The global artificial intelligence in diagnostics market size was valued at USD 910.69 million in 2022. It is estimated to reach USD 11,308.68 million by 2031, growing at a CAGR of 32.30% during the forecast period (2023–2031).
Medical diagnostics is the process of determining whether a patient is sick or ill by reviewing their symptoms, past health, and test findings. Medical diagnostics aims to establish the root cause of a medical issue and offer accurate diagnostics to give appropriate therapy. This may entail different diagnostics techniques, including imaging tests (X-rays, MRIs, and CT scans), blood tests, and biopsy procedures. The results of these tests help doctors select the best suitable course of treatment for their patients.
The field of medical diagnostics could be revolutionized by increasing the diagnostics process's predictability, speed, and efficiency thanks to the current AI revolution. Medical imaging data, including X-rays, MRIs, ultrasounds, CT scans, and DXAs, can be analyzed by AI algorithms to help doctors discover and diagnose diseases more precisely and rapidly. This can assist healthcare professionals in making better judgments regarding patient care. Additionally, AI-powered Clinical Decision Support Systems (CDSSs) could offer in-the-moment help and assistance to make better judgments on patient care.
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Due to the increasing digitization and use of information technology within the healthcare business, big data (large and complicated data) is produced at many stages of the care delivery process. Big data in medical diagnostics include the information generated from clickstream and web and social media interactions, readings from medical devices like sensors, ECGs, X-rays, and other billing records, and biometric data. The acceptance of electronic health records (EHRs), digitalized laboratory slides, and high-resolution radiological pictures among healthcare professionals has increased over the past years. As a result, big data and analytical solutions have gotten exponentially more complex and popular.
Additionally, it is projected that the adoption of bidirectional patient portals, which allow patients to upload data and photographs to their EMRS, would increase the volume of big data in medical diagnostics over the forecast period. The healthcare sector is turning to various Al-based solutions to effectively manage the ever-growing number of massive and complex medical diagnostics data.
High-resolution medical imaging, molecular imaging, and wearable devices provide a wealth of data for AI systems. Artificial intelligence can aid in the interpretation of medical imaging, the detection of small anomalies, and the diagnostics of serious ailments like cancer, cardiovascular disease, and neurological disease. These technological developments are pushing for the widespread adoption of AI in diagnostics settings. Combined with AI algorithms' analytical capability, their ability to acquire precise data increases diagnostics accuracy, boosts patient outcomes, and advances precision medicine.
The market for AI-based healthcare involves high procurement costs, significant initial capital requirements, and expenditures for maintenance and upgrade. Hospitals and other established financial players are significant market investors. Most costs associated with creating and adopting AI-based products are covered directly by private consumers due to poor government spending on these activities. The European Union, for instance, has not yet adopted long-term investment-intensive strategies for AI-based healthcare solutions. Due to the intricate engineering of the system, purchasing hardware and software solutions to integrate AI into the healthcare context entails significant expenses.
Additionally, an AI-based system's typical repair or maintenance can be expensive. These systems require ongoing improvements to stay current with evolving scenarios, including such expenses. In addition, significant financial commitments are needed for training initiatives and digitalization. Adopting electronic health record systems and the potentially costly process of acquiring and integrating AI technology into healthcare settings have already required large capital commitments from healthcare systems.
Large volumes of patient data, like medical records, imaging scans, test results, and genetic data, can be analyzed by AI algorithms. AI can dramatically increase diagnostics accuracy by seeing tiny patterns, anomalies, or correlations that may be challenging for human observers to notice. By enabling earlier and more precise diagnostics, this potential lowers the possibility of missing or delayed diagnoses and enhances patient outcomes. In addition, AI in diagnostics can improve healthcare workflows by automating repetitive operations and lightening the load on healthcare personnel.
Furthermore, AI algorithms can effectively process and analyze pathology slides, diagnostics data, and medical images, enabling quicker and more accurate interpretation. Healthcare practitioners can concentrate their knowledge on challenging patients by automating routine processes, improving efficiency, and decreasing response times. Likewise, AI algorithms can continuously learn from feedback and new data inputs. This chance enables continuous advancement in diagnostics precision and effectiveness over time. AI systems can also update and improve their algorithms to improve performance and keep up with changing medical knowledge by utilizing user feedback and real-world data. Such factors are expected to create opportunities for market growth over the forecast period.
| Study Period | 2019-2031 | CAGR | 32.30% |
| Historical Period | 2019-2021 | Forecast Period | 2023-2031 |
| Base Year | 2022 | Base Year Market Size | USD 910.69 Million |
| Forecast Year | 2031 | Forecast Year Market Size | USD 11308.68 Million |
| Largest Market | North America | Fastest Growing Market | Europe |
Based on region, the global artificial intelligence in diagnostics market is bifurcated into North America, Europe, Asia-Pacific, Latin America, and the Middle East and Africa.
North America is the most significant global artificial intelligence in diagnostics market shareholder and is estimated to exhibit a CAGR of 32.5% over the forecast period. The presence of a well-established healthcare IT infrastructure, ongoing technological improvements, rising digital literacy, the creation of startups, supportive government initiatives, expanding funding opportunities, and significant players in the region were all credited with this expansion. In addition, the use of AI in diagnostics is accelerating due to the growing need for lowering testing costs, enhancing patient care, and decreasing machine downtime. According to Health IT Analytics, Case Western Reserve University researchers used a deep learning network, a type of AI, in May 2017 to correctly identify breast cancer in pathology photographs.
