The global AI in omics studies market involves the application of artificial intelligence techniques to analyze large volumes of genomic, proteomic and metabolomic data to better understand diseases. AI algorithms can process huge datasets, identify patterns and relationships, and generate novel insights to accelerate scientific discovery and precision medicine initiatives. It allows automatic detection of anomalies and biologically relevant patterns, classification of samples, prediction of drug responses and more. The widespread availability of cloud-based AI analytics services has made this technology more accessible to researchers.
The Global AI in Omics Studies Market is estimated to be valued at US$ 639.8 Mn in 2024 and is expected to exhibit a CAGR of 32% over the forecast period 2024 To 2031.
Key Takeaways
Key players: Key players operating in the AI in Omics Studies market include Thermo Fisher Scientific, Agilent Technologies, Illumina, BGI Genomics, Dassault Systèmes, Qiagen, Waters Corporation, GE Healthcare, Amazon Web Services, Inc., Bruker, and Danaher. These companies offer integrated workflow solutions, reagents, software and services for AI-driven omics applications.
Growing demand: The increasing volumes of multi-omic datasets and the need for advanced analytics to accelerate insights is driving significant demand for AI technologies in research. Cloud-based solutions are finding more adoption due to their scalability, cost benefits and support for multi-omics data integration.
Global expansion: Leading market players are investing in AI In Omics Studies Market Growth focused acquisitions and partnerships to expand their geographical presence into emerging markets. North America currently dominates however the Asia Pacific market is expected to register fastest growth owing to increasing R&D expenditures and government funding.
Market drivers
Cloud-based analytics services: The wide availability of cloud-based AI platforms for omics data from leading Service providers such as Amazon Web Services, Microsoft Azure, Google Cloud etc has made these technologies highly accessible. The cloud handles huge storage, computing & analytics requirements and enables collaborative research globally. This is a key driver propelling the adoption of AI in omics studies market.
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