Artificial Intelligence (AI) in Biotechnology Market Size, Share, By Offering (Hardware, and Software & Services), By Application (Health Informatics, Therapeutic Development, Epidemiological Modeling, Remote monitoring & Wearable, and Others), By Usage (Forensic Biotechnology, Clinical Biotechnology, Environmental Monitoring, and Others), and Region - Trends, Analysis and Forecast till 2034

Artificial Intelligence (AI) in Biotechnology Market Size was valued at USD 3.4 million in 2024 and is projected to grow at a CAGR of 19.4%to reach USD 17.1 million by 2034.

Artificial Intelligence (AI) is revolutionizing the biotechnology sector by accelerating research, streamlining processes, and unlocking new possibilities in various domains of life sciences. In biotechnology, AI plays a transformative role by applying machine learning (ML), deep learning, natural language processing (NLP), and other AI technologies to process and analyze vast amounts of biological and biomedical data.

The ability of AI to process and draw insights from these data sources far exceeds the capabilities of traditional methods, leading to faster discoveries, enhanced accuracy, and improved efficiency. AI has become instrumental in drug discovery and development, genomics, personalized medicine, and bioinformatics, significantly reducing the time and cost required for scientific breakthroughs.

For example, AI algorithms can predict the structure and behavior of proteins, identify potential drug targets and screen compounds for efficacy expediting the development of new treatments. Additionally, AI-driven tools for analyzing genomic data are opening new doors in understanding genetic mutations enabling more precise diagnostics, and facilitating the rise of personalized and precision medicine.

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Key Drivers of Target Market:

Rapid Advancements in Drug Discovery and Development

• AI's ability to accelerate drug discovery by predicting molecular interactions and identifying drug candidates is reshaping the pharmaceutical industry. AI-driven drug discovery platforms are also being adopted by major biotech firms, leading to increased investment in this area.
• For instance, in August 2024, a major AI-drug discovery startup, Insilico Medicine, announced a $400 million funding round to expand its AI-driven drug discovery platform.

Growing Adoption of AI in Genomics

• AI-based tools are being increasingly integrated into genetic research, especially in oncology and rare disease studies, to develop precision medicine. AI is transforming genomics by analyzing vast genetic data sets, identifying mutations, and providing insights into personalized treatments. For example, Google DeepMind’s AI model, “AlphaFold”, expanded its database to cover the human genome, aiding genomics researchers worldwide.

Increased Investment in AI-driven Bio manufacturing

• AI is being utilized to optimize biomanufacturing processes, ensuring higher efficiency and consistency in producing biologics, vaccines, and biosimilars.  
• For instance, in June 2024, Ginkgo Bioworks announced the expansion of its AI-driven cell programming platform to enhance biomanufacturing attracting significant investments from biotech companies.

Rising Demand for Personalized Medicine

• The growing prevalence of chronic diseases like cancer, diabetes, and cardiovascular diseases has fueled the demand for AI-powered solutions to customize treatments. AI is also being used to predict patients' responses to therapies, allowing for more efficient treatment plans and reducing the risk of adverse reactions. ‘
• AI's application in personalized medicine is enabling healthcare providers to tailor treatments based on individual genetic profiles, improving patient outcomes. For example, IBM Watson Health collaborated with several biotech companies to develop AI-based personalized medicine solutions targeting rare diseases.

Restrains:

Lack of Standardization in AI Models

• The absence of standardized models and standards for artificial intelligence in biotechnology results in inconsistent output and performance. Applying different AI algorithms to the same biological data results in different outcomes which makes it challenging to guarantee consistency and repeatability between researches.

Ethical Concerns and Public Trust Issues

• The use of AI in biotechnology, especially in areas like genetic research and personalized medicine, raises ethical questions related to data ownership, consent, and manipulation of genetic information.

Opportunities:

Collaborations between AI and Biotech Companies

• The increasing partnerships between AI developers and biotechnology firms are fostering innovation across drug discovery, genomics, and clinical trials. Such collaborations allow biotech companies to leverage AI’s capabilities for rapid drug screening, protein folding analysis, and genomic sequencing.

The market is segmented based on Offering, Application, Usage, and Region.

Offering Insight:

• Hardware: This segment encompasses the physical components necessary to support AI-driven biotechnology applications, including processors, GPUs (Graphics Processing Units), specialized AI chips, servers, storage devices, and network infrastructure.