Europe is estimated to exhibit a CAGR of 32.2% over the forecast period. Due to several important reasons, including rising expenses, an aging population, rising prevalence of chronic illnesses, rising treatment demand, and a stagnant or declining healthcare workforce, the sustainability of the European healthcare sector is in danger. Additionally, structural inefficiencies in some European nations are a problem for the sector. The shift to value-based healthcare is anticipated to increase the need for improved patient outcomes at a more manageable price. In addition, AI integration into cutting-edge medical technologies can solve urgent healthcare problems.
Furthermore, many healthcare AI applications are in use or being deployed. These applications can help detect diseases early, improve diagnostics, discover new human physiology patterns, and create personalized diagnoses and treatments. For instance, in 2018, the GDPR created requirements for collecting, processing and securing personal data in healthcare organizations. This rule covers genetic, biometric, and health-related data. Similarly, in April 2019, the EU issued healthcare recommendations on moral AI for enterprises and governments. Privacy and Data Governance, Transparency, Technical Robustness and Safety, Non-discrimination, Diversity and Fairness, Accountability, Human Agency and Oversight, and Environmental and Societal well-being are the seven AI requirements. Such factors are anticipated to propel market growth over the forecast period.
Asia-Pacific is anticipated to register significant growth over the forecast period. AI-based diagnostics solutions are growing due to public and private initiatives. Startups, visibility, and investment boost regional industry growth. Private finance and startup incubators also affect regional market growth. Acute and chronic illnesses and an aging population are expected to boost market growth. In addition, the growing patient pool, pandemic, cloud computing, and government AI programs are expected to drive the Asia-Pacific market. AI is also used in diagnostics and by biopharmaceutical companies to modernize medication research. For instance, in 2017, Tencent launched AI Medical Innovation System (AIMIS), an AI-driven diagnostics medical imaging facility. The first lung and esophageal cancer diagnoses were 90% and 95% accurate, respectively.
Latin America is expected to be a potentially lucrative location for AI in the diagnostics industry due to politics, a shortage of skilled labor, and the government's openness to embracing current technologies. The International Development Research Centre (IDRC) and Oxford Insights evaluated the governments of 194 countries about their readiness to deploy AI, and Uruguay, Mexico, and Brazil were among the top 50. The regional market is expected to be driven by the expanding breadth of digitalization, the growth of IT infrastructure, technological improvements to improve patient care quality, and lower healthcare costs. For instance, Brazilian Minister Marcos Pontes launched eight AI laboratories in 2019, focusing on partnerships with funding and research support organizations. Industry 4.0, smart cities, health, and agribusiness were the focus areas for four of the eight laboratories.
In the Middle East and Africa (MEA), the demand for advanced healthcare facilities is anticipated to rise due to rising chronic illnesses like respiratory conditions, heart diseases, and an aging population. Chronic conditions like obesity, cardiovascular disease, and diabetes are becoming more common. This is due to several reasons, including sedentary lifestyles, hypertension, bad eating habits, physical inactivity, and inadequate sleep. The regional market is expanding quickly due to cooperation between the government, business stakeholders, and other investors in the healthcare ecosystem. For instance, Nigeria created a system called Apmis that enables healthcare experts, hospital owners, patients, and caregivers to share and exchange healthcare records. It makes data exchange visible, simple, safe, and affordable possible.
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The global artificial intelligence in diagnostics market is bifurcated into components and diagnostics type.
Based on components, the global artificial intelligence in diagnostics market is bifurcated into hardware, software, and services.
The software segment dominates the global market and is projected to exhibit a CAGR of 33.5% over the forecast period. One of the main forces pushing the sector forward is the rising need for AI-powered and cloud-based augmented diagnostics solutions, which aid in providing more diagnostics precision when evaluating medical images of a patient. Additionally, the ongoing pandemic of COVID-19 and the introduction of cutting-edge AI software in diagnostics involving multiple data sources, such as genomics and proteomics, MRI, CT, and patient data, are expected to drive the market.
For instance, in February of 2018, John Snow Labs released their Natural Language Processing (NLP) package, which included deep learning models tailored to the healthcare industry. Programmers may use these models to build software that can comprehend medical documents. This has contributed to the expansion of AI software in healthcare by assisting professionals in analyzing and identifying high-risk patients, matching patients to clinical trials, alerting caregivers about patient safety, automating clinical coding and billing, and making significant clinical recommendations.
Based on diagnostics type, the global artificial intelligence in diagnostics market is segmented into cardiology, oncology, pathology, radiology, chest and lungs, and neurology.
The neurology segment owns the highest market share and is expected to grow at a CAGR of 31.4% during the forecast period. Growing older populations and rising rates of certain neurological conditions, including epilepsy, Alzheimer's disease, and Parkinson's disease, are boosting the need for accurate diagnoses and favorably affecting market expansion. According to the United Nations World Ageing Population 2017 study, there will be 2.1 billion individuals over 60 on the planet by the year 2050, double the 962 million there were in 2017.
Additionally, the use of value-based care is accelerating the segment's growth, a developing trend in managing the burden of neurological disorders. The development of sophisticated deep neural networks and cutting-edge algorithms trained on many image datasets acquired for various assessments and diagnoses are among the drivers driving this market's expansion. In addition, AI-based diagnostics options in neurology increase precision and accuracy as well as the productivity and clinical judgment of the radiologist. The widespread usage of AI-enabled solutions has aided the improvement of neurological departments.
