Artificial Intelligence for Drug Discovery and Development Market Size & Outlook, 2026-2034

Artificial Intelligence for Drug Discovery and Development Market Overview

The artificial intelligence for drug discovery and development market size is valued at USD 2.40 billion in 2025 and is estimated to reach USD 25.35 billion by 2034, growing at a CAGR of 29.9% during the forecast period. The artificial intelligence market in drug discovery is poised for significant growth, driven by increasing research and development initiatives aimed at developing novel AI models with enhanced interpretability and minimal bias. Thus, the growing demand for efficient drug discovery, combined with advancements in AI technologies and pharmaceutical innovation, is driving growth in the AI-driven drug discovery market.

Key Market Trends & Insights

• North America's artificial intelligence in the drug discovery market held the largest market share of 60.7% in 2025.
• The Asia-Pacific region is expected to witness the highest growth rate of 32.4% during the forecast period.
• Based on application, the drug optimisation and repurposing segment accounted for the highest market share of 55.7% in 2025.
• Based on therapeutic area, the oncology segment held the largest revenue share of 25.4% in 2025.
• Based on end-use, the pharmaceutical and biotechnology companies segment dominated the market in 2025 with a market share of 54.2%.
• The U.S. Artificial Intelligence in Drug Discovery Market held the largest market share in 2025

Market Revenue Figures

• 2025 Market Size: USD 2.40 billion
• 2034 Projected Market Size: USD 25.35 billion
• CAGR (2026-2034): 29.9%
• Dominating Region: North America
• Fastest-Growing Region: Asia Pacific

Artificial intelligence is transforming drug discovery by reducing the time, cost, and complexity of developing new therapies. AI accelerates hit identification, target validation, and molecule optimisation, enabling faster progress from research to clinical development. Pharmaceutical companies are increasingly relying on AI to analyse genetic, molecular, and clinical datasets to uncover disease-drug relationships and design more effective candidates. The rising prevalence of chronic diseases is driving the demand for efficient treatment development, prompting manufacturers to adopt innovative, cost-effective research and development models.

Latest Market Trends

AI-Driven Innovations Revolutionising Drug Discovery

A major trend in the market is the rapid adoption of machine learning and deep learning to streamline the drug discovery process. AI tools analyse large datasets, predict molecular interactions, and identify promising drug candidates with far greater speed and accuracy than traditional methods. These technologies also support smarter clinical trial design by forecasting success rates and pinpointing ideal patient groups.

As a result, AI is significantly reducing development risks and timelines. This growing integration of algorithm-based insights is reshaping pharmaceutical R&D, fueling innovation, and enabling companies to address unmet medical needs more efficiently, ultimately driving the strong uptake of AI-driven drug discovery solutions.

Strategic Collaborations Between Big Pharma and Specialised AI Drug-Discovery Companies

Pharmaceutical companies are increasingly forming long-term partnerships with AI-focused drug discovery firms to accelerate research and development (R&D) and reduce costs. Through these collaborations, the pharmaceutical industry gains access to advanced generative AI models, machine learning platforms, and computational chemistry tools that enable the rapid design of molecules, identification of new targets, and prediction of therapeutic outcomes. Meanwhile, AI companies benefit from pharma’s proprietary datasets and clinical expertise. These alliances are expanding across key therapeutic areas, including oncology, neurology, immunology, and rare diseases.

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Market Driver

Rising R&D Investments in the Pharmaceutical Industry

Growing R&D spending in the pharmaceutical industry is boosting the adoption of AI across drug development workflows. Companies are integrating AI to accelerate early-stage candidate screening, improve target discovery, and enhance decision-making accuracy. High-throughput AI tools efficiently filter large chemical libraries, identifying the most promising compounds for further research and development.

Additionally, AI’s ability to analyse genomic datasets, clinical trial results, and patient demographics helps uncover new biological insights. AI-driven improvements in trial design and patient recruitment also reduce operational inefficiencies and shorten development timelines. Collectively, these capabilities strengthen pipeline productivity and support sustained investment in AI-enabled R&D solutions.

Market Restraint

High Initial Investment Costs

Implementing AI in drug discovery requires significant upfront investment in high-performance computing infrastructure, secure data storage, and advanced analytical software. Recruiting skilled professionals, including data scientists, AI engineers, and biotech researchers, further increases operational costs. Integrating AI into existing legacy R&D systems requires additional investment in workflow redesign, training, and system optimisation. Ongoing maintenance, algorithm updates, and hardware upgrades add to long-term financial commitments. These economic barriers can limit the adoption of AI-driven solutions.

