AI in Real-World Evidence Market Size, Share & Industry Analysis, By Component (Software/Platform and Services), By Deployment (Cloud-Based, On-Premise & Hybrid), By Technology (Machine Learning & Deep Learning, NLP/Generative AI), By Application (Cohort Discovery & Patient Stratification, Endpoint Extraction & NLP, Comparative Effectiveness & Outcomes Research, Safety Surveillance & Signal Detection, Regulatory & HTA Evidence Generation), By End User (Pharmaceutical & Biotechnology Companies, CROs/Real-world Data Vendors, Payers, Healthcare Providers), and Regional Forecast, 2026-2034

The global AI in real-world evidence market size was valued at USD 2.09 billion in 2025. The market is projected to grow from USD 2.70 billion in 2026 to USD 21.00 billion by 2034, exhibiting a CAGR of 29.22% during the forecast period.

The global market for AI in Real-World Evidence (RWE) encompasses software solutions and services that transform real-world data from EHRs, claims, registries, laboratories, wearables, and patient-reported inputs into practical clinical, regulatory, and business insights. The market is influenced by the escalating need for quicker evidence generation, heightened use of real-world data in regulatory and payer choices, and rising pressure on pharmaceutical firms to showcase product value beyond clinical studies.

Key market players in the global market include IQVIA Inc., Oracle, Datavant, and Komodo Health, Inc. Large-scale RWD access, AI-enabled analytics platforms, EHR and claims data integration, oncology-specific datasets, regulatory-grade evidence capabilities, and partnerships with pharma, payers, CROs, and healthcare providers are some of the strategies undertaken by these companies to strengthen their market presence.

AI in REAL-WORLD EVIDENCE MARKET TRENDS

Increasing Adoption of AI-powered Healthcare Analytics is a Significant Market Trend

The growing use of AI-driven healthcare analytics is becoming a significant trend in the global market, as life sciences firms transition from manual, case-by-case evidence production to quicker, data-centric analytics approaches. AI tools are capable of analyzing vast amounts of EHR, claims, registry, lab, and patient-level data to define cohorts, retrieve endpoints, assess treatment outcomes, and identify safety signals more quickly. This is crucial as pharmaceutical companies, payers, and regulators require prompt real-world insights to aid in clinical development, market access, and post-launch decision-making. With the expansion and fragmentation of healthcare datasets, AI driven analytics aid in decreasing data curation time and enhancing consistency in evidence creation. The trend is further bolstered by the increasing utilization of cloud-based RWE platforms, generative AI assistants, and automated processes for regulatory-quality analytics. Consequently, businesses providing AI-powered RWD and analytics solutions are experiencing greater acceptance among pharmaceutical firms, CROs, data suppliers, and payer entities. These factors are supporting the overall global AI in real-world evidence market growth during the forecast period.

• For instance, in October 2024, IQVIA announced the IQVIA AI Assistant, powered by its Healthcare-grade AI, to help users generate insights from high-quality health data, advanced analytics, and IQVIA Connected Intelligence across life sciences and healthcare workflows.

MARKET DYNAMICS

MARKET DRIVERS

Download Free sample to learn more about this report.

Rising Demand for Evidence-Based Decision Making is Propelling Market Growth

Rising demand for evidence-based decision making is a major driver for the global market, as pharma companies, payers, regulators, and healthcare providers increasingly need clear proof of treatment safety, effectiveness, and value in real-world populations. Traditional evidence generation is often slow, costly, and limited by manual data review, so organizations are adopting AI-enabled RWE platforms to convert EHR, claims, registry, and lab data into decision-ready insights. This helps companies support clinical development planning, label expansion, reimbursement negotiations, post-market safety monitoring, and health technology assessment submissions. AI also improves cohort identification, endpoint extraction, and comparative outcomes analysis, which makes evidence generation faster and more consistent. As drug pricing pressure and value-based care models increase, decision makers need stronger real-world proof before approving, covering, or prescribing therapies. Therefore, demand for AI-supported evidence workflows is growing across life sciences and healthcare organizations. All these factors cumulatively drive the overall market growth.

• For instance, in May 2025, Komodo Health announced that its real-world evidence platform supported 31 patient-journey research studies presented at ISPOR 2025, covering oncology, neurology, cardiovascular, metabolic, and rare diseases and helping address key evidence gaps for healthcare decision-making.

