AI in Life Science Market

The report "AI in Life Science Market by Offering (End-to-End, Niche/Point, AI Tech), Application (Drug Discovery, Clinical Trials, Quality Assurance, Regulatory), Tool (Machine Learning, NLP, Computer Vision), End User (Pharma, Biotech) - Global Forecast to 2031", is projected to grow from USD 21.58 billion in 2026 and to reach USD 69.34 billion by 2031, at a Compound Annual Growth Rate (CAGR) of 26.3% during the forecast period.

Browse 350 market data Tables and 60 Figures spread through 400 Pages and in-depth TOC on "AI in Life Science Market by Offering (End-to-End, Niche/Point, AI Tech), Application (Drug Discovery, Clinical Trials, Quality Assurance, Regulatory), Tool (Machine Learning, NLP, Computer Vision), End User (Pharma, Biotech) - Global Forecast to 2031"
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The Al in life science market is being driven by the growing convergence of advanced analytics, real-world data platforms, and intelligent automation across the pharmaceutical and healthcare value chain. Organizations are increasingly leveraging AI to enhance translational research, optimize commercial strategies, and enable data-driven decision-making across product lifecycles. The focus on AI-driven commercialization and customer-centric engagement is expected to increase demand for AI, boosting market growth as firms move to create integrated platforms that combine clinical insights with commercialization and field activities. Moreover, the emergence of agentic AI platforms is helping companies shift their operations from insight generation to autonomous execution. For instance, in April 2026, Boehringer Ingelheim (Germany) expanded its computational innovation portfolio by launching an AI accelerator in the UK’s Knowledge Quarter, backed by a capital investment of approximately USD 150 million to support AI-based pharmaceutical research and development. Likewise, in April 2026, Axtria, Inc. (US) acquired Conexus Solutions to integrate agentic AI with CRM solutions, providing a complete end-to-end AI-driven commercialization platform for life sciences firms.

The natural language processing (NLP) segment is expected to register the fastest growth in the AI in life science market during the forecast period.

Based on tool, the market for AI in life sciences has been segmented into machine learning, natural language processing (NLP), context-aware processing and computing, computer vision, image analysis, and other categories. Among these segments, NLP is expected to grow at a higher rate over the forecast period, driven by its importance in processing unstructured text across life science workflows. Recent studies indicate that NLP applications are performing exceptionally well in healthcare, as shown by a 2025 systematic review of EHR-based cognitive impairment detection (PMC11873039). The authors reported that NLP applications achieved a median sensitivity of 0.88 and a specificity of 0.96. Furthermore, the US FDA hosted a precisionFDA GenAI Challenge from January 10 to February 28, 2025, signaling increased interest among industry players and regulatory bodies in language-based AI applications in healthcare settings. Other significant developments have also occurred in this domain. For instance, Anthropic (US) announced "Claude for Healthcare" in early 2026, which includes several NLP-based capabilities. Microsoft Corporation (US) introduced Dragon Copilot in March 2025, an AI-based voice recognition technology that automates documentation tasks in healthcare organizations.

The cloud-based solution segment held the largest share of the AI in life sciences market in 2025.

Based on deployment mode, the market for AI in life sciences has been segmented into cloud-based solutions, on-premise solutions, and hybrid solutions. In 2025, the cloud-based solutions category accounts for the largest share, owing to the rising preference for scalable, flexible, and high-performance computing resources needed to handle the intensive data processing demands of AI applications. The growing preference for cloud-native solutions, which emphasize agility, efficiency, and speed in AI model deployments, is fueling demand for these services. According to statistics from ZipDo.co, 81% of biotech startups rely on cloud-based platforms to integrate multi-omics data for drug discovery. Furthermore, the cloud has become the default mode for deploying AI models, as almost all organizations are increasing their cloud spending to facilitate AI adoption. For instance, in April 2026, Amazon Web Services (US) released "Amazon Bio Discovery" - a cloud-based AI solution that enables researchers to execute drug discovery workflows and create candidate molecules at an accelerated pace.

North America registered the largest share in the global AI in life science market in 2025.

North America held the largest share of the global AI in life sciences market in 2025. In addition, the region's ability to commercialize and its early adoption of AI across the entire product cycle, including discovery, approval, post-approval, and even post-market activities, have contributed to its leadership. The use of AI by businesses in the region is not limited to R&D but is increasingly used for regulatory intelligence, market access, and patient engagement. The presence of advanced data infrastructure and interoperable frameworks that enable the easy exchange of clinical and real-world data among various players in the region is another important reason for its leading position. Moreover, North America has many AI-native life sciences startups and vendors that help it stay at the forefront of the race.

Key Players

The report profiles key players such as NVIDIA Corporation (US), Illumina, Inc. (US), Tempus AI, Inc. (US), Recursion Pharmaceuticals, Inc. (US), Dassault Systèmes SE (France), Schrödinger, Inc. (US), Data4Cure, Inc. (US), Microsoft Corporation (US), Insilico Medicine Ltd. (Hong Kong), Eurofins Discovery Services (Eurofins Scientific SE) (Luxembourg), BenevolentAI Limited (UK), Owkin, Inc. (France), PathAI, Inc. (US), Aidoc Medical Ltd. (Israel), Qure.ai Technologies Pvt. Ltd. (India), Deep Genomics Inc. (Canada), SOPHiA GENETICS SA (Switzerland), and Unlearn.AI, Inc. (US), CureAI (India).

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