Market Opportunity

Enhanced Predictive Modelling for Clinical Trials

AI offers significant opportunities to enhance clinical trial efficiency through advanced predictive modelling. Algorithms help optimise trial design by determining ideal sample sizes, endpoints, and treatment parameters, improving trial robustness. By analysing electronic health records and patient data, AI supports precise participant selection, accelerating recruitment and improving cohort quality. Predictive tools also forecast trial success and identify when protocol adjustments may be required. AI-driven monitoring can detect participants at risk of dropout and suggest interventions to retain them. These capabilities streamline trial execution, reduce delays, and substantially lower operational costs, positioning AI as a key enabler of next-generation clinical research.

Regional Analysis

North America dominated the artificial intelligence in drug discovery market in 2025, accounting for a 60.7% share, fueled by substantial investments in healthcare technology and robust partnerships between pharmaceutical firms and technology leaders. The presence of world-class research institutions, combined with a supportive regulatory framework, further promotes innovation in the region. Companies are increasingly leveraging AI to enhance efficiency across drug discovery workflows, reduce R&D costs, and accelerate the launch of new therapies.

• The U.S. held the largest market share in 2025. The U.S. stands out as a global hub for AI in drug discovery, with major pharmaceutical companies and tech firms investing heavily in AI technologies. The U.S. market is characterised by a high level of M&A activity, with companies seeking to integrate AI capabilities to gain a competitive edge in drug development.

Asia Pacific Market Insights

The Asia Pacific artificial intelligence in drug discovery market is expected to record the fastest CAGR of 32.4% by 2034, driven by strong technological adoption across major economies, including China, India, Japan, and South Korea. Regional pharmaceutical and biotech companies are rapidly integrating AI to accelerate target identification, molecule design, and clinical trial optimisation. Governments are also investing heavily in AI research, digital health infrastructure, and precision medicine initiatives, creating a supportive innovation ecosystem. Increasing collaborations among global pharmaceutical companies, academic institutions, and AI startups continue to strengthen market growth.

• China’s artificial intelligence in the drug discovery market is at the forefront of AI adoption in the Asia-Pacific region, with significant investments in healthcare AI and biotechnology. Many pharmaceutical firms in China are increasingly partnering with AI-driven companies, aiming to accelerate drug development efforts. These collaborations are seen as pivotal to enhancing China's pharmaceutical industry, which has faced slower growth rates.

Europe Market Insights

Europe is leading the way in leveraging AI in drug discovery, thanks to its robust biopharma ecosystem and government-backed initiatives that facilitate innovative research. Countries including Germany, the U.K., and France, among others, are employing AI for molecular modelling, predicting disease, and finding biomarkers. Regulatory frameworks that support innovation and collaborative research across borders, funded by the EU, are also aiding market penetration. The European focus on responsible AI use and digital therapeutics is also providing benefits for pharmaceutical and biotech companies to adopt AI.

• The United Kingdom is the leading country in the artificial intelligence in drug discovery market. The UK’s leadership is supported by its strong pharmaceutical and biotechnology sector, world-renowned research institutions, advanced AI and computational biology expertise, and supportive government policies promoting digital health and AI innovation.

Latin America Market Insights

In Latin America, the AI in Drug Discovery Market is generating momentum, especially as the region's governments move towards implementing digital transformation in healthcare. Latin American countries, including Brazil, Mexico, and Argentina, have been utilising AI-based technologies to enhance the efficiency of clinical research while also addressing patient needs. Increased partnerships between universities, biotechnology companies and international AI solution providers is also supporting growth.

• Brazil is the largest market in Latin America, driven by its relatively advanced pharmaceutical and biotechnology sector, growing investments in AI and digital health technologies, and supportive government initiatives to promote innovation in life sciences. The country is increasingly leveraging AI to streamline drug discovery processes, enhance clinical trial efficiency, and address unmet medical needs, making it the primary hub for AI-driven pharmaceutical research in the region.

Middle East and Africa Market Insights

The Middle East and Africa region is witnessing growing adoption of artificial intelligence in drug discovery, driven by increasing healthcare investments, government initiatives supporting digital health and innovation, and rising collaborations between local pharmaceutical companies and global tech firms. The MEA region’s focus on building advanced research infrastructure and fostering public–private partnerships is contributing to its gradual emergence as a key market for AI-driven pharmaceutical R&D.

• The United Arab Emirates leads the artificial intelligence in drug discovery market, driven by strong government initiatives to promote AI and digital health, significant investments in healthcare infrastructure, and strategic partnerships with global pharmaceutical and technology companies. The country is leveraging AI to accelerate drug discovery, optimise clinical trials, and develop advanced therapeutics, positioning itself as a regional hub for innovation in AI-enabled pharmaceutical research.