MARKET RESTRAINTS

Limited Availability of High-Quality Structured Healthcare Data to Limit Market Growth

The limited availability of high-quality structured healthcare data serves as a major limitation for the global market, since AI models require clean, complete, standardized, and accurately labeled data to produce trustworthy evidence. In practice, much of the valuable clinical data is contained in unstructured physician notes, scanned files, PDFs, lab narratives, imaging reports, and scattered EHR fields, complicating cohort discovery, endpoint extraction, and outcomes analysis. Data quality issues including absent values, inconsistent coding, duplicate entries, and restricted longitudinal follow-up can diminish trust in AI-produced RWE results. This results in additional expenses for data cleaning, validation, tokenization, and mapping prior to utilizing evidence for regulatory, payer, or clinical decisions. It also hinders adoption among pharmaceutical firms, contract research organizations, insurers, and healthcare providers needing verifiable and suitable evidence. Consequently, suppliers need to allocate significant resources toward data normalization, NLP extraction, governance, and quality assurance, which may limit rapid market growth.

• For example, in July 2024, the U.S. FDA issued guidance on assessing EHR and medical claims data for regulatory decision-making, emphasizing that sponsors must evaluate whether real-world data are fit-for-use, including data relevance, reliability, completeness, and traceability.

MARKET OPPORTUNITIES

Growing Utilization of Real-World Data in Drug Development and Regulatory Processes to Offer Lucrative Opportunities

The rising use of real-world data in drug development and regulatory activities is generating a significant opportunity for the global market, with pharmaceutical firms increasingly leveraging RWD to aid trial design, external control groups, label expansion, post-market safety, and reimbursement documentation. Conventional clinical trials frequently exhibit constrained patient diversity and extended timelines, therefore RWD from EHRs, claims, registries, and laboratories assists firms in grasping treatment efficacy in wider real-world groups. AI enhances this opportunity by automating cohort identification, endpoint extraction, managing missing data, and comparing outcomes across extensive datasets. This accelerates the process of generating evidence, enhances scalability, and increases its utility for regulatory and HTA conversations. With regulators increasingly formalizing the use of RWE in submissions, there will likely be a growing demand for AI platforms capable of producing transparent, auditable, and decision-quality evidence. As a result, suppliers providing AI-driven RWE analytics, NLP extraction, and regulatory-compliant data curation are effectively positioned to capitalize on this transition. All these factors would drive the market growth in the coming years.

• For instance, in December 2024, the U.S. FDA’s Center for Drug Evaluation and Research created the Center for Real-World Evidence Innovation to coordinate, advance, and promote the use of real-world data and real-world evidence in regulatory decision-making for drugs.

MARKET CHALLENGES

Regulatory Complexities Pose a Prominent Challenge to Market Growth

Regulatory complexities continue to pose a significant challenge for the global market, as RWE produced by AI must adhere to rigorous standards for data quality, transparency, traceability, and methodological validity before it can assist in regulatory decision-making. Pharma firms and RWE providers must demonstrate that the data source is appropriate for its intended use, the AI model is understandable, and the study design effectively manages bias, confounding factors, missing data, and coding discrepancies. This raises the time and expenses needed for validation, documentation, audit trails, and evidence packages ready for regulators. The difficulty increases when data is produced from various EHR, claims, registry, and lab datasets in different nations with varying privacy and regulatory regulations. Consequently, numerous firms continue to employ AI-driven RWE carefully for regulatory applications, particularly when results hinge on unstructured clinical information or endpoints derived from NLP. These demands can hinder platform adoption and restrict the quicker commercialization of AI-driven RWE solutions. All the factors cumulatively affect the market growth.

• For instance, in January 2025, the U.S. FDA issued draft guidance on the use of AI to support regulatory decision-making for drugs and biological products, highlighting the need to assess the credibility of AI model outputs used to support safety, effectiveness, or quality decisions.

Segmentation Analysis

By Component

Software/Platforms Segment Dominated Due to Wider Use of AI Platforms for Scalable RWE Generation

In terms of component, the market is divided into software/platform and services.

The software/platform segment accounted for the largest global AI in real-world evidence market share in 2025 as AI in real-world evidence is mainly delivered through cloud-based and enterprise platforms that can integrate EHR, claims, registry, lab, and patient-level datasets. Moreover, software platforms offer stronger scalability as they can be deployed across multiple studies, therapy areas, geographies, and evidence workflows with repeatable analytics. The segment is also supported by rising demand from pharmaceutical companies, CROs, payers, and data vendors for faster, auditable, and cost-efficient RWE generation.

• For instance, in March 2025, Aetion announced the availability of the Aetion Evidence Platform in AWS Marketplace, enabling customers to access its RWE technology through a scalable cloud procurement and deployment channel.

The services segment is anticipated to rise with a CAGR of 24.91% over the forecast period.  

To know how our report can help streamline your business, Speak to Analyst

By Deployment

Scalable Access to Large RWD and AI Analytics Workflows Led to Cloud-Based Segment Dominance

On the basis of deployment, the market is divided into on-premise, cloud-based, and hybrid.

