ARTIFICIAL INTELLIGENCE DIAGNOSTICS MARKET ANALYSIS

The global artificial intelligence (AI) diagnostics market was valued at US$ 1,110.7 Mn in 2022 and is forecast to reach a value of US$ 5,773.6 Mn by 2030 at a CAGR of 21.2% between 2023 and 2030. The global artificial intelligence (AI) diagnostics market is experiencing strong growth owing to the increasing technology advancement and the integration of artificial intelligence (AI) into the healthcare system. This integration has led to improved diagnostics, personalized treatment plans, and more efficient healthcare delivery. Additionally, the AI market is also being driven by the growing demand for automation and optimization of various industries such as manufacturing, finance, and retail.

Global Artificial Intelligence (AI) Diagnostics Market: Regional Insights

• Based on geography, the global artificial intelligence (AI) diagnostics market is segmented into North America, Latin America, Europe, Asia Pacific, Middle East, and Africa.
• Among regions, increasing adoption of Artificial Intelligence (AI) in disease identification & diagnostics, and increasing investment in AI healthcare startups are factors expected to drive North America’s AI in diagnostics market. In addition, growing demand for reducing diagnostic costs, improving patient care, and reducing machine downtime are further accelerating usage of AI in diagnostics. According to Health IT Analytics in May 2017, researchers from Case Western Reserve University used a deep learning network, which is a subset of AI, to identify breast cancer in pathology images with 100% accuracy. 
• Increasing patient pool, ongoing pandemic, growing acceptance of cloud computing, and rising number of government programs supporting AI are among the key factors expected to drive the market in Asia Pacific. In addition, an increasing number of biopharmaceutical firms are applying AI to modernize the drug discovery process, with more AI applications being found in the field of diagnostics. For instance, in 2017, China’s Tencent introduced an AI-driven diagnostic medical imaging facility, called AI Medical Innovation System (AIMIS). The technology exhibited 90% and 95% accuracy for initial diagnoses of esophageal & lung cancers, respectively.

Figure 1. Global Artificial Intelligence (AI) Diagnostics Market Share (%), by Region, 2023

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Global Artificial Intelligence (AI) Diagnostics Market Drivers:

• Increasing Number of Startups, Collaborations, and Venture Capitalist Funding: The AI healthcare market is growing at a rapid pace, constantly showing untapped opportunities for entrepreneurs. As per a DataRoot Labs article in September 2020, over the recent years, AI innovation in the healthcare space has been overwhelming and the market is growing from USD 1,110.7 Mn in 2022 to USD 5,773.6 Mn in 2030 at a CAGR of 21.2%. The healthcare space holds large volumes of data from imaging, genomics, and diagnostics, which has led to the emergence of startups over recent years. In addition, the ongoing COVID-19 pandemic has given digital health a push, ranging from telehealth diagnostics to rapid testing, with startups receiving motivation & boosts to their product deliveries. Startups in personalized and connected healthcare are receiving recognition by enabling patients to track their health, allowing them to choose & manage their healthcare services.
• Integration AI into the medical system is expected to drive market growth: Another factor which is driving the growth of the global artificial intelligence (AI) diagnostics market is the integration of AI in to the medical, and healthcare sector. For instance, Integration of AI into electronic medical records can provide multiple benefits and can significantly improve diagnostic algorithms, decision support, interoperability, flexibility, capturing physician-patient conversation. For instance, Google collaborated with delivery networks for prediction modules to alert health risks such as heart failure. Machine learning solutions for IBM Watson, AllScripts, and Change Healthcare are using healthcare data to recommend personalized treatment options. Amazon Web Services provides a cloud computing tool that uses AI to extract and index data from clinical notes.
• Saykara’s virtual assistant tool, Kara, uses voice recognition, language processing, and machine learning models to capture physician-patient conversation & turn it into notes stored in EMRs.
• Market players trying to improve the alignment between EMRs and AI technologies are limited, leaving scope for untapped opportunities, to be leveraged by innovators and startups. Future EMRs can be developed with scope for integration of data captured from telehealth services and wearable’s. This can allow data to be used in clinical studies, home health tracking, advanced diagnostics, and prediction of health risk events.

