PUBLISHER: MarketsandMarkets | PRODUCT CODE: 2126793
PUBLISHER: MarketsandMarkets | PRODUCT CODE: 2126793
The AI in drug discovery market is anticipated to grow from USD 5.09 billion in 2026 to USD 17.56 billion by 2031, at a CAGR of 28.1% during the forecast period. The market is driven by the increasing adoption of AI to improve R&D productivity, expanding use of multimodal biological datasets, and growing investments in precision medicine and computational drug discovery. According to a 2025 review published in Drug Discovery Today, declining pharmaceutical R&D productivity continues to reshape innovation strategies across the biopharmaceutical industry, prompting companies to increasingly adopt AI-driven platforms to improve research efficiency and accelerate drug discovery.
| Scope of the Report | |
|---|---|
| Years Considered for the Study | 2026-2031 |
| Base Year | 2025 |
| Forecast Period | 2026-2031 |
| Units Considered | Value (USD billion) |
| Segments | Process, Use Case, Therapeutic Area, Player Type, AI Tool, Deployment Model, and End User |
| Regions covered | North America, Europe, Asia Pacific, Latin America, and the Middle East & Africa |
However, challenges related to data quality, model validation, regulatory uncertainty, and integration with existing pharmaceutical R&D workflows continue to influence the pace of market adoption.

Machine learning to be the fastest-growing AI tool segment between 2026 and 2031
By AI tool, the machine learning segment is expected to register the fastest growth during the forecast period as pharmaceutical companies increasingly leverage predictive algorithms to improve decision-making across the drug discovery workflow. Machine learning enables rapid analysis of complex biological, chemical, and clinical datasets, significantly enhancing target identification, hit prioritization, molecular property prediction, and lead optimization. Continuous advancements in deep learning, graph neural networks, and generative AI have further expanded the application of machine learning across small molecule discovery, biologics development, and precision medicine research. Reflecting this trend, in March 2026, NVIDIA expanded its BioNeMo platform with next-generation foundation models and agentic AI capabilities to accelerate biomolecular research and molecular design. As pharmaceutical companies continue to prioritize faster drug development and improved R&D efficiency, machine learning is expected to remain the fastest-growing technology segment in the AI in drug discovery market.
Oncology segment accounted for the largest share of the AI in drug discovery market in 2025
By therapeutic area, the oncology segment accounted for the largest share of the AI in drug discovery market in 2025 due to the high global cancer burden, extensive oncology research pipelines, and increasing demand for precision therapeutics. According to the International Agency for Research on Cancer (IARC), global cancer incidence is projected to increase from 20.6 million new cases in 2024 to 34.4 million by 2050, highlighting the growing need for innovative technologies that can accelerate oncology drug discovery. AI is widely adopted to identify novel therapeutic targets, predict biomarkers, optimize patient stratification, and accelerate the discovery of targeted therapies and immuno-oncology drugs. The availability of large genomic, transcriptomic, proteomic, and clinical datasets has made oncology one of the most data-rich therapeutic areas, enabling AI models to generate more accurate and clinically relevant insights. Pharmaceutical companies continue to prioritize oncology within their R&D portfolios due to its significant commercial potential and the growing demand for personalized cancer therapies. Increasing collaborations between AI companies and oncology-focused biopharmaceutical organizations are further accelerating innovation and reinforcing oncology's leading position in the AI in drug discovery market.
Europe to exhibit the second-highest CAGR during the forecast period
Europe is expected to register the second-highest growth rate during the forecast period, driven by increasing investments in pharmaceutical innovation, expanding adoption of AI across biomedical research, and a strong regulatory framework supporting trustworthy AI. The region is home to leading pharmaceutical companies, research institutions, and AI-native biotechnology firms that are accelerating the integration of AI into target discovery, molecular design, and precision medicine. The implementation of the European Health Data Space (EHDS) and the EU AI Act is expected to facilitate secure cross-border access to health data while establishing harmonized governance for AI applications in life sciences. In parallel, the proposed Cloud and AI Development Act (CADA) aims to strengthen Europe's cloud and AI infrastructure by expanding sovereign computing capacity, improving access to high-performance computing resources, and supporting the development of AI innovation across strategic sectors, including healthcare and life sciences. In addition, collaborative programs such as the Innovative Health Initiative (IHI) continue to fund AI-enabled drug discovery projects, including LIGAND-AI, to accelerate therapeutic research through high-quality biological datasets and advanced AI models. Collectively, these initiatives are expected to reinforce its position as the second-fastest-growing regional market for AI in drug discovery.
Key Players
The key players operating in the AI in drug discovery market include NVIDIA Corporation (US), Schrodinger, Inc. (US), Recursion (US), Insilico Medicine (US), Google (US), Microsoft Corporation (US), Tempus AI, Inc. (US), Illumina, Inc. (US), XtalPi Inc. (China), and Iktos (France). These companies have adopted strategies such as strategic partnerships, collaborations, product launches, platform enhancements, investments in foundation models and generative AI, mergers and acquisitions, and geographic expansion to strengthen their market presence in the market.
Research Coverage
The report analyzes the AI in drug discovery market. It aims to estimate the market size and future growth potential of various market segments based on process, use case, therapeutic area, player type, AI tool, deployment model, end user, and region. The report also analyzes factors such as drivers, restraints, opportunities, and challenges influencing market growth. It evaluates opportunities across the AI-driven drug discovery ecosystem and assesses the competitive landscape for key stakeholders. The report further analyzes micro markets with respect to their growth trends, prospects, and contributions to the overall AI in drug discovery market. It forecasts market revenue across major regions and provides a comprehensive competitive analysis of leading market participants, including their company profiles, product portfolios, recent developments, and key growth strategies.
Reasons to Buy the Report
This report will enrich established firms as well as new entrants/smaller firms to gauge the pulse of the market, which, in turn, would help them garner a greater share of the market. Firms purchasing the report could use one or a combination of the following strategies to strengthen their positions in the market.