The cloud-based segment dominated the global market in 2025. Cloud deployment allows pharma companies, CROs, payers, and data vendors to access AI analytics platforms faster without heavy internal infrastructure investment. It also supports multi-source data linkage, remote collaboration, automated model updates, and faster scaling across therapy areas and geographies. Furthermore, the segment is set to hold 70.1% share in 2026.

• For instance, in October 2024, Oracle launched Oracle Analytics Intelligence for Life Sciences, an AI-powered analytics platform with continuously updated real world data sources, including CancerMPact and multiomics, to help life sciences companies, health systems, and research institutes generate insights into diseases and patient impact.

The hybrid segment is growing at a CAGR of 25.42% over the forecast period.  

By Technology

NLP/Generative AI Segment is Growing at Highest CAGR Due to Faster Extraction of Evidence from Unstructured Clinical Data

Based on technology, the market is classified into machine learning & deep learning, NLP/generative AI, and others.

The NLP/generative AI segment is expected to grow at the highest CAGR as a large share of real-world evidence is hidden in unstructured clinical notes, pathology reports, physician narratives, discharge summaries, and imaging reports. The segment is gaining faster adoption because it reduces manual chart abstraction, improves scalability, and supports faster evidence generation across oncology, rare diseases, and specialty therapies. As pharma companies and RWE vendors seek deeper patient-level insights, demand for LLM-enabled extraction and validation tools is increasing rapidly.

• For instance, in July 2025, Flatiron Health presented research on AI-driven cancer progression extraction, showing the use of LLM-generated data and validation frameworks to support oncology real-world evidence and predictive modeling.

The machine learning & deep learning segment is anticipated to rise with a CAGR of 28.72% over the forecast period.  

By Application

Cohort Discovery & Patient Stratification Segment Dominated Due to Higher Use in Trial Planning and Targeted Evidence Generation

On the basis of application, the market is divided into cohort discovery & patient stratification, endpoint extraction & NLP, comparative effectiveness & outcomes research, safety surveillance & signal detection, regulatory & HTA evidence generation, and others.

The cohort discovery & patient stratification segment captured the highest share of the global market in 2025 as it is one of the earliest and most frequent uses of AI in real-world evidence workflows. Moreover, cohort discovery is used across almost every RWE study since accurate patient identification is the foundation for reliable outcomes analysis and evidence generation. The segment is also supported by rising demand for precision medicine, rare disease research, oncology studies, and therapy-area-specific patient journey analysis. Furthermore, the segment is set to hold 21.0% share in 2026.

• For instance, in September 2025, BostonGene announced that its AI-powered multiomic platform was recognized for supporting discovery, patient stratification, and clinical trial optimization. The company highlighted that its platform integrates molecular and clinical data to help identify patient subgroups and support precision medicine research.

The endpoint extraction & NLP segment is anticipated to rise with a CAGR of 30.78% over the forecast period.  

By End User

Pharmaceutical & Biotechnology Companies Segment Dominated Due to Higher Use of AI-RWE Across Drug Development and Market Access

In terms of end user, the market is segmented into pharmaceutical & biotechnology companies, CROs/real-world data vendors, payers, healthcare providers, and others.

In 2025, the pharmaceutical & biotechnology companies segment held the leading position in the global market. These companies are the largest users of AI-enabled real-world evidence for clinical development, regulatory strategy, post-market surveillance, label expansion, and reimbursement planning. Additionally, pharma and biotech companies have stronger budgets, larger drug pipelines, and continuous evidence needs across the product lifecycle. The segment is also supported by growing pressure to improve trial design, accelerate patient recruitment, demonstrate product differentiation, and support payer discussions with real-world outcomes. Furthermore, the segment is set to hold 46.4% share in 2026.

• For instance, in May 2025, Datavant and Boehringer Ingelheim expanded their collaboration to support Boehringer Ingelheim’s growing RWE initiatives.

In addition, CROs/real-world data vendors segment is projected to witness 30.76% growth rate during the forecast period.

AI in Real-World Evidence Market Regional Outlook

By geography, the market is divided into North America, Latin America, Asia Pacific, Europe, and the Middle East & Africa.

North America

To get more information on the regional analysis of this market, Download Free sample

The North American market reached USD 0.81 billion in 2024 and led the global market. In 2025, the region continued to hold its dominance, with USD 1.02 billion. The regional growth is driven by strong adoption of AI-enabled RWE platforms by pharmaceutical and biotechnology companies.

U.S. AI in Real-World Evidence Market

The U.S. market dominated the North American market and can be analytically approximated at around USD 1.20 billion in 2026, accounting for roughly 44.4% of global market.

Europe

Europe market size is anticipated to grow at 27.97% CAGR during the forecast period. Growth in Europe is supported by rising use of real-world data for health technology assessment, reimbursement decisions, and post-market evidence generation. The region is also benefiting from cross-border health data initiatives, stronger focus on data standardization, and growing demand for privacy-compliant evidence platforms.

