According to DelveInsight’s analysis, The demand for Artificial Intelligence in clinical trials is experiencing strong growth, primarily driven by the rising global prevalence of chronic conditions like diabetes, cardiovascular diseases, respiratory illnesses, and cancer. This growth is further supported by increased investments and funding dedicated to advancing drug discovery and development efforts. Additionally, the growing number of strategic collaborations and partnerships among pharmaceutical, biotechnology, and medical device companies is significantly boosting the adoption of AI-driven solutions in clinical trials. Together, these factors are anticipated to fuel the expansion of the AI in the clinical trials market during the forecast period from 2025 to 2032.

DelveInsight’s “Artificial Intelligence (AI) in Clinical Trials Market Insights, Competitive Landscape and Market Forecast-2032” report provides the current and forecast market outlook, forthcoming device innovation, challenges, market drivers and barriers. The report also covers the major emerging products and key Artificial Intelligence (AI) in Clinical Trials companies actively working in the market.

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Artificial Intelligence (AI) in Clinical Trials Overview

Artificial Intelligence (AI) in clinical trials refers to the use of advanced machine learning algorithms and data analytics to streamline and improve various aspects of clinical research. AI enhances trial design, patient recruitment, site selection, and data analysis by identifying patterns and predicting outcomes. It enables faster patient matching, optimizes protocol design, reduces trial timelines, and improves data quality and monitoring. AI also helps in real-time adverse event detection and adaptive trial management, making clinical trials more efficient, cost-effective, and patient-centric.

DelveInsight Analysis: The global Artificial Intelligence in clinical trials market size was valued at USD 1,350.79 million in 2024 and is projected to expand at a CAGR of 12.04% during 2025-2032, reaching approximately USD 3,334.47 million by 2032.

Artificial Intelligence (AI) in Clinical Trials Market Insights

Geographically, North America is expected to lead the AI in the clinical trial market in 2024, driven by several critical factors. The region’s growing burden of chronic diseases, substantial investments in R&D, and the rising volume of clinical trials contribute significantly to this dominance. Additionally, an increasing number of collaborations and partnerships among pharmaceutical and medical device companies, along with the advancement of sophisticated AI solutions, are accelerating market expansion. These developments are enhancing the ability to manage complex clinical trials efficiently, driving the adoption of AI technologies and supporting the market’s growth in North America throughout the forecast period from 2025 to 2032.

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Recent Developments in the Artificial Intelligence (AI) in Clinical Trials Market Report

• In May 2025, Avant Technologies, Inc. (OTCQB: AVAI) and joint venture partner Ainnova Tech, Inc. announced the initiation of acquisition discussions aimed at enhancing their presence in the rapidly growing AI-powered healthcare sector.

• In March 2025, Suvoda introduced Sofia, an AI-driven assistant created to optimize clinical trial management processes. Sofia aids study teams by providing quick access to essential trial data and real-time, intelligent insights. This tool boosts operational efficiency, minimizes manual tasks, and helps teams make faster, data-informed decisions throughout the clinical trial journey.

• In December 2024, ConcertAI and NeoGenomics unveiled CTO-H, an advanced AI-powered software platform designed to enhance research analytics, clinical trial design, and operational efficiency. CTO-H provides an extensive research data ecosystem, offering comprehensive longitudinal patient data, deep biomarker insights, and scalable analytics to support more precise, efficient, and data-driven clinical development processes.

• In June 2024, Lokavant introduced SpectrumTM, the first AI-powered clinical trial feasibility solution aimed at enhancing trial performance throughout the clinical development process. Spectrum enables study teams to forecast, control, and improve trial timelines and expenses in real-time.

• Thus, owing to such developments in the market, rapid growth will be observed in the Artificial Intelligence (AI) in Clinical Trials market during the forecast period

Key Players in the Artificial Intelligence (AI) in Clinical Trials Market

Some of the key market players operating in the Artificial Intelligence (AI) in Clinical Trials market include- TEMPUS, NetraMark, ConcertAI, AiCure, Medpace, Inc., ICON plc, Charles River Laboratories, Dassault Systèmes, Oracle, Certara, Cytel Inc., Phesi, DeepHealth, Unlearn.ai, Inc., H1, TrialX, Suvoda LLC, Risklick, Lokavant, Research Solutions, and others.

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Analysis on the Artificial Intelligence (AI) in Clinical Trials Market Landscape

To meet the growing needs of clinical trials, leading companies in the AI in Clinical Trials market are creating advanced AI solutions aimed at improving trial efficiency, optimizing patient recruitment, and enhancing clinical trial design at investigator sites. For example, in April 2023, ConcertAI introduced CTO 2.0, a clinical trial optimization platform that utilizes publicly available data and partner insights to deliver comprehensive site and physician-level trial data. This tool provides key operational metrics and site profiles to evaluate trial performance and site capabilities. Additionally, CTO 2.0 assists sponsors in complying with FDA requirements for inclusive trial outcomes, promoting a shift toward community-based trials with more streamlined and patient-centric designs.

As a result of these advancements, the software segment is projected to experience significant growth throughout the forecast period, contributing to the overall expansion of the AI in the clinical trials market.

