The state of AI diagnostics in health care: projected 24.6% CAGR through 2030

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In recent years, the global health care industry has begun a trend of rapidly implementing artificial intelligence (AI)-powered solutions to achieve better health outcomes and alleviate some of the burden from clinicians. In 2023, the AI in diagnostics market size was valued at $1.2 billion, and is projected to grow to $5.4 billion, at a compound annual growth rate (CAGR) of 24.60%, through 2030, according to a market report from Grand View Research.

The report attributes the growth of AI diagnostics to advancements in information technology (IT) infrastructure, in addition to technological advancements in cloud storage, computer processing and machine learning (ML) algorithms, particularly in North America, which dominated the global market, accounting for the largest revenue share of more than 56%.

AI diagnostics offer automated and innovative solutions to overburdened health care systems struggling with staffing shortages, aging populations and a rising prevalence of chronic diseases.

“The ongoing COVID-19 pandemic exposed the shortcomings of the existing health care system and accelerated the adoption of digital technologies, such as AI in diagnostics, to accurately analyze complex datasets, thereby reducing the burden of administrative and operational tasks on clinicians,” the authors of the report wrote.

Key players and emerging startups

The report highlights the emergence of startups and their growing financial recognition, in the form of funding and investments, as keys that kickstarted market growth. “Health care startups rapidly began adopting AI-powered systems and receive recognition in [the] form of funding and investments, [which] boosted the market growth.”

The report provided cases in which companies received funding, including Arterys, a medical imaging AI platform for radiology, and Aidoc, a company that develops computer-aided triage systems. Other key players in the health care market have shifted their focus toward developing AI-backed diagnostics products. GE Healthcare’s Thoracic Care Suite, for example, used AI-diagnostics to detect chest anomalies, and Alivecor has received approval from the U.S. Food and Drug Administration (FDA) for their AI-based technology used for advanced electrocardiogram (ECG) diagnostics.

Additional key players in the global AI diagnostics market, as detailed in the report, include Siemens Healthineers, Zebra Medical Vision, Inc., Riverain Technologies, Vuno, Inc., Neural Analytics, Imagen Technologies and Digital Diagnostics, Inc.

Key components

The AI in diagnostics market is segmented into hardware, software and services. As of 2022, the software component segment accounted for the largest revenue share—more than 45% of the market. This trend is expected to continue, as the software segment is estimated to record the fastest CAGR of 25.7% through 2030. Advances in health care infrastructure, and AI’s implementation into electronic health records (EHRs), are notable contributors.

In addition, the report attributes the growth to an increased demand for early and accurate diagnostics, especially as acute and chronic diseases become increasingly common and health care providers face additional burdens, leaving them susceptible to burnout.

Diagnosis type

AI diagnostics are available in cardiology, oncology, pathology, radiology, chest and lung and neurology, among others. In 2022, the neurology diagnostics segment accounted for the largest revenue share—approximately 24.4% of the market. The report credits the growing incidence of neurological disorders and value-based care (VBC) for the segment’s growth.

However, the report projects radiology, not neurology, to register the fastest growth rate of 27.3% through 2030 because of the growing demand for low-cost, precise and accurate radiology analysis.

“The growing demand for early diagnosis and classification of disorders is expected to boost the segment growth,” the authors explained. “AI-enabled solutions can be integrated with EHRs and radiological findings to diagnose diseases in the early stages so that appropriate treatments could be provided to the patient. The shortage of radiologists across the globe is driving the demand for AI-based solutions in radiology.”

Most chronic conditions are preventable if detected early enough, underscoring the demand for AI-based diagnostics across health care segments. AI technology can alleviate some of the burden from clinicians, creating a path to better health outcomes. “Health care professionals can provide a preventive and proactive care approach instead of a reactive approach by using these advanced diagnostic solutions,” the authors wrote.