Artificial Intelligence (AI) Diagnostics Market Opportunities:

Managing and preventing or delaying the onset of chronic diseases can be a taxing & time-consuming task. AI-based data-driven technologies are enabling healthcare personnel to accurate and timely treatment, enabling a more proactive & preventive approach rather than a reactive one. AI can help provide an integrated care plan to better manage chronic ailments. Image processing, diagnostic findings, deep learning, and neural networks have experienced advancements over the past few years. For instance, in December 2020, the two companies partnered and combined resources in medical image analysis for pulmonary diseases, to develop an end-to-end AI-based solution for detecting and treating pulmonary embolism, based on historical images.

Global Artificial Intelligence (AI) Diagnostics Market Trends:

• Increase rise in research on AI by combining with the heath sector: In the field of pathology, which is filled with large datasets consisting of types and subtypes of a disease specimen & biomarkers, it can be extremely complicated & exhausting for a human pathologist to keep up with changes. A research article was published by Dyche in 2018, studying deep learning approaches in detecting metastatic breast cancer in lymph nodes. The study showed significant accuracy in detecting small deposits of cancer, which could be fatiguing for a human pathologist. AI- based systems can work continuously and can be trained to record and analyze any number of specimens. The integration of AI in pathology with large datasets of genomics and biomarkers can help ease out the role of a pathologist in providing accurate and efficient diagnostics.

Global Artificial Intelligence (AI) Diagnostics Market Restraints:

• Procurement costs and maintenance is expected to hinder market growth: The AI-based healthcare market includes high procurement costs and requires major initial capital, followed by upgradation & maintenance costs. Financially established players, such as hospitals are major investors in the market. With low government spending on developing and introducing AI-based technologies, most of the expenses are borne directly by the private consumer. For instance, the European government has yet to long-term investment-intensive strategies in adopting AI-based healthcare solutions. Procurement of hardware and software solutions to integrate AI into the healthcare setting involves major costs due to the complexity of engineering in the system. Furthermore, an average repair or maintenance of an AI-based system can be extremely expensive. These systems need constant upgrades to keep up with changing scenarios involving such costs. In addition, substantial investments are required in digitalization and training programs. Healthcare systems have already made significant capital investments in rolling out electronic health record systems and to acquire & integrate AI solutions in healthcare settings, which is likely to be an expensive ordeal.

Figure 2. Global Artificial Intelligence (AI) Diagnostics Market Share (%), by Component, 2023

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Global Artificial Intelligence (AI) Market Segmentation:

The global artificial intelligence (AI) diagnostics market report is segmented into Product, Application, End User, and Region.

• Based on Component, the market is segmented into Software, Hardware, and Services. Out of which, Software Segment is expected to dominate the artificial intelligence (AI) market over the forecast period and this is attributed to the increasing integration of AI technology into the healthcare system.
• Based on diagnostics Type, the market is segmented into Cardiology, Oncology, Pathology, Radiology, Neurology, and Others. Out of which, Cardiology Segment is expected to dominate the market over the forecast period and this is attributed to the increasing prevalence rate of cardiovascular disease worldwide. 

Global Artificial Intelligence (AI) Diagnostics Market: Key Developments

• In February 2021, Vuno expanded its business offerings to Taiwanese markets by signing a distribution agreement with CHC Healthcare Group, to hand over marketing and distribution rights of its AI solutions in Taiwan.
• In November 2020, AliveCor, Inc., the company received U.S. FDA approval for its product, Karida AI V2, a next-gen interpretive ECG algorithm. This approval enables the company plan commercialization strategies for the product in the U.S. market.

Global Artificial Intelligence (AI) Diagnostics Market: Key Companies Insights

The global artificial intelligence (AI) diagnostics market is highly competitive. This is attributed to the rise demand for advanced hardware component for the integration of AI technology, as a result, players in the market are focusing on launching novel hardware components in the market.

Some of the key players in the global artificial intelligence (AI) diagnostics market are Kaz USA Inc., Microlife Corporation, Omron Corporation, Cardinal Health, Easywell Biomedicals, Welch Allyn Inc., Hicks Thermometers Limited, and American Diagnostic Corporation, among others.

*Definition: By using AI algorithms to analyze vast amounts of medical data and identify patterns and relationships, general AI for medical diagnostics can transform the field of medicine, leading to improved patient outcomes and a more efficient and effective healthcare system. However, the development and deployment of AI in medical diagnostics are still in the early stages, and there are several technical, regulatory, and ethical challenges that must be overcome for the technology to reach its full potential.