AI in Drug Discovery Market Report 2026

The artificial intelligence (AI) in drug discovery market size has grown exponentially in recent years. It will grow from $2.33 billion in 2025 to $2.93 billion in 2026 at a compound annual growth rate (CAGR) of 25.9%. The growth in the historic period can be attributed to increasing pharmaceutical R&D spending, growing complexity of drug discovery pipelines, rising availability of biological and chemical datasets, early adoption of machine learning in bioinformatics, increasing collaboration between pharma and tech firms.

The artificial intelligence (AI) in drug discovery market size is expected to see exponential growth in the next few years. It will grow to $7.42 billion in 2030 at a compound annual growth rate (CAGR) of 26.2%. The growth in the forecast period can be attributed to increasing adoption of generative ai models, rising demand for precision therapeutics, expansion of ai-enabled clinical trial design, growing investments in cloud-based discovery platforms, regulatory acceptance of ai-assisted drug development. Major trends in the forecast period include increasing use of AI-driven target identification, rising adoption of deep learning for molecule screening, growing integration of virtual drug screening platforms, expansion of AI-based lead optimization tools, enhanced focus on reducing drug development timelines.

The increasing demand for personalized medicine is expected to drive the growth of artificial intelligence (AI) in the drug discovery market going forward. Personalized medicine involves a targeted approach to disease prevention, diagnosis, and treatment that utilizes an individual’s genetic, proteomic, or biological profile to inform clinical decisions. The rising adoption of personalized medicine is fueled by the growing need for precise, patient-specific therapies that enhance treatment effectiveness and minimize adverse effects. AI facilitates this transition by speeding up the identification of molecular targets, optimizing drug candidates, and improving clinical decision-making across the development pipeline. For example, in February 2024, according to the Personalized Medicine Coalition, a US-based advocacy and research organization, the U.S. FDA approved 26 new personalized treatments in 2023, including 20 new molecular entities and 6 gene- or cell-based therapies. Consequently, the increasing demand for personalized medicine is driving the growth of artificial intelligence (AI) in the drug discovery market.

Major companies are investing in firms operating in artificial intelligence (AI) within the drug discovery market to identify and develop new therapies and provide those models to other pharmaceutical companies. Strategic investments can offer funding for research and development of new drugs, a process that is often costly and time-consuming. This funding can enable companies to advance their drug discovery programs and bring new treatments to the market. For example, in July 2023, Nvidia, a US-based software company, invested $50 million in Recursion Pharmaceuticals, a US-based biotech firm that leverages artificial intelligence (AI) for drug discovery. The investment will support Recursion in accelerating the development of its AI foundation models for biology and chemistry through the use of Nvidia's cloud services.

In November 2025, Merck KGaA, a Germany-based provider of pharmaceuticals and life-science tools, formed a partnership with Valo Health to accelerate neurology innovation through AI-driven drug discovery. The collaboration seeks to advance Merck KGaA’s neurology pipeline by leveraging Valo Health’s AI platform to quickly identify novel targets and develop preclinical candidates for Parkinson’s and related disorders. Valo Health is a US-based company offering AI-driven drug discovery solutions using large-scale human data, machine-learning platforms, and automated chemistry to generate preclinical small-molecule candidates.

Major companies operating in the artificial intelligence (AI) in drug discovery market are Exscientia, Insilico Medicine, Owkin Inc., XtalPi Inc., Standigm Inc., Innoplexus AG, Atomwise, Inc., BenevolentAI, Deep Genomics Inc., NuMedii, Inc., Verge Genomics, Inc., Berg LLC, Cyclica Inc., Iktos, Quris, Adagene Inc., Gero Pte. Ltd., IBM Corporation, Microsoft Corporation, NVIDIA Corporation, Alphabet Inc., DeepMind Technologies Limited, IQVIA Holdings Inc., GNS Healthcare, Inc., GE HealthCare Technologies Inc., Novartis AG, Pfizer Inc., F. Hoffmann-La Roche Ltd., Merck & Co., Inc., AbbVie Inc., AstraZeneca PLC, Amgen Inc., GlaxoSmithKline plc, Johnson & Johnson, Takeda Pharmaceutical Company Limited, Ipsen S.A., Galderma S.A.

North America was the largest region in the artificial intelligence (AI) in drug discovery market in 2025. Western Europe was the second largest region in the global artificial intelligence (AI) in drug discovery market share. The regions covered in the artificial intelligence (AI) in drug discovery market report are Asia-Pacific, South East Asia, Western Europe, Eastern Europe, North America, South America, Middle East, Africa. The countries covered in the artificial intelligence (AI) in drug discovery market report are Australia, Brazil, China, France, Germany, India, Indonesia, Japan, Taiwan, Russia, South Korea, UK, USA, Canada, Italy, Spain.

Tariffs are impacting the artificial intelligence in drug discovery market by increasing costs of imported high-performance computing hardware, specialized processors, data storage systems, and advanced laboratory equipment required for AI-driven research workflows. Pharmaceutical and biopharmaceutical companies in North America and Europe are most affected due to reliance on imported computing infrastructure, while Asia-Pacific faces cost pressures on AI hardware procurement. These tariffs are increasing operational expenditures and slowing infrastructure upgrades. However, they are also encouraging domestic production of computing hardware, localized data center investments, and long-term development of cost-efficient AI research platforms.

The artificial intelligence (AI) in drug discovery market research report is one of a series of new reports that provides artificial intelligence (AI) in drug discovery market statistics, including artificial intelligence (AI) in drug discovery industry global market size, regional shares, competitors with a artificial intelligence (AI) in drug discovery market share, detailed artificial intelligence (AI) in drug discovery market segments, market trends and opportunities, and any further data you may need to thrive in the artificial intelligence (AI) in drug discovery industry. This artificial intelligence (AI) in drug discovery market research report delivers a complete perspective of everything you need, with an in-depth analysis of the current and future scenario of the industry.

Artificial Intelligence (AI) in drug discovery involves using machine learning algorithms and data-driven models to speed up and enhance the process of discovering and developing new drugs. AI can process large datasets to predict drug-target interactions, refine molecular structures, and identify potential drug candidates more efficiently than conventional methods.

The primary technologies in AI for drug discovery are deep learning and machine learning. Deep learning is a branch of machine learning and AI that simulates the way humans learn and acquire knowledge. Data science, encompassing statistics and predictive modeling, incorporates deep learning as a crucial element. The various drug types include small molecules and large molecules and cover multiple types of therapies. AI is applied across several end-users, including pharmaceutical companies, biopharmaceutical companies, academic and research institutions, and others.

The artificial intelligence (AI) in drug discovery market includes revenues earned by entities by offering AI for drug discovery. Artificial Intelligence (AI) for drug discovery is a technology that uses a simulation of the human intelligence process by machines to tackle complex problems in the drug discovery process. It helps to find new molecules to identify drug targets and develop personalized medicines in the pharmaceutical industry. Values in this market are factory gate values, that is the value of goods sold by the manufacturers or creators of the goods, whether to other entities (including downstream manufacturers, wholesalers, distributors and retailers) or directly to end customers. The value of goods in this market includes related services sold by the creators of the goods.

The market value is defined as the revenues that enterprises gain from the sale of goods and/or services within the specified market and geography through sales, grants, or donations in terms of the currency (in USD unless otherwise specified).

The revenues for a specified geography are consumption values that are revenues generated by organizations in the specified geography within the market, irrespective of where they are produced. It does not include revenues from resales along the supply chain, either further along the supply chain or as part of other products.

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