by Artificial intelligence (AI) powered diagnostic tools have gained immense significance in healthcare sector owing to their ability to analyze massive patient data and medical images for providing accurate diagnosis. AI diagnostic tools leverage various imaging modalities such as X-Ray, CT, MRI, ultrasound and leverage deep learning and neural networks for image analysis and diagnosis. The incorporation of AI into diagnostic workflows have helped radiologists in reducing diagnosis time, improve efficiency and provide consistent results. AI tools augmented with imaging modalities can detect diseases at an early stage by identifying subtle abnormalities, thereby improving patient outcomes.
The global Artificial Intelligence Diagnostics Market is estimated to be valued at US$ 1731.35 Bn in 2024 and is expected to exhibit a CAGR of 7.9% over the forecast period 2024 to 2031, as highlighted in a new report published by Coherent Market Insights.
Market key trends
One of the key trends in the artificial intelligence diagnostics market is the growing adoption of advanced imaging modalities integrated with AI. Advanced imaging technologies such as digital X-ray, CT, MRI, ultrasound provide high resolution images which when processed through deep learning algorithms can detect minute abnormalities with high accuracy. Further, hybrid imaging technologies which fuse functional and anatomical information such as PET-CT and SPECT-CT are gaining popularity. AI integrated with such hybrid modalities offers synergistic advantages for clinical diagnosis. Another trend is the development of customized AI tools for specific clinical applications and disease areas. Vendors are focusing on developing AI solutions leveraging vast proprietary clinical datasets for applications in oncology, cardiology, neurology and others to provide targeted diagnosis.
Porter’s Analysis
Threat of new entrants: The threat of new entrants is moderate as AI diagnostic technology requires significant investment in R&D. However, entry barriers are reducing over time due to availability of cloud platforms and open source tools.
Bargaining power of buyers: The bargaining power of buyers is high given the availability of substitute diagnostic methods. Buyers can negotiate on price and demand additional services.
Bargaining power of suppliers: Diagnostic tool and AI solution developers hold moderate bargaining power as there are many players in the market producing similar products and services.
Threat of new substitutes: Substitutes include conventional diagnostic methods, imaging, and pathology tests. The threat is moderate as AI diagnostics provides accurate and faster results reducing diagnostic time.
Competitive rivalry: The artificial intelligence diagnostics market is highly competitive with presence of major global players. Companies compete based on technology, services, and pricing.
Key Takeaways
The global Artificial Intelligence Diagnostics Market Growth is estimated to be valued at US$ 1731.35 Bn in 2024 and is expected to exhibit a CAGR of 7.9% over the forecast period 2024 to 2031.
North America dominates the market currently due to availability of funding for research activities and presence of key players in the region. However, Asia Pacific is expected to grow at the fastest pace during the forecast period. North America held the largest share of the artificial intelligence diagnostics market in 2024 and is expected to continue its dominance during the forecast period. This is attributed to increased funding for research activities and presence of key market players in the US and Canada.
Key players: Key players operating in the Artificial Intelligence Diagnostics Market are Zoetis Inc., Merck & Co. Inc., Elanco, Ceva Santé Animale, Boehringer Ingelheim, Biovac, Hester Biosciences Limited, Dechra Pharmaceuticals PLC, Venky€TMs Limited, and Phibro Animal Health Corporation, among others. Zoetis Inc. offers pet health products including vaccines, pharmaceuticals and diagnostics.
*Note:
1. Source: Coherent Market Insights, Public sources, Desk research
2. We have leveraged AI tools to mine information and compile it