• Software & Services: This segment is expected to fuel the target market growth as services include implementation services, AI platform management, training, and customization for specific biotech needs such as clinical trials, genomic research, or drug development whereas solutions enables biotech companies to analyze data, model biological processes, and simulate experiments, greatly reducing the time and cost of research.

Application Insights

• Health Informatics: AI is increasingly being used in health informatics to manage and analyze vast amounts of healthcare data. AI systems can extract insights from electronic health records (EHRs), clinical notes, lab results, and imaging data to enhance diagnostics, treatment plans, and patient care.  
• Therapeutic Development: This segment includes AI applications in drug discovery, clinical trials management, and personalized therapies, with significant contributions in areas like oncology, neurology, and infectious diseases as this segment is expected to dominate the target market growth.
• Epidemiological Modeling: AI driven epidemiological models employ machine learning to examine data from previous outbreaks, forecast future trends, and spot patterns that conventional approaches might miss. This aids in the distribution of vaccines, the allocation of resources, and the creation of public health policies.
• Remote Monitoring & Wearable’s: These technologies are used for continuous health monitoring, early disease detection, and personalized patient care without the need for hospital visits. AI's predictive capabilities allow healthcare providers to intervene early, reducing hospital readmissions and improving patient outcomes.
• Epidemiological Modeling: This category includes specialized AI uses in biotechnology that don't fit into any of the other categories. This can include the use of AI in agricultural biotechnology to maximize crop yields, the use of AI in forensic biotechnology for DNA analysis, and the use of AI in environmental biotechnology to monitor ecosystems and manage environmental issues.

Usage Insights

• Forensic Biotechnology: Artificial intelligence (AI) is used in forensic biotechnology to examine biological materials, such DNA, for use in criminal investigations and court trials. Artificial intelligence (AI) can speed up procedures like toxicological analysis, fingerprint matching, and DNA profiling, giving law enforcement access to quicker and more precise forensic data.
• Clinical Biotechnology: Artificial Intelligence is employed in clinical biotechnology to identify therapeutic targets, stratify patients, find biomarkers, and develop clinical decision support systems. AI models can help in the creation of individualized treatment programs by forecasting the course of diseases.
• Environmental Monitoring: AI-driven environmental biotechnology offers solutions for sustainable resource management, pollution control, and climate change adaptation, supporting global efforts in environmental conservation.
• Others: This section covers a range of specialized uses of artificial intelligence in biotechnology, including biofuels, aquaculture, and bioinformatics. These cutting-edge fields employ AI to enhance biological processes, create new bio-based products, and boost the effectiveness of biotechnology applications in non-traditional industries.

Regional Insights

• North America: Government initiatives like the "National AI Initiative Act" and collaborations between AI companies and research institutions fuel growth in AI applications. The region benefits from a well-developed healthcare infrastructure, advanced R&D capabilities, and high adoption rates of AI technologies across biotech sectors.
• Asia Pacific: This region is the fastest-growing region in the AI in Biotechnology Market, driven by rapid advancements in technology, a growing biotech ecosystem, and increasing healthcare needs.
• Europe: This region is a significant player in the AI in Biotechnology Market, known for its strong regulatory framework and a growing number of biotech startups integrating AI technologies.
• Latin America: This region is experiencing growing investments in biotechnology, particularly in healthcare, agriculture, and environmental biotechnology.
• Middle East & Africa: AI-driven biotech applications in this region are mainly focused on healthcare, such as improving diagnostic tools, medical imaging, and developing local biopharmaceutical production capabilities.

Artificial Intelligence (AI) in Biotechnology Market Report Scope:

Segments Covered in the Report:

This report forecasts revenue growth at global, regional, and country levels and provides an analysis of the latest industry trends and opportunities in each of the sub-segments from 2024 to 2034. For the purpose of this study segmented the target market report based on Offering, Application, Usage, and Region:

Segmentation:

By Offering:

• Hardware
• Software & Services

By Application:

• Health Informatics
• Therapeutic Development
• Epidemiological Modeling
• Remote monitoring & Wearable
• Others

By Usage:

• Forensic Biotechnology
• Clinical Biotechnology
• Environmental Monitoring
• Others

By Region:

