Artificial intelligence (AI) in genomics refers to the use of AI technologies such as machine learning and deep learning for analyzing genomic data. Key applications of AI in genomics include precision medicine, drug discovery, agricultural genetics, and clinical diagnostics. Precision medicine utilizes a patient's genomic data to develop customized treatment plans. Pharmaceutical companies leverage AI tools for drug target identification, compound screening, and clinical trial monitoring. In the field of agricultural genomics, AI aids in accelerating the breeding process for developing high-yield and climate-resilient crop varieties. Hospitals deploy AI-powered diagnostics to detect genetic disorders from clinical samples.

The global artificial intelligence (AI) in genomics Market is estimated to be valued at US$ 1.33 Mn in 2024 and is expected to exhibit a CAGR of 6.1%  over the forecast period 2024 to 2030, as highlighted in a new report published by Coherent Market Insights.

Market Dynamics: A key driver responsible for the growth of the AI in genomics market is rising investments in genomic research by both public and private organizations. For instance, in 2021, Genome Canada invested over US$ 85 million in AI and genomics projects focused on precision medicine and industrial biotech applications. Similarly, Genomics England raised funds worth US$ 164 million for its 100,000 Genomes Project that applies advanced analytics to genomic data. AI enhances genomic research capabilities by speeding up sequencing analysis, discovering new molecular targets, and powering clinical trials. Further, growing adoption of multi-omics analysis that integrates genomic, proteomic and phenotypic data also boosts the demand for AI tools. Integration of various datasets facilitates development of personalized treatment regimens and disease risk prediction models with higher accuracy.

SWOT Analysis
Strength: Artificial intelligence (AI) in genomics can analyze huge amounts of genomic data faster and more accurately than humans. It can discover patterns and correlations that humans may miss. It allows researchers to gain insights from genomic data that would be impossible to see without AI. AI is also able to analyze large population-level genomic datasets and clinical datasets in ways that help researchers better understand genetics of diseases.
Weakness: Lack of transparency in how AI arrives at its conclusions can be a limitation. The complexity of AI models often makes it difficult for researchers to understand the factors that influence an algorithm's decisions. Errors or biases in training data used to develop AI systems could propagate inaccurate findings. Regulatory challenges also exist around using AI for clinical decision-making.
Opportunity: AI can help accelerate drug discovery and development by analyzing genomic and other biomedical data to identify novel targets and develop personalized treatment strategies. It also offers potential for improving disease screening, diagnosis and prediction. Growing genomic and clinical datasets provide richer data for training more advanced AI systems. Partnerships between technology and pharma/biotech companies can help develop and apply AI solutions.
Threats: Security and privacy of large genomic and clinical datasets used to train AI systems needs to remain a high priority. Lack of explainability and flaws/biases in AI systems could undermine confidence in research findings. Competing technologies or failure to access required data or talent pools may impede growth potential. High development costs pose barriers for smaller players.

Key Takeaways
The global Artificial Intelligence (AI) In Genomics Market Demand is expected to witness high growth over the forecast period of 2024 to 2030. The market size for 2024 is estimated at US$ 1.33 million and predicted to rise at a CAGR of 6.1%  through 2030.

Regional analysis: North America currently dominates the AI in genomics market driven by significant R&D investments and presence of leading technology and pharma companies. However, Asia Pacific is emerging as the fastest growing regional market with countries like China and India rapidly increasing investments in genomics and AI research. A few leading global companies are also establishing new R&D centers in Asia to tap into the large patient pools and growing biotech industry in the region.

Key players analysis: Key players operating in the artificial intelligence (AI) in genomics market are Thermo Fisher Scientific, F. Hoffmann-La Roche AG, Qiagen N.V, Hologic Inc., Siemens Healthineers AG, BioMerieux SA, Abbott Laboratories, Bio-Rad Laboratories Inc., Becton, Dickinson and Company, and Danaher Corporation (Beckman Coulter, Inc.), among others. These companies are focusing on partnerships, new product launches and acquisitions to strengthen their positions in the AI-driven genomics space.

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