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AI in Nanotechnology Market

AI in Nanotechnology Market Size, Share & Trends Analysis Report By Type (Machine Learning Algorithms, Deep Learning Models, Natural Language Processing (NLP) Systems, Expert Systems, Robotics and Automation), By Application, By End-User Industry, By Region, And By Segment Forecasts, 2024-2031

Report ID : 2743 | Published : 2024-09-25 | Pages: 170 | Format: PDF/EXCEL

The AI in Nanotechnology Market Size is valued at USD 9.30 billion in 2023 and is predicted to reach USD 40.14 billion by the year 2031 at a 20.5% CAGR during the forecast period for 2024-2031.

ai in nanotechnology

The AI in Nanotechnology Market is emerging as a crucial segment within the broader nanotechnology and artificial intelligence fields. Integrating AI into nanotechnology enhances precision, efficiency, and scalability in various applications, such as drug delivery, material science, and electronics. One significant driver is the evolving demand for advanced and personalized medical treatments, where AI aids in designing nanoparticles for targeted drug delivery systems. Additionally, AI algorithms optimize the synthesis and characterization of nanomaterials, reducing time and costs.

During the COVID-19 pandemic, the market faced both challenges and opportunities. The disruption of supply chains and a temporary halt in research activities hindered progress. However, the pandemic also underscored the importance of advanced technologies in healthcare, leading to a surge in demand for AI-powered nanotech solutions. AI-driven nanotechnology played a crucial role in developing diagnostic tools, drug delivery systems, and antiviral coatings, demonstrating its potential in addressing global health crises. As the world recovers from the pandemic, the market is poised for accelerated growth, driven by the lessons learned and the increased focus on technological advancements in healthcare and other critical sectors.

Competitive Landscape

Some Major Key Players In The AI in Nanotechnology Market:

  • IBM Corporation
  • Google LLC
  • Microsoft Corporation
  • Intel Corporation
  • NVIDIA Corporation
  • Amazon Web Services (AWS)
  • Siemens AG
  • Thermo Fisher Scientific Inc.
  • ABB Ltd.
  • General Electric (GE)
  • Samsung Electronics Co. Ltd.
  • IBM Research
  • NanoString Technologies, Inc.
  • Accenture plc
  • Fujitsu Limited
  • Hewlett Packard Enterprise (HPE)
  • Hitachi, Ltd.
  • Agilent Technologies, Inc.
  • Oracle Corporation
  • Huawei Technologies Co., Ltd.
  • Baidu, Inc.
  • Cognex Corporation
  • Qualcomm Incorporated
  • Cisco Systems, Inc.
  • Dell Technologies Inc.
  • Other Market Players

Market Segmentation:

The AI in Nanotechnology market is segmented on the basis of type, application, and end-user industry. Based on type, the market is segmented into machine learning algorithms, deep learning models, natural language processing (NLP) systems, expert systems, robotics, and automation. By application, the market is segmented into Nanomedicine and Drug Delivery, Nanoelectronics and Optoelectronics, Nanomaterials Synthesis and Characterization, Nanorobotics and Nanomanipulation, Nanosensors and Nanodevices, Environmental Monitoring and Remediation, Nanotechnology in Energy Storage and Conversion. By end-user industry, the market is segmented into Healthcare and Biomedical, Electronics and Semiconductors, Energy and Environment, Aerospace and Defense, Manufacturing and Material Science, Consumer Electronics, and Others.

Based On Type, The Machine Learning Algorithms Segment Is Accounted As A Major Contributor To AI In The Nanotechnology Market.

The Machine Learning Algorithmscategory is expected to hold a major share of the global AI in the Nanotechnology market in 2023. Machine learning (ML) algorithms are pivotal in advancing nanotechnology applications by enabling precise analysis and prediction models for nanoscale materials and processes. These algorithms facilitate the design and discovery of new nanomaterials, optimizing properties for specific applications, such as drug delivery, electronics, and energy storage.The integration of ML algorithms enhances the efficiency and accuracy of nanoscale simulations, reducing the need for extensive experimental trials. It leads to faster innovation cycles and cost savings.

The Nanomedicine And Drug Delivery Segment Witnessed Rapid Growth.

The nanomedicine and drug delivery segment is projected to grow at a rapid rate in the global AI in Nanotechnology market owing to the integration of AI technologies that enhance precision, efficiency, and efficacy in medical treatments. AI algorithms facilitate the design and optimization of nanocarriers, improving targeted drug delivery systems, which reduce side effects and enhance therapeutic outcomes.

In The Region, The North American AI In Nanotechnology Market Holds A Significant Revenue Share.