• North America
  • U.S.
  • Canada
• Europe
  • Germany
  • UK
  • France
  • Russia
  • Italy
  • Rest of Europe
• Asia Pacific
  • China
  • India
  • Japan
  • South Korea
  • Rest of Asia Pacific
• Latin America
  • Brazil
  • Mexico
  • Rest of Latin America
• Middle East & Africa
  • GCC
  • Israel
  • South Africa
  • Rest of Middle East & Africa

The key players operating the Artificial Intelligence (AI) in Biotechnology Market include IBM Watson Health, Google DeepMind, Microsoft Genomics, NVIDIA Corporation, Insilico Medicine, Atomwise, BenevolentAI, Exscientia, Cyclica, PathAI, Zebra Medical Vision, and Recursion Pharmaceuticals.  

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• In March 2024, NVIDIA launched more than two dozen new microservices that allow healthcare enterprises worldwide to take advantage of the latest advances in generative AI from anywhere and on any cloud. Optimized NVIDIA NIMTM AI models and processes with industry-standard APIs, or application programming interfaces, are included in the new suite of NVIDIA healthcare microservices. The healthcare microservices are being used by about fifty application providers, as well as biotech and pharmaceutical firms and platforms, such as Astellas, Amgen, DNA Nexus, Iambic Therapeutics, Recursion, and Terray, and manufacturers of medical imaging software, such V7.
• According to the research article by DataToBiz, in May 2023, Artificial Intelligence is becoming more and more important in biotechnology. With the help of AI and ML technologies, the biotech sector is reinventing its procedures to provide better, quicker, and more accurate outcomes. AI and biotech are paving the way for even more breakthroughs and developments in a variety of fields, including agriculture, animal husbandry, healthcare, and pharmaceuticals.
• In July 2023, Chipmaker Nvidia will invest $50 million in Recursion Pharmaceuticals to speed up the development of the biotech firm’s artificial intelligence models for drug discovery. Stock in Recursion shot up 80% after the news. More than 2% increase in Nvidia's shares, which have contributed to stock market advances this year amid expectations for its AI processing chips.

• IBM Watson Health
• Google DeepMind
• Microsoft Genomics
• NVIDIA Corporation
• Insilico Medicine
• Atomwise
• BenevolentAI
• Exscientia
• Cyclica
• PathAI
• Zebra Medical Vision
• Recursion Pharmaceuticals

