The Business Research Company’s report on the AI In Genomics Market provides insights into the global market size, growth rate, regional distribution, competitive landscape, key segments, emerging trends, and strategic opportunities.
What are the primary drivers fueling the growth of the ai in genomics market in recent years?
Growing adoption of AI is expected to propel the growth of the AI in genomics market going forward. Artificial intelligence (AI) is a field that uses computer science and large datasets to solve problems. It includes the subfields of machine learning and deep learning, commonly referenced in the context of artificial intelligence. AI in genomics assists in identifying genetic illnesses and the primary type of cancer, forecasting the progression of certain diseases in a patient, identifying disease-causing genomic variations, and improving the function of gene editing tools. Additionally, due to such benefits, there is an increased demand for artificial intelligence (AI) in genomics. For instance, in May 2022, according to a report published by International Business Machines Corporation (IBM), a US-based technology corporation, the global adoption rate of AI climbed dramatically to 35%, up four percent from the previous year. Furthermore, for instance, in May 2023, according to the report published by the Commonwealth Scientific and Industrial Research Organization (CSIRO), an Australia-based government agency, 68% of businesses in Australia have already adopted artificial intelligence (AI) technologies, while an additional 23% intend to implement them within the next year. Therefore, the growing adoption of AI is driving the growth of the AI in genomics market.
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What is the projected market size of the ai in genomics industry, and how is it expected to grow?
The AI in genomics market size has grown exponentially in recent years. It will grow from $1.06 billion in 2024 to $1.52 billion in 2025 at a compound annual growth rate (CAGR) of 42.8%. The growth in the historic period can be attributed to advancements in genomic sequencing, data handling challenges, personalized medicine demand, disease understanding and diagnosis, drug discovery and development.
The AI in genomics market size is expected to see exponential growth in the next few years. It will grow to $6.64 billion in 2029 at a compound annual growth rate (CAGR) of 44.6%. The growth in the forecast period can be attributed to expansion of genomic databases, enhanced genomic data security, AI-driven biomarker discovery, integration with other ‘omics’ data, patient empowerment and education. Major trends in the forecast period include AI in cancer genomics, AI-enhanced genomic imaging, AI-driven biomarker discovery, genomic data integration across healthcare systems, AI in functional genomics research.
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Who are the key players driving competition in the ai in genomics market?
Major companies operating in the AI in genomics market include International Business Machines Corporation, Microsoft Corp., NVIDIA Corporation, Deep Genomics Inc., BenevolentAI Ltd., Fabric Genomics Inc., Verge Genomic Inc., Freenome Holdings Inc., MolecularMatch Inc., SOPHiA GENETICS SA, Data4Cure Inc., PrecisionLife Ltd., Genoox Ltd., Lifebit Ltd., Empiric Logic Ltd., FDNA Inc., DNAnexus Inc., Engine Biosciences Pte Ltd., 4baseCare, Congenica Ltd., CytoReason Ltd., Emedgene Technologies LTD, Illumina Inc., Lifebit Biotech Ltd., Mendel.ai, Predictive Oncology Inc., Tempus Labs Inc., 10x Genomics Inc., Repositive Limited, Genedata AG, Global Gene Corp, Nference Inc., Bluebee Holding B.V., Genomenon Inc.
What key trends are expected to drive the agriculture and forestry services market during the forecast period?
Technological advancements are a key trend gaining popularity in the AI in genomics market. Major companies operating in the AI in genomics market are focused on developing innovative technological solutions to strengthen their position in the market. For instance, in March 2023, Genomic Vision, a France-based biotechnology company that specializes in the development of diagnostic solutions for genetic diseases and cancers, launched FiberSmart, AI-powered software that enables the visualization and analysis of long DNA fibers at high resolution. It has the potential to completely change the diagnosis and treatment of genetic illnesses. It was introduced to increase the precision and effectiveness of diagnosing and treating genetic diseases. Large amounts of data are analyzed using this technology to find patterns and insights that would be impossible for humans to find on their own.
Which key geographies are driving the growth of the ai in genomics market?
North America was the largest region in the AI in genomics market in 2024. Asia-Pacific is expected to be the fastest-growing region in the AI in the genomics market report during the forecast period. The regions covered in the AI in genomics market report are Asia-Pacific, Western Europe, Eastern Europe, North America, South America, Middle East, Africa
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What are the key segments driving growth in the ai in genomics market?
The AI in genomics market covered in this report is segmented –
1) By Component: Hardware, Software, Services
2) By Technology: Machine Learning, Computer Vision
3) By Functionality: Genome Sequencing, Gene Editing, Other Functionalities
4) By Application: Drug Discovery And Development, Precision Medicine, Diagnostics, Other Applications
5) By End-Use: Pharmaceutical And Biotech Companies, Healthcare Providers, Research Centers, Other End-Users
Subsegments:
1) By Hardware: Servers, Storage Devices, Networking Equipment
2) By Software: Data Analysis Software, Machine Learning Algorithms, Visualization Tools, Genomic Data Management Software
3) By Services: Consulting Services, Integration Services, Support And Maintenance, Data Analytics Services
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What defines the structure and scope of the ai in genomics market?
AI in genomics is a set of computer tools used by genomics researchers to manage and understand any important information concealed in big datasets for DNA sequencing and other biological procedures. These algorithms are capable of detecting human genetic patterns and abnormalities in genomic data.
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