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市场调查报告书
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1687281

AI影像识别：市场占有率分析、产业趋势与统计、成长预测（2025-2030 年）

AI Image Recognition - Market Share Analysis, Industry Trends & Statistics, Growth Forecasts (2025 - 2030)
出版日期: | 出版商: Mordor Intelligence | 英文 118 Pages | 商品交期: 2-3个工作天内

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简介目录

2025年AI影像识别市场规模预估为49.4亿美元，预估至2030年将达95.7亿美元，预测期间（2025-2030年）复合年增长率为14.14%。

AI影像辨识-市场-IMG1

人工智慧 (AI)影像识别可以识别和分类影像中的物件。作为电脑视觉的一个方面，影像识别通常与物件侦测和分类等任务交织在一起。影像识别、照片辨识和影像识别等术语经常互换使用。目前，影像识别是人工智慧（AI）最盈利的应用之一。

主要亮点

  • 要训练影像识别模型，您需要标记的图像（影片、照片、图片等）。神经网路利用精选资料集的这些训练影像来形成对各种类别的识别。一旦整理好，这些影像就会被输入到神经网路演算法中，体现影像识别模型的深度学习或机器学习性质。这种训练使卷积类神经网路能够精确定位特定的类别。训练完成后，在训练资料集以外的图像上对模型进行测试。
  • 世界各地越来越多地采用人工智慧来简化流程、提高效率和生产标准。由于人工智慧能够增强和自动化业务并丰富用户体验，因此其应用正在加速。这一激增的主要驱动力是人工智慧预期的投资经济收益（ROI）。企业认识到人工智慧增加收益、降低成本和获得竞争优势的潜力。因此，许多国家都在大力投资加速人工智慧的应用，进而扩大市场潜力。
  • 巨量资料分析涉及使用流程和技术，特别是人工智慧和机器学习，筛选大量资料集以识别模式并得出可操作的见解。这使组织能够做出更快、更明智的决策，从而提高效率、收益和利润。此外，巨量资料和人工智慧领域相互交织，相互推动对方的研究和技术进步。巨量资料技术利用了人工智慧的原理，而人工智慧则依靠大量的巨量资料资料和强大的技术来磨练其决策能力。
  • 先进的人工智慧概念，尤其是影像识别，现在对于推动各个领域的创新至关重要。这些领域的专业知识缺乏可能会阻碍新兴技术的进步和部署。随着人工智慧和深度学习在全球范围内获得关注并受到从科技巨头到灵活的中小企业等各类企业的青睐，对熟练的人工智慧工程师的需求正在飙升。然而，儘管需求日益增长，但合格的专业人员却明显短缺。
  • 人工智慧（AI）影像识别发展因其应用的多样性而涵盖整个价值链。虽然研发发挥着至关重要的作用，但人工智慧系统需要不断的训练和升级才能适应特定的应用。这确保了系统仍然具有相关性并且能够满足各个行业的需求。因此，人工智慧产品的开发和部署在不同的领域和用例中有所不同，这取决于最终用户及其行业的特定要求。

AI影像识别市场趋势

医疗保健产业成为成长最快的终端用户产业

  • 人工智慧影像识别将彻底改变医疗保健产业，并且已经展示了其潜力。透过实现准确的物体检测并不断改进影像分类和分割，人工智慧主导的影像识别正在推动医疗保健服务的创新。
  • 医疗诊断是当今市场上电脑视觉最具创新性的应用之一。利用先进的影像识别技术分析医学影像，检测多种病症，可以大大提高诊断和早期发现的准确性。这在癌症和肿瘤的检测中尤其重要，早期检测对于挽救生命和改善患者预后起着关键作用。
  • 由于技术进步和对高效、准确诊断工具的需求不断增加，医疗保健领域对人工智慧影像识别的需求正在迅速增长。人工智慧演算法经过训练可以分析 X 光、 电脑断层扫描和 MRI 等医学影像，并检测出人眼可能错过的异常情况。这有助于更早、更准确地诊断疾病。
  • 此外，人工智慧可用于自动化影像分割和量化等流程，减轻医疗专业人员的负担并提高临床工作流程的效率。人工智慧影像识别的日益普及正在推动医疗保健的转型，使其能够提供更快、更准确和个人化的患者照护。
  • 多家医疗保健解决方案公司已经展示了战略倡议，并致力于推动人工智慧影像识别的进步。 2024 年 7 月，GE Healthcare 宣布将收购 Intelligent Ultrasound Group plc 的临床人工智慧部门。智慧型超音波专门开发旨在增强超音波诊断的人工智慧影像分析工具。 GE 将把这些技术整合到其超音波产品系列中，以简化工作流程并提高临床医生的易用性。
  • 此外，GE 计划引入智慧超音波的研发专家团队，推动 GE 医疗女性超音波诊断设备和其他解决方案的人工智慧影像识别和创新方面的进步。由于这些发展及其在医疗保健领域的广泛应用，预计预测期内人工智慧影像识别的采用将会成长。

