Global Artificial Intelligence in Healthcare Market - 2022-2029
The Global Artificial Intelligence in Healthcare Market is expected to grow at a CAGR of 49.7% during the forecasting period (2021-2028).
Artificial intelligence (AI), the term broadly refers to computing technologies that resemble processes associated with human knowledge. It is an integration of several techniques such as natural language processing, machine learning, and reasoning. AI is being used for a range of healthcare and research purposes, including detection of disease, management of chronic conditions, delivery of health services, and drug discovery.
The global artificial intelligence in healthcare market growth is driven by the ability of AI to improve patient outcomes increase in adoption of precision medicine, and the need strengthen coordination between the healthcare workforce & patients. With the need for pre-operative planning, high costs associated with healthcare, and rising chronic diseases, the technological advancements are seen in AI are much anticipated.
Improving computing power and declining hardware cost is driving the market growth
The increasing adoption of AI has been a new growth driver for semiconductor chipset manufacturers in recent years. GPU/CPU manufacturers, such as Nvidia, AMD, Intel, Qualcomm, Huawei, and Samsung, have significantly invested in this field for the development of chipsets that are compatible with AI-based technologies and solutions. Apart from CPUs and GPUs, application-specific integrated circuits (ASICs) and field-programmable gate arrays (FPGAs) are being developed for AI applications. For instance, Google has built a new ASIC called tensor processing unit (TPU).
A compute-intensive chipset is one of the critical parameters for processing AI algorithms, the faster the chipset, the quicker it can process the data required to create an AI system. Currently, AI chipsets are mostly deployed in data centers/high-end servers as end computers are currently incapable of handling such huge workloads and do not have enough power and time. Nvidia has a range of GPUs that offer GPU memory bandwidth based on the application. For instance, GeForce GTX Titan X offers a memory bandwidth of 336.5 GB/s and is mostly deployed in desktops, while Tesla V100 16 GB offers a memory bandwidth of 900 GB/s and is used in AI applications. Similarly, Nvidia’s Tesla V100 (32 GB) is used in high computing workloads. It delivers two times higher throughput compared with its previous generation and offers ~300 GB/s to unleash the highest application performance possible on a single server for approximately the same price (USD 8,799).
Concerns regarding data privacy will hamper the market growth
AI has several useful applications in healthcare. However, the adoption of AI in the industry is restricted owing to data privacy concerns. Patient health data is protected under federal laws in several countries, and any breach or failure to maintain its integrity can result in legal and financial penalties. As AI used for patient care requires access to multiple health datasets, AI-based tools need to adhere to all the data security protocols implemented by governments and regulatory authorities. This is a difficult task as most AI platforms are consolidated and require extensive computing power owing to which patient data, or parts of it, can be required to reside in a vendor’s data center. The vendor data centers are not secure enough to avoid data breaches as the data is accessible to an array of employees and containing breaches becomes much more difficult. If the patients’ data is leaked from these data centers, even inadvertently, it can lead to huge lawsuits and settlement claims by aggrieved parties. This is a major challenge in the market.
COVID-19 Impact Analysis
The onset of the COVID-19 pandemic proved to be an opportunity to showcase the prowess and sophistication AI can bring to the healthcare sector. During the second wave of the pandemic hospitals and clinics across the world made use of AI-based virtual assistants, inpatient care bots, and AI-assisted surgery robots to handle the continuous influx of patients, which would have otherwise overwhelmed the entire hospital operation cycle. With several countries such as the US, Germany, France, China, India, Japan, and South Korea allocating funds to develop AI applications in the healthcare sector, the market is expected to boom over the course of 5 to 10 years.
The machine learning segment is expected to grow at the fastest CAGR during the forecast period (2022-2029)
The machine learning segment is anticipated to witness significant growth. Machine learning (ML) is a subclass of artificial intelligence technology, where algorithms process large data sets to detect patterns, learn from them, and execute tasks autonomously without being instructed on exactly how to address the problem. In recent years, the wide availability of powerful hardware and cloud computing has resulted in the broader adoption of ML in different areas of human lives, from using it for recommendations on social media to adopting it for process automation in factories. And its adoption will only grow further.
Healthcare is an industry that keeps up with the times as well. With the amount of data generated for each patient, machine learning algorithms in healthcare have great potential. So, that’s no wonder that there are multiple successful machine learning applications in healthcare right now. Let’s learn more about them. Using machine learning for healthcare for tasks above can provide a lot of opportunities for healthcare organizations. First, it allows healthcare professionals to focus on patient care rather than spend their time on information search or entry. Using machine learning in medicine can help to develop a more precise treatment plan. A lot of medical cases are unique and require a special approach for effective care and side effect reduction. Machine learning algorithms can simplify the search for such solutions.
North America region holds the largest market share of the global artificial intelligence in the healthcare market
North America has the largest market share in the forecast period owing to the factors such as the robust adoption trends registered by digital technologies in healthcare. Various government initiatives and funding in the U.S. are focusing on encouraging the industry progression of healthcare AI. Increased funding for big data analytics is a key aspect for improving healthcare artificial intelligence in the region. For instance, artificial intelligence has started transforming healthcare by leveraging big data analytics to optimize better healthcare services. Similarly, IBM Watson examines patient data and provides treatment plans by combining attributes from external research, patient file, and clinical expertise.
Moreover, the growing geriatric population, changing lifestyles, increasing prevalence of chronic disorders, growing demand for value-based care, and rising awareness levels towards the implementation of AI-based technologies is bolstering the market growth in North America.
Artificial intelligence in healthcare market is a moderately competitive presence of local as well as global companies. Some of the key players which are contributing to the growth of the market include Intel, Koninklijke Philips, Microsoft, IBM, Siemens Healthineers, Nvidia, Google, General Electric Company, Medtronic, Micron Technology among others. The major players are adopting several growth strategies such as product launches, acquisitions, and collaborations, which are contributing to the growth of artificial intelligence in healthcare market globally. For instance, in November 2021, Philips extended the artificial intelligence (AI)-enabled CT imaging portfolio at the Radiological Society of North America (RSNA) 2021.
Intel Corporation designs manufacture and sells computer components and related products. The Company’s major products include microprocessors, chipsets, embedded processors and microcontrollers, flash memory, graphic, network and communication, systems management software, conferencing, and digital imaging products.
Intel Distribution of OpenVINO toolkit: OpenVINO toolkit is a free toolkit facilitating the optimization of a deep learning model from a framework and deployment using an inference engine onto Intel hardware. OpenVINO also provides new acoustic and language models to work. A full end-to-end speech processing scenario is covered and demonstrated by libraries and tools distributed with OpenVINO.
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Global Artificial Intelligence in Healthcare Market– By Product type
Global Artificial Intelligence in Healthcare Market- By Technology
Natural language processing
Global Artificial Intelligence in Healthcare Market– By Application
Imaging & diagnostics
Insights & risk analytics
Healthcare assistant robots
Global Artificial Intelligence in Healthcare Market– By End User
Global Artificial Intelligence in Healthcare Market- By Region
Middle East & Africa
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