AI In Life Science Analytics Market Size to reach $3.6 billion, Globally, by 2030 - Exclusive Research by The Research Insights

CHICAGO, May 15, 2025 /PRNewswire/ -- The global AI In Life science Analytics Market is projected to be valued at USD 1.9 billion in 2024 and reach USD 3.6 billion by 2030, growing at a CAGR of 10.9% according to a new report by The Research Insights. The ai in life science analytics market will achieve substantial growth in future years through AI and machine learning developments alongside healthcare spending increases.

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Growing Integration of AI in Diagnostics, Real-World Evidence Generation, and Personalized Healthcare:
The second main driver involves AI technology's growing usage in diagnostics and patient monitoring which enables real-world evidence generation to provide life science analytics with detailed and useful information. Diagnostic tools now integrate AI technologies to increase their accuracy and speed while enabling early detection of various diseases such as cancer and cardiovascular and neurological disorders. Life sciences analytics platforms depend on the massive datasets generated through AI-powered diagnostic tools to obtain valuable insights.

The Research Insights reports on Artificial Intelligence in Diagnostics Market Size reveal that AI's capability to process various data types like imaging results and genomic information allows healthcare organizations to create predictive patient outcome models and improve treatment strategies. The abundance of data within this environment supports the creation of real-world evidence which regulatory bodies increasingly require for drug approval processes and post-market oversight.

The Healthcare Analytics Market report reveals that merging AI-powered real-world data analytics serves as a fundamental step toward personalizing medical treatments and enhancing patient adherence by allowing healthcare providers to design interventions according to individual risk profiles. The merging of AI diagnostic tools with life science analytics platforms drives market growth through innovation and enhanced healthcare delivery which boosts the AI In Life science Analytics Market.

The use of artificial intelligence technologies enables faster and more economical methods for discovering and developing new drugs:
The primary factor driving AI adoption in Life Science Analytics Market is the critical demand to improve drug discovery and development efficiency while reducing costs and time. Traditional drug development requires extensive time and financial resources to reach market introduction after more than ten years and billions in investment while facing substantial clinical trial failure rates. AI-driven analytical tools are transforming the field through their capability to conduct deep evaluation of multifaceted biological and chemical data along with clinical information. Machine learning and deep learning methods combined with natural language processing techniques enable swift identification of drug targets and molecular interaction prediction while optimizing selection of candidates.

According to The Research Insights Artificial Intelligence in Drug Discovery Market report these AI innovations enable virtual screening of compound libraries and biomarker discovery while simulating clinical trial results which leads to significant reductions in development time and costs. AI integration enhances precision medicine through patient stratification and personalized therapies which result in higher clinical trial success rates. The surge in R&D productivity serves as a pivotal force that accelerates the implementation of AI-based analytics tools throughout pharmaceutical companies, biotech firms and research institutions globally.

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By Based on Component, the AI In Life science Analytics Market is divided into, Software, Hardware, and Services. Life science analytics relies on AI software that supports advanced data modelling techniques as well as pattern recognition and predictive analytics. These platforms enable the processing of massive datasets from genomics studies to clinical trials and real-world evidence so that organizations can obtain actionable insights. Life science organizations' focus on precision medicine and faster drug development drives increasing demand for AI software solutions that offer both customization and scalability. The increasing demand for high-performance computing and data storage demonstrates Hardware's essential supporting function. Deep learning applications together with image analysis and simulation demand strong infrastructure support. The expanding amount of biomedical data along with requirements for faster processing and precise results drives growth in this segment. Services generated the highest revenue share in 2023 at 37.7% of the market size.