1. Research Objective and Assumption
   • Research Objectives
   • Assumptions
   • Abbreviations
2. Market Preview
   • Report Description
     • Market Definition and Scope
   • Executive Summary
     • Market Snippet, By Offerings
     • Market Snippet, By Application
     • Market Snippet, By Usage
     • Market Snippet, By Country
   • Opportunity Map Analysis
3. Market Dynamics, Regulations, and Trends Analysis
   • Market Dynamics
     • Drivers
     • Restraints
     • Market Opportunities
   • Market Trends
   • Product Launch
   • Merger and Acquisitions
   • Impact Analysis
   • PEST Analysis
   • Porter’s Analysis
4. Market Segmentation, By Offering, Forecast Period Forecast Period up to 10 Years, (US$ Mn)
   • Overview
     • Market Value and Forecast (US$ Mn), and Share Analysis (%), Forecast Period up to 10 Years
     • Y-o-Y Growth Analysis (%), Forecast Period up to 10 Years
     • Segment Trends
   • Hardware
     • Overview
     • Market Size and Forecast (US$ Mn), and Y-o-Y Growth (%), Forecast Period up to 10 Years
   • Software & Services
     • Overview
     • Market Size and Forecast (US$ Mn), and Y-o-Y Growth (%), Forecast Period up to 10 Years
     • Segment Trends
5. Market Segmentation, By Application, Forecast Period Forecast Period up to 10 Years, (US$ Mn)
   • Overview
     • Market Value and Forecast (US$ Mn), and Share Analysis (%), Forecast Period up to 10 Years
     • Y-o-Y Growth Analysis (%), Forecast Period up to 10 Years
     • Segment Trends
   • Health Informatics
     • Overview
     • Market Size and Forecast (US$ Mn), and Y-o-Y Growth (%), Forecast Period up to 10 Years
   • Therapeutic Development
     • Overview
     • Market Size and Forecast (US$ Mn), and Y-o-Y Growth (%), Forecast Period up to 10 Years
   • Epidemiological Modeling
     • Overview
     • Market Size and Forecast (US$ Mn), and Y-o-Y Growth (%), Forecast Period up to 10 Years
   • Remote monitoring & Wearable
     • Overview
     • Market Size and Forecast (US$ Mn), and Y-o-Y Growth (%), Forecast Period up to 10 Years
   • Others
     • Overview
     • Market Size and Forecast (US$ Mn), and Y-o-Y Growth (%), Forecast Period up to 10 Years
6. Market Segmentation, By Usage, Forecast Period Forecast Period up to 10 Years, (US$ Mn)
   • Overview
     • Market Value and Forecast (US$ Mn), and Share Analysis (%), Forecast Period up to 10 Years
     • Y-o-Y Growth Analysis (%), Forecast Period up to 10 Years
     • Segment Trends
   • Forensic Biotechnology
     • Overview
     • Market Size and Forecast (US$ Mn), and Y-o-Y Growth (%), Forecast Period up to 10 Years
   • Clinical Biotechnology
     • Overview
     • Market Size and Forecast (US$ Mn), and Y-o-Y Growth (%), Forecast Period up to 10 Years
   • Environmental Monitoring
     • Overview
     • Market Size and Forecast (US$ Mn), and Y-o-Y Growth (%), Forecast Period up to 10 Years
   • Others
     • Overview
     • Market Size and Forecast (US$ Mn), and Y-o-Y Growth (%), Forecast Period up to 10 Years
7. Market, By Region, Forecast Period Forecast Period up to 10 Years, (US$ Mn)
   • Overview
     • Market Value and Forecast (US$ Mn), and Share Analysis (%), Forecast Period up to 10 Years
     • Y-o-Y Growth Analysis (%), Forecast Period up to 10 Years
     • Regional Trends
   • North America
     • Market Size and Forecast (US$ Mn), By Offering, Forecast Period up to 10 Years
     • Market Size and Forecast (US$ Mn), By Application, Forecast Period up to 10 Years
     • Market Size and Forecast (US$ Mn), By Usage, Forecast Period up to 10 Years
     • Market Size and Forecast (US$ Mn), By Country, Forecast Period up to 10 Years
       • U.S
       • Canada
   • Asia Pacific
     • Market Size and Forecast (US$ Mn), By Offering, Forecast Period up to 10 Years
     • Market Size and Forecast (US$ Mn), By Application, Forecast Period up to 10 Years
     • Market Size and Forecast (US$ Mn), By Usage, Forecast Period up to 10 Years
     • Market Size and Forecast (US$ Mn), By Country, Forecast Period up to 10 Years
       • India
       • Japan
       • South Korea
       • China
       • Rest of Asia Pacific
   • Europe
     • Market Size and Forecast (US$ Mn), By Offering, Forecast Period up to 10 Years
     • Market Size and Forecast (US$ Mn), By Application, Forecast Period up to 10 Years
     • Market Size and Forecast (US$ Mn), By Usage, Forecast Period up to 10 Years
     • Market Size and Forecast (US$ Mn), By Country, Forecast Period up to 10 Years
       • UK
       • Germany
       • France
       • Russia
       • Italy
       • Rest of Europe
   • Latin America
     • Market Size and Forecast (US$ Mn), By Offering, Forecast Period up to 10 Years
     • Market Size and Forecast (US$ Mn), By Application, Forecast Period up to 10 Years
     • Market Size and Forecast (US$ Mn), By Usage, Forecast Period up to 10 Years
     • Market Size and Forecast (US$ Mn), By Country, Forecast Period up to 10 Years
       • Brazil
       • Mexico
       • Rest of Latin America
   • Middle East and Africa
     • Market Size and Forecast (US$ Mn), By Offering, Forecast Period up to 10 Years
     • Market Size and Forecast (US$ Mn), By Application, Forecast Period up to 10 Years
     • Market Size and Forecast (US$ Mn), By Usage, Forecast Period up to 10 Years
     • Market Size and Forecast (US$ Mn), By Country, Forecast Period up to 10 Years
       • GCC
       • Israel
       • South Africa
       • Rest of Middle East and Africa

Competitive Landscape

• IBM Watson Health
• Google DeepMind
• Microsoft Genomics
• NVIDIA Corporation
• Insilico Medicine
• Atomwise
• BenevolentAI
• Exscientia
• Cyclica
• PathAI
• Zebra Medical Vision
• Recursion Pharmaceuticals

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