Artificial Intelligence (AI)-Powered Clinical Trial Site Feasibility Market Report 2025

The artificial intelligence (AI)-powered clinical trial site feasibility market size has grown exponentially in recent years. It will grow from $1.24 billion in 2024 to $1.53 billion in 2025 at a compound annual growth rate (CAGR) of 23.8%. Growth during the historic period was driven by the rising adoption of AI in clinical research, increasing demand for faster patient recruitment, expansion of decentralized clinical trials, advancements in electronic data capture systems, and regulatory support for innovative trial designs.

The artificial intelligence (AI)-powered clinical trial site feasibility market size is expected to see exponential growth in the next few years. It will grow to $3.55 billion in 2029 at a compound annual growth rate (CAGR) of 23.4%. Growth in the forecast period is expected to be fueled by the integration of real-world data with AI analytics, expansion of virtual clinical trial platforms, rising investment in precision medicine, adoption of predictive modeling for site selection, and development of adaptive trial designs powered by AI. Key trends anticipated for the forecast period include the use of predictive analytics to optimize site selection, integration of real-world data to strengthen feasibility assessments, deployment of machine learning algorithms to forecast patient recruitment, adoption of cloud-based AI platforms for collaborative trial planning, and application of natural language processing to evaluate site performance data.

The increase in clinical trials is contributing to the expansion of the market due to rising demand for improved trial site selection and participant enrollment. The anticipated growth in clinical trials is expected to drive the artificial intelligence powered clinical trial site feasibility market in the future. Clinical trials are research studies conducted worldwide to evaluate the safety and effectiveness of new medical treatments, drugs, and devices. This rise in clinical trials is largely the result of increased funding in biomedical research and development, as both public and private sectors acknowledge the urgent need for innovative healthcare solutions. The expansion of clinical trials fuels the need for artificial intelligence powered feasibility tools, as research organizations require advanced systems to identify the most suitable locations, evaluate site performance, and estimate enrollment success. For example, in November 2023, the Association of the British Pharmaceutical Industry reported that the number of industry-sponsored clinical trials initiated in the United Kingdom grew by 4.3 percent, increasing from 394 trials in 2021 to 411 in 2022. As a result, the growing number of clinical trials is driving the demand for artificial intelligence powered clinical trial site feasibility solutions.

Key companies operating in the artificial intelligence powered clinical trial site feasibility market are concentrating on the development of advanced tools such as artificial intelligence based feasibility and recruitment platforms to enhance site selection and streamline operations within clinical trials. These platforms use artificial intelligence and machine learning technologies to evaluate trial protocols and site data, allowing for better identification of clinical sites and more effective patient recruitment through accurate participant matching. This accelerates trial timelines and increases the chances of success. For example, in June 2023, ObjectiveHealth, a company based in the United States that offers integrated research and technology services, introduced ObjectiveScreen, a platform powered by artificial intelligence that improves clinical trial outcomes by enhancing patient identification, prequalification, and retention. It connects directly with electronic health records and applies machine learning algorithms to identify high-risk individuals and match them with appropriate trials, thereby speeding up recruitment and improving overall trial performance.

In February 2023, ZS Associates, a United States based technology and consulting firm, acquired Trials.ai for an undisclosed amount. This acquisition aims to strengthen ZS Associates’ role in the healthcare industry by enhancing the efficiency of clinical trials, shortening the time required to bring therapies to market, and improving the experience of trial participants. Trials.ai is a United States based company focused on healthcare that provides artificial intelligence and analytics solutions to support and improve clinical trial site feasibility.

Major players in the artificial intelligence (AI)-powered clinical trial site feasibility market are Oracle Corporation, Thermo Fisher Scientific Inc., NVIDIA Corporation, IQVIA Holdings Inc., Labcorp Holdings Inc., Dassault Systèmes SE, Parexel International Corporation, ZS Associates Inc., Veeva Systems Inc., Verily Life Sciences LLC, Signant Health Holding Corp., Saama Technologies LLC, Elligo Health Research Inc., ConcertAI Inc., Medable Inc., Science 37 Inc., Castor EDC Inc., Unlearn.AI Inc., Antidote Technologies Inc., Deep 6 AI.

North America was the largest region in the artificial intelligence (AI)-powered clinical trial site feasibility market in 2024. Asia-Pacific is expected to be the fastest-growing region in the forecast period. The regions covered in artificial intelligence (AI)-powered clinical trial site feasibility report are Asia-Pacific, Western Europe, Eastern Europe, North America, South America, Middle East and Africa. The countries covered in the artificial intelligence (AI)-powered clinical trial site feasibility market report are Australia, Brazil, China, France, Germany, India, Indonesia, Japan, Russia, South Korea, UK, USA, Canada, Italy, Spain.

Note that the outlook for this market is being affected by rapid changes in trade relations and tariffs globally. The report will be updated prior to delivery to reflect the latest status, including revised forecasts and quantified impact analysis. The report’s Recommendations and Conclusions sections will be updated to give strategies for entities dealing with the fast-moving international environment.

The sudden escalation of U.S. tariffs and the consequent trade frictions in spring 2025 are severely impacting the healthcare sector, particularly in the supply of critical medical devices, diagnostic equipment, and pharmaceuticals. Hospitals and healthcare providers are facing higher costs for imported surgical instruments, imaging equipment, and consumables such as syringes and catheters, many of which have limited domestic alternatives. These increased costs are straining healthcare budgets, leading some providers to delay equipment upgrades or pass on expenses to patients. Additionally, tariffs on raw materials and components are disrupting the production of essential drugs and devices, causing supply chain bottlenecks. In response, the industry is diversifying sourcing strategies, boosting local manufacturing where possible, and advocating for tariff exemptions on life-saving medical products.

Artificial intelligence (AI)-powered clinical trial site feasibility refers to platforms and services that use advanced algorithms to assess and identify the most suitable clinical trial sites. These solutions process large datasets to forecast site performance and patient recruitment potential. They improve the speed and accuracy of decision-making, reduce the likelihood of trial delays, and streamline feasibility assessments while enhancing overall operational efficiency.

The primary component types of AI-powered clinical trial site feasibility are software and services. Software consists of AI-driven platforms and tools that evaluate trial data, site performance, and patient demographics to optimize site selection and feasibility. Deployment options include cloud-based and on-premises models, supporting applications such as site selection, patient recruitment, protocol design, performance analytics, and more. Key end-users include pharmaceutical companies, contract research organizations, academic research institutes, hospitals, and other healthcare entities.

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

The artificial intelligence (AI)-powered clinical trial site feasibility market includes revenues earned by providing services such as site identification and selection, predictive enrollment modeling, investigator performance analysis, risk assessment and mitigation, and patient population analytics. The market value includes the value of related goods sold by the service provider or included within the service offering. Only goods and services traded between entities or sold to end consumers are included.

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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