PUBLISHER: Coherent Market Insights | PRODUCT CODE: 1705930
PUBLISHER: Coherent Market Insights | PRODUCT CODE: 1705930
Global Artificial Intelligence (AI) in Biotechnology Market is estimated to be valued at USD 2.50 Bn in 2025 and is expected to reach USD 8.56 Bn by 2032, growing at a compound annual growth rate (CAGR) of 19.2% from 2025 to 2032.
Report Coverage | Report Details | ||
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Base Year: | 2024 | Market Size in 2025: | USD 2.50 Bn |
Historical Data for: | 2020 To 2024 | Forecast Period: | 2025 To 2032 |
Forecast Period 2025 to 2032 CAGR: | 19.20% | 2032 Value Projection: | USD 8.56 Bn |
The field of biotechnology has witnessed rapid advancements due to technological developments in various domains including artificial intelligence and machine learning. AI is being increasingly used in biotechnology for applications ranging from drug discovery and genome analysis to clinical trial monitoring and precision medicine. AI tools help researchers to process huge volumes of genomic and proteomic data and gain novel insights into disease mechanisms. Several AI-powered techniques like deep learning, neural networks, natural language processing, and others assist in critical functions like target identification, lead optimization, toxicity prediction and biomarker discovery, thus, significantly accelerating the drug development process. AI help biotech companies in monitoring and managing clinical trials more efficiently. It also has promising applications in personalized medicine by supporting treatment recommendations tailored to individual patients' genetic profile and medical history. Global AI in biotechnology market growth is driven by rising adoption of these technologies in pharma/biotech industry and healthcare.
Market Dynamic:
Global AI in biotechnology market growth is driven by factors like increasing funding for AI startups developing solutions for healthcare and life sciences, growing volumes of complex biological and patient-generated healthcare data requiring sophisticated analysis, and rising need to enhance R&D productivity and reduce costs in drug discovery. However, factors like lack of skilled workforce, data quality issues, security and regulatory concerns related to AI and big data can hamper its adoption. Expanding applications of predictive analytics, machine learning and artificial intelligence in precision medicine, personalized therapeutics, gene therapies and diagnostics can offer market growth opportunities.
Detailed Segmentation-