The North American AI in Nanotechnology market holds a significant revenue share, driven by the region's robust technological infrastructure, substantial investment in research and development, and the presence of leading market players. The integration of AI with nanotechnology is revolutionizing various sectors, such as healthcare, electronics, energy, and materials science. AI's ability to analyze vast datasets, optimize nanomaterial properties, and predict outcomes accelerates innovation and application development. The region's regulatory environment also supports innovation, with policies encouraging the development and commercialization of advanced nanotechnologies. Additionally, government funding and initiatives aimed at promoting AI and nanotechnology research further boost the market. The high adoption rate of advanced technologies in North America positions it as a leader in the AI in Nanotechnology market, ensuring sustained growth and a significant revenue share.

Recent Developments:

  • In May 2024, Siemens Digital Industries Software introduced Catapult™ AI NN software, which enables the High-Level Synthesis (HLS) of neural network accelerators on Application-Specific Integrated Circuits (ASICs) and System-on-a-chip (SoCs). Catapult AI NN is a comprehensive solution that begins with an AI framework's neural network description, transforms it into C++ code, and then synthesizes it into a hardware accelerator written in Verilog or VHDL for silicon implementation.
  • In Oct 2023, Gov. Kathy Hochul unveiled the establishment of the Center for Emerging Artificial Intelligence Systems (CEAIS) at the University at Albany. This collaboration, valued at $20 million, involves UAlbany and IBM. It aims to support cutting-edge AI research initiatives by utilizing advanced cloud computing and emerging hardware from the IBM Research AI Hardware Center.

AI in Nanotechnology Market Report Scope

Report Attribute

Specifications

Market Size Value In 2023

USD 9.30 Bn

Revenue Forecast In 2031

USD 40.14 Bn

Growth Rate CAGR

CAGR of 20.5% from 2024 to 2031

Quantitative Units

Representation of revenue in US$ Bn and CAGR from 2024 to 2031

Historic Year

2019 to 2023

Forecast Year

2024-2031

Report Coverage

The forecast of revenue, the position of the company, the competitive market structure, growth prospects, and trends

Segments Covered

By Type, Application, End-User industry

Regional Scope

North America; Europe; Asia Pacific; Latin America; Middle East & Africa

Country Scope

U.S.; Canada; U.K.; Germany; China; India; Japan; Brazil; Mexico; France; Italy; Spain; South East Asia; South Korea

Competitive Landscape

IBM Corporation, Intel Corporation, Google LLC, Microsoft Corporation, General Electric (GE), Siemens AG, Thermo Fisher Scientific Inc., NVIDIA Corporation, Hewlett Packard Enterprise (HPE), Quantum Base Ltd., Cytosurge AG, Accelrys Inc. and Others.

Customization Scope

Free customization report with the procurement of the report and modifications to the regional and segment scope. Particular Geographic competitive landscape.

Pricing And Available Payment Methods

Explore pricing alternatives that are customized to your particular study requirements.

 

Chapter 1. Methodology and Scope
1.1. Research Methodology
1.2. Research Scope & Assumptions

Chapter 2. Executive Summary

Chapter 3. Global Artificial Intelligence in Nanotechnology Market Snapshot

Chapter 4. Global Artificial Intelligence in Nanotechnology Market Variables, Trends & Scope
4.1. Market Segmentation & Scope
4.2. Drivers
4.3. Challenges
4.4. Trends
4.5. Investment and Funding Analysis
4.6. Industry Analysis – Porter’s Five Forces Analysis
4.7. Competitive Landscape & Market Share Analysis
4.8. Impact of Covid-19 Analysis

Chapter 5. Market Segmentation 1: by Type Estimates & Trend Analysis
5.1. by Type & Market Share, 2019 & 2031
5.2. Market Size (Value (US$ Mn)) & Forecasts and Trend Analyses, 2019 to 2031 for the following by Type:

5.2.1. Machine Learning Algorithms
5.2.2. Deep Learning Models
5.2.3. Natural Language Processing (NLP) Systems
5.2.4. Expert Systems
5.2.5. Robotics and Automation

Chapter 6. Market Segmentation 2: by Application Estimates & Trend Analysis
6.1. by Application & Market Share, 2019 & 2031
6.2. Market Size (Value (US$ Mn)) & Forecasts and Trend Analyses, 2019 to 2031 for the following by Application:

6.2.1. Nanomedicine and Drug Delivery
6.2.2. Nanoelectronics and Optoelectronics
6.2.3. Nanomaterials Synthesis and Characterization
6.2.4. Nanorobotics and Nanomanipulation
6.2.5. Nanosensors and Nanodevices
6.2.6. Environmental Monitoring and Remediation
6.2.7. Nanotechnology in Energy Storage and Conversion