By Based on Delivery, the AI In Life science Analytics Market is divided into Cloud, and On Premise. Market dominance of cloud-based solutions stems from their ability to adapt to business needs while scaling resources and reducing operational costs. During 2023, the cloud segment led the market with revenue share reaching 51.1%. The ability of cloud platforms to facilitate real-time data access and remote team collaboration while enabling seamless updates makes them particularly suitable for multi-site clinical trials and global research teams working with data-heavy AI tasks. Cloud adoption continues to rise as decentralized trials and real-world data analytics become more important. Organizations that need rigorous data security protocols and infrastructure control still find on-premise deployment solutions relevant. Pharmaceutical and biotech companies often select on-premise solutions to ensure complete control over their proprietary and sensitive data. The expansion of cloud technology goes hand-in-hand with the development of hybrid models that aim to provide both operational flexibility and robust security.

By Based on Application, the AI In Life science Analytics Market is divided into, Research and Development, Sales and Marketing Support, Supply Chain Analytics, and Others. Research and Development stands as the primary domain where AI transforms drug discovery alongside preclinical modelling and clinical trial optimization. Machine learning algorithms enable researchers to forecast molecular behaviour while identifying therapeutic targets and speeding up compound screening processes which significantly reduces both time and cost throughout R&D operations.
In 2023 the sales and marketing sector controlled the market while generating 33% of total revenue. The expanding field of Sales and Marketing Support leverages AI to evaluate customer behaviour patterns while predicting market movements and fine-tuning sales approaches through personalized physician interactions. Natural language processing together with sentiment analysis tools enable teams to grasp physician and patient requirements as they happen.

By Based on End Use, the AI In Life science Analytics Market is divided into, Medical Devices, Pharmaceutical, Biotechnology, and Others. In 2023 the pharmaceutical sector became the market leader with 46.3% of total revenue share. Among industries adopting AI analytics, pharmaceutical companies lead by applying AI technologies throughout drug development and clinical trials as well as regulatory and commercial functions. AI enables pharmaceutical companies to increase pipeline efficiency while shortening market launch times and boosting return on investment.
Biotechnology firms use AI technology to advance genomics research and develop personalized treatments as well as discover biomarkers. Biotech companies that concentrate on innovation and data-heavy processes are quickly adopting AI to achieve scientific understanding and competitive benefits.

By Geography, the North American AI In Life science Analytics Market maintained its leading position by generating 50.23% of total market revenues during 2023. The dominance of this region stems from government initiatives and public-private partnerships which drive technological advancement. The ongoing fruitful efforts indicate that numerous success stories will soon emerge for this market segment. Healthcare organizations adopting analytics solutions throughout the industry will fundamentally change organizational workflows. These institutions that harness advanced technologies will achieve operational efficiency while simplifying data-driven decision-making which leads to overall market expansion in life sciences analytics.

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The key players in the AI In Life science Analytics Market are Indegene Pvt. Ltd. (India), Lexalytics, Inc. (United States), Databricks, Inc. (United States), SAS Institute Inc. (United States), IQVIA Inc. (United States), International Business Machines Corporation (IBM) (United States), Sorcero, Inc. (United States), and Axtria, Inc. (United States).

IQVIA Inc. (United States):
IQVIA leads the AI In Life science Analytics Market analytics sector by applying its advanced AI and machine learning solutions to clinical trials, real-world evidence, and commercial analytics. IQVIA CORE, the company's proprietary platform, combines sophisticated data science and technology with extensive healthcare expertise to deliver practical insights for global biopharma companies and healthcare providers.

Through its massive healthcare data network of over one billion anonymized patient records the company supports evidence-based decision-making and predictive analytics capabilities. IQVIA maintains leadership in revolutionizing R&D efficiency and patient engagement through AI-powered personalized medicine by leveraging its worldwide presence and robust partnerships within pharmaceutical and biotech industries.

IBM Corporation (United States):
IBM continues to advance AI In Life science Analytics Market through its Watson Health platform despite its restructuring and partial sale because its technological legacy remains influential. The company provides sophisticated data integration and AI modelling solutions which enable life sciences firms to speed up drug discovery processes while creating optimized clinical trial designs and maintaining regulatory compliance.