U.K. AI in Real-World Evidence Market

The U.K. market is estimated at around USD 0.13 billion in 2026, representing roughly 4.7% of global revenues.

Germany AI in Real-World Evidence Market

Germany’s market size is projected to reach approximately USD 0.15 billion in 2026, equivalent to around 5.5% of global sales.

Asia Pacific

The Asia Pacific’s market is expected to reach a valuation of USD 0.60 billion by 2026. Asia Pacific is expected to grow rapidly due to expanding digital healthcare infrastructure, rising EHR adoption, and increasing clinical research activity across China, Japan, India, South Korea, and Australia.

Japan AI in Real-World Evidence Market

The Japanese market is estimated at around USD 0.13 billion in 2026, accounting for roughly 4.7% of global revenues.

China AI in Real-World Evidence Market

China’s market is projected to reach revenues of around USD 0.19 billion in 2026, representing roughly 6.9% of global sales.

India AI in Real-World Evidence Market

The Indian market is estimated at around USD 0.06 billion in 2026, accounting for roughly 2.1% of global revenues.

Latin America and Middle East & Africa

The Middle East & Africa and Latin America regions are likely to witness a moderate growth over the forecast period. The market in Latin America is projected to attain a valuation of USD 0.11 billion by 2026. The growth of both the regions is supported by improving healthcare digitization, rising use of electronic medical records, and increasing demand for evidence-based treatment and reimbursement decisions.

GCC AI in Real-World Evidence Market

The GCC market is projected to reach approximately USD 0.03 billion by 2026, representing about 1.1% of global revenues.

COMPETITIVE LANDSCAPE

Key Industry Players

Strong RWD Assets, AI Analytics Platforms, and Pharma Partnerships to Strengthen Market Positions

The global AI in real-world evidence market is moderately consolidated, with companies such as IQVIA Inc., Oracle, Datavant and Komodo Health, Inc. holding strong positions across AI-enabled RWE platforms space. These companies maintain their presence through large EHR and claims data networks, oncology-specific datasets, cloud-based analytics platforms, privacy-preserving data linkage, and partnerships with pharmaceutical companies, CROs, payers, and healthcare providers.

Additional key contributors include TriNetX, ConcertAI, and HealthVerity. These companies are expected to focus on AI-powered analytics, real-world data partnerships, cloud deployment, regulatory-grade study tools, and therapy-specific evidence solutions to strengthen their positions during the forecast period.

• For instance, in January 2025, ConcertAI and Foundation Medicine announced a collaboration to combine clinical and genomic real-world data assets for life sciences research, supporting precision oncology evidence generation and therapy development.

LIST OF KEY AI in REAL-WORLD EVIDENCE COMPANIES PROFILED IN REPORT

• IQVIA Inc. (U.S.)
• Oracle (U.S.)
• Datavant (U.S.)
• Komodo Health, Inc. (U.S.)
• TriNetX, LLC (U.S.)
• ConcertAI (U.S.)
• HealthVerity Inc. (U.S.)
• Veradigm LLC (U.S.)
• TEMPUS (U.S.)
• Truveta (U.S.)

KEY INDUSTRY DEVELOPMENTS

• May 2026: Tempus expanded its strategic collaboration with Bristol Myers Squibb to use AI, multimodal real-world data, and data science techniques to optimize clinical trial designs and improve probability of technical and regulatory success across five initial clinical development programs.
• April 2026: Truveta launched Truveta Intelligence, an AI-powered solution that delivers real-time insights from continuously refreshed real-world data for life sciences, public health, and healthcare organizations.
• March 2026: IQVIA unveiled IQVIA.ai, a unified agentic AI platform powered by NVIDIA to support decision-making across clinical, commercial, and real-world domains in life sciences.
• January 2026: Oracle launched the Oracle Life Sciences AI Data Platform, combining generative AI, agentic intelligence, public and owned data, and Oracle Health Real-World Data to support R&D, trials, post-market safety, commercialization, and regulatory workflows.
• October 2025: Flatiron Health launched six new hematology AI-powered longitudinal datasets, using LLM-enabled data extraction and validation to support real-world evidence generation in blood cancers.

REPORT COVERAGE

The global AI in real-world evidence market analysis encompasses an extensive examination of the market size and projections for all market segments featured in the report. It provides information on the market dynamics and trends that are anticipated to propel the market during the forecast period. It offers insights into crucial elements, such as innovations in products, the regulatory landscape, and the introduction of new products. Furthermore, the global market report outlines collaborations, mergers & acquisitions, along with significant advancements in the industry within the market. The global market forecast report additionally offers a comprehensive competitive landscape with details on market share and profiles of major active participants.

Request for Customization   to gain extensive market insights.

Report Scope & Segmentation