Chapter 7. Market Segmentation 3: by End-User Industry Estimates & Trend Analysis
7.1. by End-User Industry & Market Share, 2019 & 2031
7.2. Market Size (Value (US$ Mn)) & Forecasts and Trend Analyses, 2019 to 2031 for the following by End-User Industry:

7.2.1. Healthcare and Biomedical
7.2.2. Electronics and Semiconductor
7.2.3. Energy and Environment
7.2.4. Aerospace and Defense
7.2.5. Manufacturing and Material Science
7.2.6. Consumer Electronics
7.2.7. Other

Chapter 8. Artificial Intelligence in Nanotechnology Market Segmentation 4: Regional Estimates & Trend Analysis

8.1. North America
8.1.1. North America Artificial Intelligence in Nanotechnology Market Revenue (US$ Million) Estimates and Forecasts by Type, 2023-2031
8.1.2. North America Artificial Intelligence in Nanotechnology Market Revenue (US$ Million) Estimates and Forecasts by Application, 2023-2031
8.1.3. North America Artificial Intelligence in Nanotechnology Market Revenue (US$ Million) Estimates and Forecasts by End-User Industry, 2023-2031
8.1.4. North America Artificial Intelligence in Nanotechnology Market Revenue (US$ Million) Estimates and Forecasts by country, 2023-2031

8.2. Europe
8.2.1. Europe Artificial Intelligence in Nanotechnology Market Revenue (US$ Million) Estimates and Forecasts by Type, 2023-2031
8.2.2. Europe Artificial Intelligence in Nanotechnology Market Revenue (US$ Million) Estimates and Forecasts by Application, 2023-2031
8.2.3. Europe Artificial Intelligence in Nanotechnology Market Revenue (US$ Million) Estimates and Forecasts by End-User Industry, 2023-2031
8.2.4. Europe Artificial Intelligence in Nanotechnology Market Revenue (US$ Million) Estimates and Forecasts by country, 2023-2031

8.3. Asia Pacific
8.3.1. Asia Pacific Artificial Intelligence in Nanotechnology Market Revenue (US$ Million) Estimates and Forecasts by Type, 2023-2031
8.3.2. Asia Pacific Artificial Intelligence in Nanotechnology Market Revenue (US$ Million) Estimates and Forecasts by Application, 2023-2031
8.3.3. Asia-Pacific Artificial Intelligence in Nanotechnology Market Revenue (US$ Million) Estimates and Forecasts by End-User Industry, 2023-2031
8.3.4. Asia Pacific Artificial Intelligence in Nanotechnology Market Revenue (US$ Million) Estimates and Forecasts by country, 2023-2031

8.4. Latin America
8.4.1. Latin America Artificial Intelligence in Nanotechnology Market Revenue (US$ Million) Estimates and Forecasts by Type, 2023-2031
8.4.2. Latin America Artificial Intelligence in Nanotechnology Market Revenue (US$ Million) Estimates and Forecasts by Application, 2023-2031
8.4.3. Latin America Artificial Intelligence in Nanotechnology Market Revenue (US$ Million) Estimates and Forecasts by End-User Industry, 2023-2031
8.4.4. Latin America Artificial Intelligence in Nanotechnology Market Revenue (US$ Million) Estimates and Forecasts by country, 2023-2031

8.5. Middle East & Africa
8.5.1. Middle East & Africa Artificial Intelligence in Nanotechnology Market Revenue (US$ Million) Estimates and Forecasts by Type, 2023-2031
8.5.2. Middle East & Africa Artificial Intelligence in Nanotechnology Market Revenue (US$ Million) Estimates and Forecasts by Application, 2023-2031
8.5.3. Middle East & Africa Artificial Intelligence in Nanotechnology Market Revenue (US$ Million) Estimates and Forecasts by End-User Industry, 2023-2031
8.5.4. Middle East & Africa Artificial Intelligence in Nanotechnology Market Revenue (US$ Million) Estimates and Forecasts by country, 2023-2031

Chapter 9. Competitive Landscape
9.1. Major Mergers and Acquisitions/Strategic Alliances
9.2. Company Profiles