IBM uses its natural language processing and machine learning capabilities to generate valuable insights from unstructured data sources such as clinical notes, research papers, and electronic medical records. IBM champions pharmaceutical advancement and global patient care through its commitment to ethical AI practices along with robust data privacy measures and scalable cloud solutions.

SAS Institute Inc. (United States):
SAS Institute leads the life sciences analytics sector with an all-encompassing artificial intelligence solution range designed specifically for clinical research activities and commercial enterprise functions as well as regulatory reporting requirements. The SAS Life Science Analytics Framework gives organizations capabilities to automate clinical trial data analysis while discovering hidden patterns and maintaining data integrity throughout the drug development process.

Leading pharmaceutical companies rely on SAS for regulatory-compliant analytics because of its extensive experience and exceptional statistical reputation. Through its investment in cloud-native artificial intelligence and machine learning technologies the company maintains its leading position in converting life sciences data into actionable real-world evidence and strategic insights.

AI In Life science Analytics Market Recent Developments and Innovations:

• In June 2024, Clinical Data Studio from Medidata integrates data streams from internal and external sources into one unified platform. Stakeholders can manage data quality through this technology enabling faster safer trials which accelerates decision-making while supporting thorough data and risk management strategies. The AI system functions to identify possible issues and track safety parameters.
• In April 2024, Salesforce and IQVIA announced their global partnership growth plans to accelerate Life Sciences Cloud development. The partnership between IQVIA OCE innovations and Salesforce's platform delivers comprehensive engagement solutions to customers. Salesforce's CRM software transforms healthcare professional and patient engagement into an efficient process through the integration of IQVIA's data and advanced analytics expertise.
• In January 2024, Cleveland Clinic and IBM research teams published their AI-based strategy to identify immunotherapy targets. The Discovery Accelerator partnership released its first peer-reviewed publication which aims to advance healthcare and life sciences research.
• In September 2023, The SAS Health platform represents SAS's new AI and analytics solution for health insurers and providers alongside public health organizations. The solution allows users to function in an adaptive environment that drives innovation in healthcare and produces superior patient care experiences as well as better health outcomes.
• In August 2023, Indegene has launched Invisage which combines AI technology with market entry strategy support for life sciences businesses. InvisageTM delivers customized outcomes for healthcare professionals by analyzing detailed HCP networks and interactions data which boosts industry engagement and performance levels.
• In March 2022, the life science customer engagement platform from IQVIA received its newest addition with the launch of OCE+. Through its OCE+ version the Orchestrated Customer Engagement (OCE) platform integrates IQVIA's Next Best recommendation engine to offer AI-driven engagement advice to healthcare professionals (HCPs). The feature upgrade enhances healthcare professional experiences and boosts productivity together with user return on investment.

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Conclusion:

The AI In Life science Analytics Market experiences substantial growth because of rising needs for precision medicine along with improved drug discovery methods and data-led clinical decisions. Artificial intelligence acts as a key instrument for converting massive amounts of data from healthcare and pharmaceutical sectors into valuable insights for diagnostics, genomics, drug development, and patient monitoring applications. North America dominates the market through substantial R&D investments and an established healthcare system while Asia Pacific experiences rapid adoption because of increasing healthcare access and ongoing digital transformation projects alongside expanded research partnerships.

Combining machine learning and natural language processing with predictive analytics boosts performance and accelerates drug time-to-market while improving patient results. Despite advancements the industry continues to struggle with data privacy issues as well as limited system interoperability while facing a critical shortage of professionals skilled in the intersection of AI and life sciences.

The Research Insights report on AI In Life science Analytics Market offers strategic guidance to various stakeholders such as biotech companies, healthcare providers, AI technology vendors, and regulatory bodies. The report shows that long-term value creation is possible through innovation adoption, ethical AI usage oversight, and robust data infrastructure investment.

The AI In Life science Analytics Market presents transformative opportunities due to its expected expansion to US$ 3.6 billion by 2030. Organizations that monitor regulatory changes and maintain transparency while building cross-disciplinary partnerships will succeed in fast-paced areas.

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