北美占有最大市场占有率

  • 美国透过对先进技术、世界一流研究机构以及多元化科学家和企业家队伍的策略性联邦投资，维持了强大的创新生态系统，促进了整个北美的人工智慧发展。
  • 人工智慧影像识别系统可以即时监控人、人群和物体，识别事故和安全风险，并促进保全服务快速反应。这种能力促使人工智慧公司开发新产品并增强现有解决方案，以满足多样化的客户需求。
  • 美国国家人工智慧安全委员会建议国会每年将人工智慧研发经费增加一倍，目标是2026财年达到320亿美元。拜登政府2023财年的联邦研发预算为2,040亿美元，较2021财年成长28%。国家人工智慧研究机构正在获得资助，以促进产学研和政府之间的合作，为影像识别公司整合人工智慧能力创造机会。
  • 北美对人工智慧技术的大量投资受到政府支持和行业特定利益的推动。该地区受益于早期技术采用者的身份，并拥有领先的基于人工智慧的影像识别公司。主要服务供应商包括AWS、IBM Watson、Google Cloud和Microsoft Azure，还有许多来自美国和加拿大的AI新兴企业。
  • 今年 3 月，Google宣布计划在 2024 年下半年在美国投资数十亿美元，以扩展其资料中心基础设施并支援云端处理和人工智慧倡议。
  • 此外，加拿大 2024 年预算宣布为人工智慧计画提供 24 亿美元的突破性资金支援。其中包括在五年内拨款 20 亿美元用于新推出的加拿大主权人工智慧运算策略。目标是为加拿大研究人员和人工智慧公司提供在全球人工智慧舞台上蓬勃发展所需的工具。
  • 此外，2023 年 9 月 27 日，科尔支持加拿大自愿行为准则，强调对先进生成人工智慧系统的负责任的开发和管理，以此强调他对人工智慧的奉献精神。这些积极的政府措施将进一步加速加拿大人工智慧影像识别技术的发展。

AI影像识别产业概况

市场主要企业不断创新其产品以确保永续的竞争优势。这种不断创新的动力正在激发参与者之间的激烈竞争。因此，竞争加剧可能会压低价格并影响整个行业的盈利。

人工智慧（AI）影像识别工具主要针对大型企业，但对于中小型企业（SME）而言仍有尚未开发的潜力。由于工具都是根据小型企业预算量身定制的，因此竞争非常激烈。

市场的主要参与者包括 Amazon Web Services Inc.（Amazon.Com Inc.）、Google LLC（Alphabet Inc.）、Clarifai Inc.

为了吸引顾客的注意力，你需要花费大量的钱做广告。拥有强大投资能力的大型公司可以利用这一点来获得竞争优势，从而增加小型市场参与者的竞争力。

透明度是这个市场的标誌，有关产品和工具的资讯都可以在网路上轻鬆取得。顾客很精明，他们清楚知道自己想要从某家公司购买什么产品。

其他福利：

  • Excel 格式的市场预测 (ME) 表
  • 3 个月的分析师支持

目录

第 1 章 简介

  • 研究假设和市场定义
  • 研究范围

第二章调查方法

第三章执行摘要

第四章 市场洞察

  • 市场概况
  • 产业吸引力－波特五力分析
    • 买家的议价能力
    • 供应商的议价能力
    • 新进入者的威胁
    • 替代品的威胁
    • 竞争程度
  • 产业价值链分析
  • COVID-19 市场影响评估

第五章 市场动态

  • 市场驱动因素
    • 人工智慧的采用率不断提高
    • 巨量资料分析的使用日益广泛
    • 扩大科技在医疗保健领域的应用
  • 市场限制
    • 缺乏技术专业知识

第六章 市场细分

  • 按类型
    • 硬体
    • 软体
    • 服务
  • 按行业
    • 车
    • BFSI
    • 卫生保健
    • 零售
    • 安全功能
    • 其他最终用户产业
  • 按地区
    • 北美洲
    • 欧洲
    • 亚洲
    • 澳洲和纽西兰
    • 拉丁美洲
    • 中东和非洲

第七章 竞争格局

  • 公司简介
    • Amazon Web Services Inc.（Amazon.Com Inc.）
    • Google LLC（Alphabet Inc.）
    • Clarifai Inc.
    • IBM Corporation
    • Intel Corporation
    • Micron Technologies Inc.
    • Microsoft Corporation
    • Nvidia Corporation
    • Qualcomm Incorporated
    • Samsung Electronics Co. Ltd.
    • Xilinx, Inc.（Advanced Micro Devices, Inc.）

第八章投资分析

第九章：市场的未来

简介目录
Product Code: 59761

The AI Image Recognition Market size is estimated at USD 4.94 billion in 2025, and is expected to reach USD 9.57 billion by 2030, at a CAGR of 14.14% during the forecast period (2025-2030).

