Artificial Intelligence (AI) in Drug Discovery Market in North America – 2030 Forecast

The artificial intelligence (AI) in drug discovery market focuses on using AI technologies to accelerate and enhance the process of discovering new drugs. AI helps researchers identify potential drug candidates, analyze complex biological data, and predict how compounds will interact with targets in the body. This significantly reduces the time and cost traditionally involved in drug development. The market is rapidly growing due to rising R&D costs, increasing demand for personalized medicine, and advancements in AI algorithms. Pharmaceutical companies and biotech firms are increasingly partnering with AI companies to improve drug discovery efficiency and success rates.

According to Fortune Business Insights, the global artificial intelligence (AI) in drug discovery market was valued at USD 3.00 billion in 2022 and is projected to grow from USD 3.54 billion in 2023 to USD 7.94 billion by 2030, exhibiting a compound annual growth rate (CAGR) of 12.2% during the forecast period (2023–2030). In 2022, North America dominated the market with a 69.33% share.

Top Companies in the Market

• Microsoft (U.S.)

• Schrödinger, Inc. (U.S.)

• Cresset (U.K.)

• IBM (U.S.)

• Atomwise Inc. (U.S.)

• Insilico Medicine (U.S.)

• Exscientia (U.K.)

• BenevolentAI (U.K.)

• Aria Pharmaceuticals, Inc. (U.S.)

• Integral BioSciences (U.S.)

• Alphabet Inc. (U.S.)

Key Industry Development

In November 2022, Cyclica received a grant of USD 1.8 million from the Bill & Melinda Gates Foundation. The funding supports Cyclica’s AI‑enabled drug discovery platform to discover novel non‑hormonal contraceptives, leveraging multiple low‑data biological targets. This landmark development underscores the role of AI in addressing global health goals.

Market Drivers

The increasing burden of chronic diseases such as cancer, cardiovascular conditions, and metabolic disorders fuels demand for AI‑based drug discovery solutions. The pharmaceutical industry’s relentless focus on reducing time‑to‑market and development costs is a pivotal driver. AI enables rapid identification of hit and lead compounds, accelerates target validation, and optimizes molecular design—thereby improving efficiency and predictability in drug pipelines.

Market Restraints

Despite robust growth, the market faces significant hurdles. A key challenge lies in data quality and standardization: bio‑medical datasets are often small, heterogeneous, and fragmented, limiting AI models’ ability to generalize reliably. Furthermore, the complexity and multi‑format nature of pharma data—including imaging, multi‑omics and clinical records—pose obstacles to AI implementation.

Market Report Coverage

The Fortune Business Insights report offers deep analysis across drug types (small molecule vs. large molecule), technology (machine learning, deep learning, NLP, etc.), applications (target discovery, screening, validation, optimization), and end‑users (pharma companies, biotech firms, CROs/CDMOs). It also examines upcoming innovations, product launches, and strategic partnerships shaping the AI‐in‑drug discovery landscape.

Market Competitive Landscape

The market is marked by strong collaboration among pharmaceutical giants and AI technology firms. Alphabet Inc. (through Isomorphic Labs, a DeepMind spin‑off), IBM (Watson Health), Insilico Medicine, Exscientia, BenevolentAI, Atomwise, and Schrödinger are at the forefront of innovation. These players are investing heavily in platform development and forming partnerships to accelerate discovery timelines and enhance therapeutic productivity.

Market Segments

• By Drug Type:

  • Small molecule segment dominated in 2022, benefiting from abundant clinical datasets and more predictable structures; small molecules make up over 90% of the pharma market and comprised 182 of 293 FDA‑approved entities in 2017–2022.

  • Large molecule segment held a lower share due to R&D complexity and limited data availability, but is projected to grow as investments increase in biologics discovery.

• By Offering: Software and services offerings support distinct stages of the drug discovery pipeline; software (platforms) is expected to lead, while services grow more slowly due to a talent shortage in AI deployment.

• By Technology: Machine learning and deep learning are key drivers; NLP and computer vision also enable drug target interpretation, multi‑omics integration, and predictive modelling.

• By End‑User: Includes pharmaceutical companies, biotechnology firms, contract research organizations (CROs) and contract development and manufacturing organizations (CDMOs), among others

Market Regional Insights

North America led the market in 2022 with a dominant share of 69.33%, driven by a strong presence of major pharma players, high R&D investment, and robust AI adoption. 

Europe held the second‑largest share in 2022, supported by growing adoption of affordable AI‑based drug discovery interventions. The Asia-Pacific region is anticipated to register the fastest CAGR during the forecast period, thanks to rising chronic disease prevalence and the expanding presence of drug manufacturers in markets like China, India, and South Korea. Latin America and Middle East & Africa are projected to grow more slowly due to lower healthcare expenditures and limited local pharmaceutical R&D ecosystems.

Explore the full research report with detailed insights and TOC:https://www.fortunebusinessinsights.com/artificial-intelligence-in-drug-discovery-market-105354 

Future Market Scope

The AI in drug discovery market is positioned for robust expansion beyond 2030, with pharmaceutical firms and AI technology providers further deepening collaboration. Ongoing advances in machine learning, deep learning, NLP, and generative AI are expected to enhance efficiency in target identification, molecule design and pre‑clinical validation pipelines.

Cloud‑based platforms and integrated multi‑omics data tools, backed by increased investment and strategic alliances, offer fertile ground for next‑generation therapeutic development. The successful deployment of AI tools—particularly in novel biologics, personalized medicine, and complex disease targets—is expected to expand the market’s potential well into the next decade.

Conclusion

With projected growth from USD 3.54 billion in 2023 to nearly USD 7.94 billion by 2030 at a CAGR of 12.2%, and North America commanding nearly 70% of the global market as of 2022, the AI‑powered drug discovery sector is reshaping pharmaceutical R&D. Despite challenges around data standardization and talent gaps, the synergy between cutting‑edge AI technologies and life sciences promises accelerated innovation, reduced costs, and faster delivery of novel therapies.

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