By Kevin Xu (CC’26, Analyst 2022–23)
The explosive growth of artificial intelligence may soon revolutionize the medical diagnostics industry. As algorithms improve and more people are living to the age where the risk of cancer and chronic illnesses rise, detecting diseases quickly and accurately has become a key focus of innovation and investment. As a result, the AI diagnostics market, valued at $576.3 million in 2021, is projected to grow to $5.5 billion by 2030, with a CAGR of 26.3%.
The use of AI in medical diagnostics has several different applications such as diagnosing various diseases and the prioritization of patients based on biometric data. For example, AI can be used to predict the probability of disease onset in chronic patients or make decisions about the triaging of patients in the ER. Another use case for AI algorithms is in image processing, whether that is creating 3D models from CAT scans or screening ultrasounds, CT scans, or X-rays for patterns of disease. Applications of AI diagnostics span numerous fields in medicine but are especially impactful in neurology, cardiology, and oncology.
There are many reasons for such a high market growth rate. First of all is the increase in digital health data. As more hospitals begin to implement electronic health records and as wearable health trackers grow in popularity, there is far more biometric data for algorithms to work with in order to predict the health outcomes of patients. Furthermore, improvements in computer vision and machine learning will also allow algorithms to identify patterns of cancer or other diseases with greater accuracy.
These opportunities have led many major tech and healthtech companies to shift their focus towards AI diagnostics in recent years. Siemens Helathineers, Google, and Nvidia have all begun developing products for the market. However, the ecosystem has witnessed many innovative founders with unique edges and business models. Some startups, such as Aidoc, an Israeli firm valued at $686.42 million, operates with a SaaS model and licenses its 12 FDA approved programs to hospitals and specialists. They have analyzing over 17 million scans since their inception in 2016. Other firms, such as Path AI (A US-based company valued at $1.02 billion), and Owkin, (a French startup valued at $1.32 billion), have applied AI algorithms to other sectors within healthcare, too. These firms integrate the use of AI across various sectors in healthcare such as drug discovery, patient risk assessment, as well as workflow and data management.
While the market has witnessed lots of startup growth, there has also been lots of M&A activity. For example, Zebra Medical Vision, Inc., an imaging and diagnostics company, was recently acquired by Nanox in a deal valued at up to $200 million. Similarly StoCastic, with its ER triaging solutions, was acquired by Beckman Coulter last year for an undisclosed amount.
Despite the thriving business ecosystem, however, there are still some industry headwinds. First of all, patient privacy is a concern to many consumers and legislators. The regulatory environment is not yet clear on how much patient data private companies are allowed to access for their diagnoses or whether crytographic methods are able to overcome that challenge. Furthermore, concerns remain on the accountability of AI algorithms to ensure not only accuracy but also fairness in their diagnoses. Given all this, it may be challenging, espeically for smaller firms, to gain access to the training datasets that will allow their algorithms to reach proficiency in their diagnoses.
Nonetheless, the AI diagnostics industry is positioned to become yet another successful instance of the implementation of artificial intelligence to improve the efficiency and the quality of services provided to both healthcare providers and patients. A future of AI-guided diagnoses and treatment recommendations may come sooner than we expect.