Global AI-Powered Real-World Evidence (RWE) Solutions Market Size is predicted to reach grow at a 14.6 % CAGR during the forecast period for 2025-2034.
Artificial intelligence (AI)-powered Real-World Evidence (RWE) solutions are those that use AI to gather, examine, and interpret real-world data (RWD) in order to produce insights on the efficacy, safety, and use of medical items in actual clinical settings. Regulatory agencies such as the FDA and the European Medicines Agency (EMA) have implemented frameworks acknowledging the importance of RWE, particularly in capturing treatment performance outside of controlled clinical trials, in response to the growing reliance on RWD to support drug approvals, label expansions, and post-marketing surveillance.
However, using RWE for regulatory reasons is still difficult since data must adhere to strict quality criteria that guarantee it is reproducible, traceable, and statistically sound. RWE's influence is limited, and wider regulatory adoption based on useful, real-world findings is delayed since many pharmaceutical companies still view it as an auxiliary tool rather than a fundamental strategic asset, despite its potential.
The increasing need for AI-powered analytics that can combine genomics with clinical outcomes is being driven by the necessity of genomic data for treating patients according to their unique genetic profiles. The significance of genetic data in population health studies, clinical trial optimization, and medication response prediction is increasing as a result of efforts to connect it with electronic health records (EHRs) and other real-world data sources. Complex genomic information is rapidly being interpreted by advanced AI technologies, such as deep learning and graph-based models, which offer greater insights into disease causes and the effectiveness of treatments. In order to speed up biomarker development, facilitate patient stratification, and improve regulatory submissions, pharmaceutical corporations are now investing heavily in genomics-driven real-world evidence (RWE).
Competitive Landscape
Some of the Major Key Players in the AI-Powered Real-World Evidence (RWE) Solutions Market are:
- Aetion
- Atropos Health
- ConcertAI
- Envision Pharma Group
- Flatiron Health
- Health Compiler
- Huma
- IQVIA
- ai
- Komodo Health
- NVIDIA CLARA
- OM1
- ai
- Optum
- Owkin
- Panalgo
- Realyze Intelligence
- Syntropy
- Tempus
- AI
- Veradigm
- Other Prominent Players
Market Segmentation
The AI-powered real-world evidence (RWE) solutions market is segmented into component, data source, therapeutic area, end-user, deployment model, technology, and application. Based on the component, the market is divided into software/platforms, services. Based on the data source, the market is divided into EHR/EMR data, claims data, genomics, wearables/IoT, patient-reported data, and imaging. Based on the therapeutic area, the market is divided into oncology, neurology, cardiology, rare diseases, and immunology. Based on the end-user, the market is divided into pharma/biotech, payers/PBMs, hospitals/IDNs, regulators, and CROs. Based on the deployment model, the market is divided into cloud-based, on-premise, and hybrid. Based on the technology, the market is divided into NLP, computer vision, federated learning, and graph ML. Based on the application, the market is divided into drug development, regulatory submissions, market access, precision medicine.
The EHR/EMR Data Segment is Expected to Have the Highest Growth Rate During the Forecast Period
The complete and longitudinal patient data found in Electronic Health Records (EHRs), such as lab results, diagnoses, prescriptions, procedures, and doctor notes, makes them a fundamental component of AI-powered Real-World Evidence (RWE) systems. These documents are essential for recording clinical outcomes, identifying patient groups, mimicking trial-like conditions, and complying with regulatory frameworks established by organizations such as the FDA and EMA. EHR data is extremely compatible with machine learning and predictive analytics, which increases its usefulness in practical research and decision-making. This is due to the structured elements of EHRs, such as lab panels and ICD codes, as well as developments in natural language processing (NLP), which extract insights from unstructured clinical notes.
The NLP Segment Dominates the Market
NLP has developed into a key component of commercial RWE platforms, generating more precise and scalable real-world insights than more recent technologies like federated learning or graph machine learning. Physician notes, pathology reports, and discharge summaries are just a few examples of the large amount of unstructured healthcare data that makes it difficult to evaluate with conventional techniques. Through the extraction of important insights from these unstructured sources, Natural Language Processing (NLP) facilitates a deeper comprehension and application of clinical data. Since Electronic Health Records (EHRs) are the main source of data for the Real-World Evidence (RWE) market, it is especially important for evaluating clinical narratives inside these systems. Pharmaceutical businesses and regulatory bodies frequently use NLP-based solutions for tasks including outcome tracking, adverse event detection, and cohort identification.
North America Has the Largest Market Share During the Forecast Period.
The United States has one of the highest rates of electronic health record (EHR) implementation, generating a vast volume of real-world data (RWD) that serves as a foundation for AI-driven analytics. The U.S. FDA’s Real-World Evidence (RWE) Framework actively supports the use of RWE in regulatory decision-making, fostering confidence and investment from the pharmaceutical and healthcare industries. Additionally, significant funding for AI in healthcare, along with strategic collaborations between technology firms and healthcare organizations, is accelerating the adoption of AI-powered RWE solutions. This growth is further supported by a rapidly expanding healthcare landscape characterized by a growing population, a rising burden of chronic diseases, and a strong focus on enhancing healthcare infrastructure, making North America the leading region in this market.
Recent Developments:
- In March 2025, Aetion declared that its Aetion® Evidence Platform (AEP) is now available in the Amazon Web Services (AWS) Marketplace, a digital catalog that facilitates the discovery, testing, purchase, and deployment of software that runs on AWS and contains hundreds of product listings from independent software suppliers. With this introduction, health sciences businesses, payers, and regulators may now leverage scalable, cloud-based evidence generation with the security and dependability of AWS, removing implementation hurdles and streamlining procurement.
- In April 2024, IQVIA declared an extension of its strategic alliance with Salesforce to accelerate the development of Salesforce's Life Sciences Cloud. For the life sciences industry, this project is a next-generation platform for consumer contact. IQVIA hopes to further the development of technological solutions that speed up decision-making processes in a number of areas, such as RWE, discovery, clinical development, medical affairs, and patient safety, through these strategic alliances.
AI-Powered Real-World Evidence (RWE) Solutions Market Report Scope :
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Report Attribute |
Specifications |
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Growth Rate CAGR |
CAGR of 14.6% from 2025 to 2034 |
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Quantitative Units |
Representation of revenue in US$ Mn and CAGR from 2025 to 2034 |
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Historic Year |
2021 to 2024 |
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Forecast Year |
2025-2034 |
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Report Coverage |
The forecast of revenue, the position of the company, the competitive market structure, growth prospects, and trends |
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Segments Covered |
By Component, Data Source, Therapeutic Area, End-User, Deployment Model, Technology, Application |
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Regional Scope |
North America; Europe; Asia Pacific; Latin America; Middle East & Africa |
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Country Scope |
U.S.; Canada; U.K.; Germany; China; India; Japan; Brazil; Mexico; The UK; France; Italy; Spain; China; Japan; India; South Korea; Southeast Asia; South Korea; South East Asia |
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Competitive Landscape |
Aetion, Atropos Health, ConcertAI, Envision Pharma Group, Flatiron Health, Health Compiler, Huma, IQVIA, Ividence.ai, Komodo Health, NVIDIA CLARA, OM1, Okra.ai, Optum, Owkin, Panalgo, Realyze Intelligence, Syntropy, Tempus, Unlearn.AI, Veradigm, Other Prominent Players |
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Customization Scope |
Free customization report with the procurement of the report and modifications to the regional and segment scope. Particular Geographic competitive landscape. |
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Pricing and Available Payment Methods |
Explore pricing alternatives that are customized to your particular study requirements. |
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