing
- Computer vision
- Services
Market, By Application
- Medical imaging & diagnosis
- Drug discovery
- Therapy planning
- Hospital workflow
- Wearables
- Virtual assistants
- Other applications
Component Insights
The software solution segment is expected to expand at the highest CAGR of 38.7% during the forecast period. Growth in the segment is due to the high-rising adoption of AI-based software solutions among patients, payers, and healthcare providers. For example, in September 2019, GE Healthcare collaborated with five local Chinese software developers i.e., 12Sigma Technologies, Biomind, Shukun Technology, Yizhun Medical AI, and YITU Technology to collectively work on developing the Edison AI platform and facilitate the smooth digital transformation of GE Healthcare.
The services segment of services component is expected to experience a high growth rate between 2024 and 2030. The segment growth can be contributed by the increasing penetration of AI-based technologies across various healthcare applications, including clinical trials, virtual assistants, robot-assisted procedures, reduction in dosage errors, and fraud prevention.
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Technology Insights
The ML technology category accounted for the largest market share in 2023. The healthcare sector produces enormous volumes of data, such as EHRs, medical images, genomic information, and wearable device data. Machine learning is well-suited to uncover meaningful insights from these huge and heterogeneous sets of data, allowing healthcare professionals to make informed decisions and enhance patient outcomes. The technology is highly embedded in healthcare solutions for the diagnosis, prognosis, and treatment planning of diseases. Leveraging patient data patterns and correlations, ML models can detect early disease indicators, forecast patient outcomes, and propose personalized treatment strategies, thereby enhancing the accuracy and timeliness of interventions.