Scope of the Artificial Intelligence (AI) in Clinical Trials Market Report

• Coverage: Global

• Study Period: 2022-2032

• Artificial Intelligence (AI) in Clinical Trials Market Segmentation By Product Type: Software and Services

• Artificial Intelligence (AI) in Clinical Trials Market Segmentation By Technology Type: Machine Learning (ML), Natural Language Processing (NLP), and Others

• Artificial Intelligence (AI) in Clinical Trials Market Segmentation By Application Type: Clinical Trial Design & Optimization, Patient Identification & Recruitment, Site Identification & Trial Monitoring, and Others

• Artificial Intelligence (AI) in Clinical Trials Market Segmentation By Therapeutic Area: Oncology, Cardiology, Neurology, Infectious Disease, Immunology, and Others

• Artificial Intelligence (AI) in Clinical Trials Market Segmentation By End-User: Pharmaceutical & Biotechnology Companies and Medical Device Companies

• Artificial Intelligence (AI) in Clinical Trials Market Segmentation By Geography: North America, Europe, Asia-Pacific, and Rest of the World

• Key Artificial Intelligence (AI) in Clinical Trials Companies: TEMPUS, NetraMark, ConcertAI, AiCure, Medpace, Inc., ICON plc, Charles River Laboratories, Dassault Systèmes, Oracle, Certara, Cytel Inc., Phesi, DeepHealth, Unlearn.ai, Inc., H1, TrialX, Suvoda LLC, Risklick, Lokavant, Research Solutions, and others

• Porter’s Five Forces Analysis, Product Profiles, Case Studies, KOL’s Views, Analyst’s View

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Table of Contents

1 Artificial Intelligence (AI) in Clinical Trials Market Report Introduction

2 Artificial Intelligence (AI) in Clinical Trials Market Executive summary

3 Regulatory and Patent Analysis

4 Artificial Intelligence (AI) in Clinical Trials Market Key Factors Analysis

5 Porter’s Five Forces Analysis

6 COVID-19 Impact Analysis on Artificial Intelligence (AI) in Clinical Trials Market

7 Artificial Intelligence (AI) in Clinical Trials Market Layout

8 Global Company Share Analysis – Key Artificial Intelligence (AI) in Clinical Trials Companies

9 Company and Product Profiles

10 Project Approach

11 Artificial Intelligence (AI) in Clinical Trials Market Drivers

12 Artificial Intelligence (AI) in Clinical Trials Market Barriers

13 About DelveInsight

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This release was published on openPR.

New York state lawmakers on June 12, 2025 passed the Responsible AI Safety and Education Act (the RAISE Act), which aims to safeguard against artificial intelligence (AI)-driven disaster scenarios by focusing on the largest AI model developers; the bill now heads to the governor’s desk for final approval. The RAISE Act is the latest legislative movement at the state level seeking to regulate AI, a movement that may continue to gain momentum after a 10-year moratorium on AI regulation was removed from the recently passed One Big Beautiful Bill.

Background and Core Provisions

Inspired by California’s SB 1047 bill, which was vetoed by California Governor Gavin Newsom in September 2024 over concerns that it could stifle innovation, the RAISE Act aims to prevent so-called “frontier AI models” from contributing to “critical harm.” For the purposes of the RAISE Act, “critical harm” is defined as events in which AI causes the death or injury of more than 100 people, or more than $1 billion in damages to rights in money or property caused or materially enabled by a large developer’s creation, use, storage, or release of frontier model, through either (1) the creation or use of a chemical, biological, radiological, or nuclear weapon or (2) an artificial intelligence model engaging in conduct that is both (a) done with limited human intervention and (b) would, if committed by a human, constitute a crime specified in the penal law that required intent, recklessness, or gross negligence or the soliciting or aiding and abetting of such crimes.

Unlike SB 1047, which faced criticism for casting too wide a net over general AI systems, the RAISE Act targets only “frontier” models developed by companies that meet both of the following criteria: (1) a training cost threshold where the applicable AI model was trained using more than $100 million in computing resources, or more than $5 million in computing resources where a smaller artificial model was trained on a larger artificial intelligence model and has similar capabilities to the larger artificial intelligence model; and (2) the model is made available to New York residents. To the extent the RAISE Act aligns with similar state-level regulations and restrictions, this would theoretically allow some room for innovation by entities (like startup companies and research organizations) less likely to cause such critical harm.

If a company meets both criteria and is therefore subject to the jurisdiction of the RAISE Act, it will need to comply with all the following before deploying any frontier AI model:

• Implement a written safety and security protocol
• Retain an unredacted version of such safety and security protocol for as long as the frontier model is deployed, plus five years
• Conspicuously publish a copy of the safety and security protocol and transmit such protocol to the division of homeland security and emergency services
• Record information on specific tests and test results used in any assessment of the frontier AI model

From a practical perspective, requirements such as recordation of information on testing of any frontier AI model may push smaller startups and research organizations out of the market to the extent the resources necessary to maintain such information present additional and costly overhead.

Enforcement and Exceptions

The RAISE Act empowers the New York attorney general to levy civil penalties of up to $10 million for initial violations and up to $30 million for subsequent violations by noncompliant covered companies. This includes penalties for violations of a developer’s transparency obligations as specified above or as required elsewhere in the RAISE Act, such as the requirement that covered companies retain an independent auditor annually to review compliance with the law. However, covered companies may make “appropriate redactions” to their safety protocols when necessary to protect public safety, safeguard trade secrets, maintain confidential information as required by law, or protect employee or customer privacy.

Looking Ahead

The bill’s fate remains uncertain. Our team is monitoring developments closely, including potential impacts on commercial contracting, compliance obligations, and technology adoption.