Application Insights

The drug optimisation and repurposing segment accounted for the highest market share of 55.7% in 2025, due to its high efficiency and cost-effectiveness. Optimisation enhances existing candidates by refining efficacy, safety, and dosing, enabling companies to accelerate approval timelines while reducing R&D spending. With growing pressure to deliver faster and more affordable treatments, AI-enabled optimisation and repurposing remain the most widely adopted applications in drug discovery.

Preclinical testing segment is another application of AI in drug development that is growing at the fastest pace. This rapid expansion is driven by AI's ability to enhance various aspects of preclinical testing, such as predicting drug toxicity, optimising drug candidate selection, and modelling biological interactions. By quickly identifying promising drug candidates and eliminating those likely to fail in later stages, AI streamlines the development process, increasing the overall efficiency of R&D efforts and fueling the segment's rapid growth.

Therapeutic Area Insights

Oncology accounted for 25.4% of the market in 2025, driven by the high global disease burden and sustained research and development (R&D) investment in cancer therapeutics. AI plays a critical role by analysing multidimensional datasets, uncovering novel drug targets, predicting treatment responses, and enabling personalised therapy design. Its use improves biomarker discovery, accelerates candidate selection, and enhances the design of clinical trials.

The infectious disease segment is expected to grow at the fastest CAGR of 34.0%, driven by advancements in AI and IoT. AI models help analyse transmission patterns, immune responses, and pathogen behaviour, while IoT devices generate real-time data on patients and their environments for disease monitoring. As global preparedness and surveillance systems expand, AI-driven platforms are becoming increasingly essential for combating infectious diseases, thereby accelerating the strong growth of this segment.

End Use Insights

Pharmaceutical and biotechnology companies captured 54.2% of the market in 2025, reflecting their extensive use of AI across discovery and development workflows. AI supports genome editing, chemical genomics, lead optimisation, ADMET analysis, and preclinical-to-clinical processes, reducing manual tasks and improving accuracy. These efficiency gains and the push for faster innovation continue to drive strong adoption across major drug developers.

Contract Research Organisations (CROs) represent the fastest-growing end-use segment with a projected CAGR of 58.6%. They are rapidly integrating AI into compound screening, predictive modelling, and clinical trial management to deliver faster, more cost-efficient research services. AI enhances trial design, improves patient recruitment accuracy, and reduces operational bottlenecks, enabling CROs to provide clients with high-quality, data-driven insights.

Competitive Landscape 

The global AI in drug discovery market is highly fragmented, with various companies offering services ranging from target identification and hit generation to lead optimisation and preclinical support. The market is dominated by firms that provide end-to-end AI capabilities, handle both small molecules and biologics, and possess strong data analysis infrastructure, predictive modelling, and financial backing. Key competitive differentiators include the breadth of AI techniques employed, comprehensiveness of service offerings, and ability to integrate large-scale omics, chemical, and clinical datasets.

BenevolentAI- A Market Leader

BenevolentAI is a clinical-stage AI-enabled drug discovery company headquartered in London, with research facilities in Cambridge (UK) and an office in New York. By combining deep scientific knowledge, biomedical data, and advanced AI/ML with experimental capabilities, BenevolentAI aims to shorten the timeline from “data → medicine,” thereby reducing R&D costs and risks, and increasing the probability of discovering novel or first-in-class therapies.

Latest News:

• In February 2025, BenevolentAI announced plans to merge with Osaka Holdings and delist from the Euronext Amsterdam stock exchange, a strategic decision aimed at reducing costs and prioritising investment in innovation and product.

List of key players in Artificial Intelligence for Drug Discovery and Development Market

1. Alphabet Inc.
2. Atomwise Inc.
3. Benevolent AI
4. Cloud Pharmaceutical
5. Deep Genomics
6. Exscientia
7. IBM Corporation
8. Insilico Medicine Inc.
9. Microsoft Corporation
10. Nvidia Corporation. 
11. GNS Healthcare
12. Google (DeepMind)
13. BioSymetrics, Inc.
14. Berg Health

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Strategic Initiatives

• December 2025 - Accenture invested in Ryght AI through Accenture Ventures to help life sciences companies transform clinical research using Agentic AI (a specialised form of generative AI).
• December 2025 - Excelsior Sciences, a company developing a new form of chemistry that machines can do and AI can use to enable closed-loop drug discovery, today announced it has raised $95 million to accelerate its mission to reinvent the process of discovering and manufacturing small molecules.
• December 2025 - Insilico Medicine licensed exclusive Greater China rights for ISM4808 (an AI-designed PHD inhibitor for Anemia of Chronic Kidney Disease) to TaiGen Biotechnology.