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The total addressable market for healthcare AI is vast but remains largely untapped

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The healthcare AI software market is forecast to grow to over US$10 billion in 2025

Omdia considers the healthcare artificial intelligence (AI) market to be nascent because of its relatively small size compared to the total addressable market. Omdia estimated that in 2019, the global market for healthcare AI software was $823 million, making it the sixth-largest industry for AI revenue, but only a small fraction of the $16 billion total AI software market. Omdia forecasts that the healthcare AI software market will grow to over $10 billion in 2025. This drastic growth will be driven by the large size of the healthcare equipment market, which totalled $214 billion in 2019, and the great amount of investment available to the healthcare industry. Despite the great potential provided by the healthcare industry, the healthcare AI market remains mostly untapped as the technology is still in early stages of development and faces barriers, such as regulation, and many healthcare providers are unsure of the value of AI.

AI vendors have developed advanced AI algorithms that can be applied to healthcare devices, especially for medical imaging. Many major healthcare equipment manufacturers have partnered with these vendors to incorporate AI tools into product lines or have developed AI software tools in-house. Collaborations between healthcare providers, equipment manufacturers, and AI vendors will be crucial to ensuring that healthcare challenges are addressed. AI has the potential to help combat the growing problem of strained healthcare provision by helping healthcare practices deliver better patient outcomes with limited resources. These challenges have been exacerbated by the pandemic caused by coronavirus disease 2019 (COVID-19), making healthcare AI of the utmost importance.

Healthcare AI, especially for ultrasound, is developed in collaboration with end-users to solve real-world problems

According to the Omdia Artificial Intelligence for Ultrasound Survey (AIUS) 2020, many healthcare practices rely on AI to address top-cited areas of improvement, including image quality and standardization, workflow efficiency, and diagnostic support. For example, algorithms assist in prioritizing and screening patients. Next, AI walks the ultrasound user through a scan and enhances the image, ensuring the acquisition of high quality and consistent scans that can be easily interpreted. Finally, AI identifies anatomy and anomalies on scans and makes measurements to help the reader interpret the scan. AI serves as a safeguard, ensuring that the radiologist does not miss any areas of concern on a scan, and as a second opinion, improving the radiologist’s confidence in their diagnosis.

Figure 1: AIUS results – Most important AI feature, Source: Omdia

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According to the AIUS, AI for ultrasound is versatile, with 60% of respondents’ practices using AI in multiple clinical applications. AI utilization in general imaging was the most frequently reported clinical application, but Omdia expects AI utilization in point-of-care (POC), cardiology, and nontraditional applications to increase during the next few years as image libraries grow enabling the development of more specialized algorithms. The development of AI at the edge and in POC settings will drive integrated and cloud-based AI deployment in addition to the use of AI with portable medical imaging equipment.

AI enables more efficient and effective diagnostics, which are crucial during the COVID-19 pandemic

As the virus continues to ravage healthcare systems around the world, healthcare providers are employing AI as an important tool to combat COVID-19. AI is being used to quickly screen and triage COVID-19 patients and identify symptoms on scans. This can help healthcare practices to limit the spread of the virus and quickly treat more patients. While many healthcare providers are utilizing preexisting AI, many AI vendors and equipment manufacturers have developed and continue to develop AI software, to aid in the identification and diagnosis of pulmonary and cardiovascular symptoms associated with COVID-19. The benefit and growing understanding of AI for COVID-19 is made clear by the accelerated development of software, increased funding, and easing of regulations.

To become commonplace, the value of healthcare AI must transcend to a broader audience

While in many cases the advantage of using a new technology is anecdotal, the benefit of AI is supported by several metrics tracked by healthcare administrators. According to the AIUS, 85% of respondents reported that AI saved their practice time, 69% reported that the use of AI saved their practice money, 82% cited improved diagnostics as a top driver for AI adoption, 74% of respondents reported that AI increased their practices’ utilization of ultrasound, and 49% reported that AI reduced the amount of training required for a technician to operate an ultrasound. These results are significant because they demonstrate that an overwhelming majority of respondents see measurable improvements following implementation.

Healthcare providers that have employed AI clearly understand the value of AI and this is reflected by usage rates. The AIUS identifies that 73% of respondents’ practices use an AI feature at least once a day, with 40% of respondents reporting hourly usage. This type of buy-in from the medical community is crucial to the widespread implementation of healthcare AI. AI vendors should continue to partner with equipment manufacturers, healthcare providers, and medical schools to identify key AI applications and to facilitate adoption.

Part II of the article focuses on why collaboration is key to the widespread adoption of AI for healthcare

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