DELRAY BEACH, Fla., Nov. 14, 2025 /PRNewswire/ -- The global AI in Biotechnology Market, valued at US$3.51000 million in 2024, stood at US$4,156.9 million in 2025 and is projected to advance at a resilient CAGR of 18.5% from 2025 to 2030, culminating in a forecasted valuation of US$22,716.5 million by the end of the period. This rapid expansion is fueled by the increasing integration of AI technologies in drug discovery, personalized medicine, and genomics research. Advancements in machine learning algorithms, coupled with the growing availability of big data in the biotech sector, are enhancing predictive accuracy and operational efficiency. Additionally, rising investments from both private and public sectors, along with strategic collaborations between AI and biotech companies, are further propelling market growth. The convergence of AI and biotechnology is transforming healthcare solutions, enabling faster, more cost-effective, and precise interventions. As the technology matures, its adoption across various applications is expected to accelerate, driving innovation across the industry.
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By offering, in 2024, the end-to-end solutions segment accounted for the largest share of the AI in biotechnology market, driven by the rising demand for integrated platforms that combine data management, analytics, and automation across the entire biotechnology workflow. These solutions enable seamless collaboration between research teams, streamline drug discovery, genomics, and precision medicine processes, and improve decision-making through real-time insights. Their ability to support large-scale data integration, predictive modeling, and regulatory compliance makes them particularly attractive to pharmaceutical and biotechnology companies, reinforcing their dominant market position.
By function, in 2024, the manufacturing and supply chain segment accounted for the second-highest CAGR of the AI in biotechnology market, driven by the increasing use of AI to optimize production processes, inventory management, and distribution logistics. AI-powered predictive analytics help minimize downtime, reduce costs, and ensure the timely delivery of biopharmaceuticals. Additionally, the integration of machine learning and automation enhances supply chain transparency, risk management, and operational efficiency, making AI solutions increasingly valuable for pharmaceutical and biotechnology companies aiming to streamline end-to-end manufacturing and distribution workflows.
By geography, in 2024, North America reinforced its position as the leading region in the AI in biotechnology market, driven by the presence of a large number of established biotechnology and pharmaceutical companies, substantial R&D investments, and advanced technological infrastructure. The region's strong focus on precision medicine, drug discovery, and genomics research, coupled with supportive government initiatives and widespread adoption of AI-powered platforms, further accelerates market growth. Additionally, collaborations between AI solution providers and life science organizations enhance innovation and strengthen North America's dominance in the global AI in Biotechnology landscape. The growing availability of high-quality genomic and clinical data, along with skilled AI professionals, further supports the rapid deployment and scalability of AI solutions across the region.
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The key players functioning in the AI in biotechnology market include NVIDIA (US), Illumina, Inc. (US), Recursion (US), Schrödinger, Inc. (US), BenevolentAI (UK), Data4Cure, Inc. (US), Qiagen (Germany), Insilico Medicine (US), DNAnexus, Inc. (US), Tempus (US), SOPHiA GENETIC (Switzerland), Predictive Oncology (US), Deep Genomics (Canada), NuMedii, Inc. (US), XtalPi Inc. (China), Iktos (France), BPGbio, Inc. (US), Eurofins Discovery (US), VeriSIM Life (US), Lifebit (UK), Verge Genomics (US), Logica (US), American Chemical Society (US), and Aganitha AI Inc. (India).
NVIDIA (US):
NVIDIA is a key player in the AI in biotechnology market, providing advanced GPU-accelerated computing and AI platforms that power drug discovery, genomics research, and molecular modeling. Its Clara platform and DGX systems enable researchers to process large-scale biological datasets, run complex simulations, and accelerate machine learning applications in life sciences. By offering scalable AI infrastructure and tools for predictive modeling, Nvidia helps biotech companies enhance research efficiency, reduce experimental costs, and drive innovation in personalized medicine and therapeutic development.
Illumina, Inc (US)
Illumina, Inc. leverages AI-driven genomic sequencing and data analytics to transform biotechnology and precision medicine. Through its NovaSeq and NextSeq sequencing platforms, coupled with advanced bioinformatics solutions, Illumina enables high-throughput analysis of genomic data, variant detection, and biomarker discovery. The integration of AI enhances the interpretation of complex datasets, supports drug target identification, and accelerates clinical research. By combining sequencing technology with AI, Illumina empowers researchers and healthcare providers to advance personalized therapies and improve patient outcomes.
Recursion harnesses artificial intelligence and automation to revolutionize drug discovery and development within the biotechnology sector. By integrating advanced AI models with high-throughput biological experimentation, Recursion's platform generates and analyzes massive datasets to uncover novel drug targets and predict therapeutic efficacy across diverse disease areas. Leveraging advanced machine learning, computer vision, and proprietary biological maps, the company accelerates the identification of promising compounds and optimizes preclinical workflows. Through its data-driven approach and scalable AI infrastructure, Recursion enhances research precision, reduces time and cost in drug development, and drives innovation in developing personalized and effective treatments for complex diseases.
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