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Agentic AI In Scientific Discovery And Research Market Value Analysis: What Growth Is Expected Over The Forecast Period?
The market for agentic AI in scientific discovery and research has witnessed significant expansion in recent years. This market is projected to expand from $0.26 billion in 2025 to $0.4 billion in 2026, demonstrating a compound annual growth rate (CAGR) of 57.0%. The historical growth can be ascribed to the early integration of data analytics in research, the development of machine learning platforms, the proliferation of digital research databases, the escalating complexity of research, and the pressing demand for accelerated discovery cycles.
The market size for agentic AI in scientific discovery and research is anticipated to witness substantial growth over the next few years. It is projected to expand to $2.4 billion by 2030, exhibiting a compound annual growth rate (CAGR) of 56.5%. This growth within the forecast period can be attributed to the advancement of agentic AI models, the proliferation of autonomous laboratories, increasing investment in AI research tools, the need for accelerated innovation, and the integration of AI with scientific infrastructure. Significant trends expected during this forecast period include autonomous research workflow execution, AI-driven hypothesis generation, self-directed experimental design, continuous learning research agents, and cross-domain scientific reasoning.
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Agentic AI In Scientific Discovery And Research Market Development Factors: Which Trends Are Supporting Demand?
The increasing demand for automation is projected to fuel the expansion of agentic AI in the scientific discovery and research market going forward. Automation involves employing technology to perform tasks or processes with very little human involvement. This rise in automation is attributed to its significant efficiency enhancements, enabling businesses to execute repetitive tasks more swiftly and accurately, thereby diminishing human error and decreasing operational costs. Agentic AI accelerates scientific discovery and research within automation by independently generating hypotheses, designing experiments, and optimizing processes with minimal human intervention. For instance, in September 2024, according to the International Federation of Robotics (IFR), a Germany-based non-profit organization, the World Robotics report registered 4,281,585 robots in operation globally, marking a 10% increase, with annual installations surpassing half a million units for the third consecutive year. In 2023, 70% of new robots were deployed in Asia, 17% in Europe, and 10% in the Americas. Therefore, the growing demand for automation will stimulate the growth of agentic AI in the scientific discovery and research market.
Agentic AI In Scientific Discovery And Research Market Segmentation Trends And Revenue Drivers
The agentic AI in scientific discovery and research market covered in this report is segmented –
1) By Component: Software, Services
2) By Deployment Mode: On-Premises, Cloud-Based
3) By Industry Type: Healthcare And Pharmaceuticals, Information Technology And Telecom, Manufacturing, Other Industries
Subsegments:
1) By Software: Research And Development Software, Data Analytics Software, Machine Learning Platforms, Natural Language Processing (NLP) Software, Predictive Analytics Software
2) By Services: Consulting Services, Integration Services, Managed Services, Training And Support Services
Agentic AI In Scientific Discovery And Research Market Trends Driving Strategic Industry Expansion
Leading companies operating within the agentic AI in scientific discovery and research market are concentrating on developing technologically advanced solutions, such as multi-agent systems, to boost robustness and fault tolerance. A multi-agent system (MAS) is defined as a network of autonomous agents that interact and collaborate to achieve shared or individual objectives, frequently employed to solve intricate problems through coordination and communication. For instance, in February 2025, Google LLC, a US-based IT corporation, unveiled an Agentic AI Co-Scientist. Built on Google’s Gemini 2.0 model, this Agentic AI Co-Scientist is capable of generating novel hypotheses, designing experiments, and replicating complex scientific findings in a fraction of the time it takes human researchers. Its unique strength originates from its capability to scale test-time compute, dedicating considerable computational resources during inference for more in-depth reasoning. The system utilizes a generate, debate, and evolve approach, where hypotheses are tested in simulated debates and refined through iterative feedback. This self-improving cycle progressively enhances the quality and accuracy of research hypotheses.
#Agentic AI In Scientific Discovery And Research Market Industry Leaders: Which Organizations Are Driving Competition?
Major companies operating in the agentic AI in scientific discovery and research market are Microsoft Corporation, Amazon Web Services Inc., Intel Corporation, IBM Corporation, NVIDIA Corporation, OpenAI LLC, DeepMind Technologies Limited, UiPath Inc., DataRobot Inc., Insilico Medicine Inc., Recursion Pharmaceuticals Inc., Cohere Inc., Causaly Ltd, Nimbus Therapeutics LLC, PostEra Inc., Beam AI Inc., Auransa Inc., Extensity AI Inc., Inquisite Innovations Private Limited, Valence Labs Private Limited.
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Agentic AI In Scientific Discovery And Research Market Largest Region By Revenue And Market Share
North America was the largest region in the agentic AI in scientific discovery and research market in 2025. The regions covered in the agentic AI in scientific discovery and research market report are Asia-Pacific, South East Asia, Western Europe, Eastern Europe, North America, South America, Middle East, Africa.
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Wasay has over a decade of experience in market research, data modelling, and analytics, with prior experience at GlobalData and Decision Tree Consulting Services. At The Business Research Company , he leads research operations across syndicated studies, customized consulting engagements, and the Global Market Model platform. His professional experience includes supporting organizations such as Boston Consulting Group, KPMG, and Ernst & Young. Wasay holds a degree in Electronics and Communications Engineering, postgraduate management qualifications from International Management Institute Belgium and Indian School of Business and Entrepreneurship, and completed the Integrated Program in Business Analytics from Indian Institute of Management Indore.