9.2.1. IBM Corporation
9.2.2. Google LLC
9.2.3. Microsoft Corporation
9.2.4. Intel Corporation
9.2.5. NVIDIA Corporation
9.2.6. Amazon Web Services (AWS)
9.2.7. Siemens AG
9.2.8. Thermo Fisher Scientific Inc.
9.2.9. ABB Ltd.
9.2.10. General Electric (GE)
9.2.11. Samsung Electronics Co. Ltd.
9.2.12. IBM Research
9.2.13. NanoString Technologies, Inc.
9.2.14. Accenture plc
9.2.15. Fujitsu Limited
9.2.16. Hewlett Packard Enterprise (HPE)
9.2.17. Hitachi, Ltd.
9.2.18. Agilent Technologies, Inc.
9.2.19. Oracle Corporation
9.2.20. Huawei Technologies Co., Ltd.
9.2.21. Baidu, Inc.
9.2.22. Cognex Corporation
9.2.23. Qualcomm Incorporated
9.2.24. Cisco Systems, Inc.
9.2.25. Dell Technologies Inc.
9.2.26. Other Prominent Players

 

Segmentation of AI in Nanotechnology Market-

AI in Nanotechnology Market By Type-

  • Machine Learning Algorithms
  • Deep Learning Models
  • Natural Language Processing (NLP) Systems
  • Expert Systems
  • Robotics and Automation

 ai in nanotechnology

AI in Nanotechnology Market By Application-

  • Nanomedicine and Drug Delivery
  • Nanoelectronics and Optoelectronics
  • Nanomaterials Synthesis and Characterization
  • Nanorobotics and Nanomanipulation
  • Nanosensors and Nanodevices
  • Environmental Monitoring and Remediation
  • Nanotechnology in Energy Storage and Conversion

AI in Nanotechnology Market By End-User Industry-

  • Healthcare and Biomedical
  • Electronics and Semiconductor
  • Energy and Environment
  • Aerospace and Defense
  • Manufacturing and Material Science
  • Consumer Electronics
  • Others

AI in Nanotechnology Market By Region-

North America-

  • The US
  • Canada
  • Mexico

Europe-

  • Germany
  • The UK
  • France
  • Italy
  • Spain
  • Rest of Europe

Asia-Pacific-

  • China
  • Japan
  • India
  • South Korea
  • South East Asia
  • Rest of Asia Pacific

Latin America-

  • Brazil
  • Argentina
  • Rest of Latin America

 Middle East & Africa-

  • GCC Countries
  • South Africa
  • Rest of Middle East and Africa

 

InsightAce Analytic follows a standard and comprehensive market research methodology focused on offering the most accurate and precise market insights. The methods followed for all our market research studies include three significant steps – primary research, secondary research, and data modeling and analysis - to derive the current market size and forecast it over the forecast period. In this study, these three steps were used iteratively to generate valid data points (minimum deviation), which were cross-validated through multiple approaches mentioned below in the data modeling section.

Through secondary research methods, information on the market under study, its peer, and the parent market was collected. This information was then entered into data models. The resulted data points and insights were then validated by primary participants.

Based on additional insights from these primary participants, more directional efforts were put into doing secondary research and optimize data models. This process was repeated till all data models used in the study produced similar results (with minimum deviation). This way, this iterative process was able to generate the most accurate market numbers and qualitative insights.

Secondary research

The secondary research sources that are typically mentioned to include, but are not limited to:

  • Company websites, financial reports, annual reports, investor presentations, broker reports, and SEC filings.
  • External and internal proprietary databases, regulatory databases, and relevant patent analysis
  • Statistical databases, National government documents, and market reports
  • Press releases, news articles, and webcasts specific to the companies operating in the market

The paid sources for secondary research like Factiva, OneSource, Hoovers, and Statista

Primary Research:

Primary research involves telephonic interviews, e-mail interactions, as well as face-to-face interviews for each market, category, segment, and subsegment across geographies

The contributors who typically take part in such a course include, but are not limited to: 

  • Industry participants: CEOs, CBO, CMO, VPs, marketing/ type managers, corporate strategy managers, and national sales managers, technical personnel, purchasing managers, resellers, and distributors.
  • Outside experts: Valuation experts, Investment bankers, research analysts specializing in specific markets
  • Key opinion leaders (KOLs) specializing in unique areas corresponding to various industry verticals
  • End-users: Vary mainly depending upon the market

Data Modeling and Analysis:

In the iterative process (mentioned above), data models received inputs from primary as well as secondary sources. But analysts working on these models were the key. They used their extensive knowledge and experience about industry and topic to make changes and fine-tuning these models as per the product/service under study.

The standard data models used while studying this market were the top-down and bottom-up approaches and the company shares analysis model. However, other methods were also used along with these – which were specific to the industry and product/service under study.

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Frequently Asked Questions

How big is the AI in Nanotechnology Market Size?

The AI in Nanotechnology Market is expected to grow at a 20.5% CAGR during the forecast period for 2024-2031.

IBM Corporation, Intel Corporation, Google LLC, Microsoft Corporation, General Electric (GE), Siemens AG, Thermo Fisher Scientific Inc., NVIDIA Corpor

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