Global artificial intelligence in healthcare market is estimated to witness high growth, owing to rising adoption of AI and increasing investments in precision medicine
Global artificial intelligence in healthcare market is estimated to be valued at USD 20.81 Bn in 2024, exhibiting a CAGR of 38.7% over the forecast period (2024-2031). Furthermore, rising demand for advanced medical technologies and need for cost effective healthcare services can also drive the market growth.
Market Dynamics:
Global artificial intelligence in healthcare market growth is driven by increasing adoption of AI technologies by healthcare providers and payers. AI helps in optimizing treatment costs by enabling precision diagnostics and streamlining workflow processes. It also facilitates drug discovery and expedites clinical trials. Rising investments by both private and public players in developing AI-driven products and platform solutions can boost adoption of AI across various segments of healthcare industry. For instance, diagnostics companies are using AI and ML for automated disease detection and surgical robots are integrated with computer vision technology for precision surgeries. Growing need for personalized care and supportive regulatory environment can drive the artificial intelligence in healthcare market growth.
Increasing investment in AI healthcare startups can drive the market growth
Rising global investments in AI healthcare startups can drive the market growth. Investors uses AI technologies to improve healthcare outcomes and reduce healthcare costs. Major tech giants like Google, Microsoft, Intel and IBM are actively investing and partnering with startups working on clinical decision support, personalized medicine, drug discovery, and population health management. Increased funding availability allows startups to further develop their AI solutions and bring them to market at a faster pace. This positive funding environment attracts more entrepreneurs to launch AI healthcare startups.
Growing need to analyze large and complex healthcare data can boost demand
Healthcare organizations are collecting massive amounts of data from various sources such as EHRs, medical images, sensors and mobile apps. However, analyzing this data to gain relevant insights manually is not feasible due to its size and complexity. AI is uniquely capable of detecting complex patterns in large datasets. It can assimilate and analyze data from multiple sources to yields actionable insights. This ability of AI to extract meaningful information from huge volumes of heterogeneous healthcare data boosts demand for AI solutions. Enterprises are increasingly adopting AI systems to gain clinical, operational and financial benefits through data-driven decision making. The need to effectively manage and analyze escalating healthcare big data with AI can drive the market growth.
Data privacy and security concerns pose challenges for market expansion
Healthcare data contains sensitive personal information of patients. Many people are rightfully concerned about potential privacy and security risks associated with collecting and sharing such data digitally. Any data breach can severely dent patients’ trust in healthcare organizations. It can also make them reluctant to share their medical records, thus, limiting the availability of data needed to train powerful AI systems. Implementing stringent data protection and anonymization techniques leads to increased cost and complexity. Addressing privacy concerns while facilitating data sharing can hamper faster adoption of AI across the healthcare spectrum. Legal and regulatory compliance issues around data privacy also create uncertainties affecting investments and innovations.
Shortage of trained AI healthcare professionals can hamper the market growth
Developing advanced AI applications for healthcare requires specialists with expertise in areas like deep learning, neural networks, computer vision, predictive modeling and medical sciences. However, there has been significant shortage of professionals with the right blend of technical and domain knowledge. Training more people with AI skills relevant to healthcare is time consuming and requires investment. Organizations face difficulties scaling up their AI teams for new product development and support. This skills gap challenges healthcare providers to leverage AI technologies to their fullest potential. It makes smaller practices and hospitals especially reluctant to implement major AI systems due to lack of in-house expertise. Shortage of qualified AI healthcare professionals can hamper the market growth.
Improving accessibility and affordability of AI-powered diagnostics
AI has the power to make critical medical knowledge and technologies more accessible to people globally, especially in underserved areas. Startups are developing AI-based tools for on-device pathology and radiology analysis using smartphone cameras. This can enable basic diagnostic tests and early disease detection in locations without modern healthcare facilities. Machine vision and language processing AI can also automate medical transcription and documentation work. This helps physicians spend more time with patients. Such accessibility-enhancing applications, if delivered at affordable prices, present a huge market opportunity. These can significantly improve outcomes for non-communicable diseases globally.
Personalized medicine enabled by analysis of individual health data
Conventional medical practices typically make diagnosis and treatment recommendations based on a "one-size-fits-all" approach. However, each patient's biology, lifestyle and underlying conditions differs. By harnessing the predictive prowess of AI on individual patient data over time, clinicians can deliver far more precise and customized healthcare. AI can identify specific biomarkers, genetic profiles or behavioral patterns linked to higher risks, better responses or adverse side-effects for a given person. This enables preemptive interventions, tailored drug therapies, and predictive care strategies. As health systems realize the clinical and financial benefits of personalized medicine enabled by AI, it will boost more investments and adoption of AI.
Key Developments:
- In April 2024, a generative AI-powered digital health promoter designed to enhance public health awareness. Known as the Smart AI Resource Assistant for Health, S.A.R.A.H. can assist users in understanding risk factors for major diseases such as cancer, heart disease, lung disease, and diabetes.
- In March 2024, NVIDIA launched new Generative AI Microservices that are designed to revolutionize medical technology (MedTech), drug discovery, and digital health. This groundbreaking initiative seeks to transform healthcare technology by leveraging cutting-edge AI capabilities.
- In March 2024, Microsoft partnered with NVIDIA to drive AI innovation and boost computing capabilities. This partnership combines Microsoft Azure's global infrastructure and advanced computing power with NVIDIA’s DGX Cloud and Clara suite to accelerate innovation and enhance patient care.
- In December 2023, Google announced the launch of MedLM, a suite of foundation models that are designed to assist healthcare organizations through generative AI, according to a blog post shared with HealthITAnalytics. This launch builds on Google's existing health AI initiatives, including the development of Med-PaLM, a healthcare-tuned large language model.
Key Player:
GE Healthcare, Siemens Healthineers, Philips Healthcare, NVIDIA, Intel, Babylon Health, Komodo Health, Aidoc, Google Health, Exscientia, Butterfly Network, Relay Therapeutics, PathAI, Viz.ai, Canon Medical Systems, Microsoft, Oncora Medical, Biosymetrics, Arterys, Ada Health