AI Image Recognition - Market - IMG1

Artificial Intelligence (AI) Image Recognition identifies objects within images and categorizes them. As a facet of computer vision, image recognition often intertwines with tasks like object detection and classification. Terms like image recognition, photo recognition, and picture recognition are often used interchangeably. Currently, image recognition stands out as one of the most profitable applications of artificial intelligence (AI).

Key Highlights

  • Image recognition models rely on labeled images (be it videos, pictures, or photos) for training. Neural networks utilize these training images from a curated dataset to form perceptions of various classes. Once curated, these images are input into a neural network algorithm, embodying the deep or machine learning essence of the image recognition model. This training empowers convolutional neural networks to pinpoint specific classes. Post-training, the model undergoes testing with images outside its training dataset.
  • Organizations worldwide are increasingly adopting AI to streamline processes and elevate efficiency and production standards. AI's capability to enhance, automate operations, and enrich user experiences is fueling its rising adoption. A key driver behind this surge is the anticipated financial return on investment (ROI) from AI. Companies are acknowledging AI's potential to boost revenue, cut costs, and gain a competitive edge. Consequently, numerous countries are making significant investments to accelerate AI adoption, amplifying the market's potential.
  • Big data analytics harnesses processes and technologies, notably AI and machine learning, to sift through vast datasets, aiming to pinpoint patterns and derive actionable insights. This empowers organizations to make quicker, more informed decisions, boosting efficiency, revenue, and profits. Furthermore, the realms of big data and artificial intelligence are intertwined, with each driving research and technological advancements in the other. While big data technologies leverage AI principles, AI, in turn, depends on the vast datasets and robust technologies of big data to refine its decision-making prowess.
  • Advanced AI concepts, particularly image recognition, are now pivotal in spurring innovation across diverse sectors. Lacking expertise in these domains can hinder the progress and deployment of emerging technologies. As AI and deep learning find their footing worldwide, embraced by everyone from tech behemoths to nimble SMEs, the demand for skilled AI technicians has surged. Yet, this rising need is met with a notable scarcity of qualified professionals.
  • Artificial Intelligence (AI) image recognition development spans the entire value chain due to its diverse applications. While research and development (R&D) plays a pivotal role, AI systems require ongoing training and upgrades tailored to their specific applications. This ensures that the systems remain relevant and effective in meeting the demands of various industries. Consequently, both the development and deployment of AI products differ across various segments and uses, depending on the specific requirements of the end-users and the industries they serve.

Artificial Intelligence Image Recognition Market Trends

Healthcare Sector to be the Fastest End-user Vertical

  • Artificial intelligence-powered image recognition is poised to revolutionize the healthcare industry and is already demonstrating its potential. By enabling precise object detection and continuously improving image classification and segmentation, AI-driven image recognition is driving innovation in medical services.
  • Medical diagnosis represents one of the most transformative applications of computer vision in today's market. By utilizing advanced image recognition to analyze medical imagery and detect various conditions, the accuracy of diagnostics and early detection improves significantly. This is especially critical for cancer and tumor detection, where early identification plays a vital role in saving lives and enhancing patient outcomes.
  • The demand for AI image recognition in healthcare is rapidly growing, driven by advancements in technology and the increasing need for efficient and accurate diagnostic tools. AI algorithms are being trained to analyze medical images like X-rays, CT scans, MRIs, and others to detect anomalies that may be missed by the human eye. This leads to earlier and more accurate diagnoses of diseases.
  • Furthermore, AI is being leveraged to automate processes such as image segmentation and quantification, reducing the burden on healthcare professionals and enhancing the efficiency of clinical workflows. The increasing adoption of AI-powered image recognition is driving transformation in healthcare by enabling faster, more accurate, and personalized patient care.
  • Several healthcare solution-providing companies are witnessing strategic initiatives and working on bringing advancements in AI image recognition. In July 2024, GE HealthCare announced that it would acquire the clinical artificial intelligence division of Intelligent Ultrasound Group plc. Intelligent Ultrasound specializes in developing AI-powered imaging analytics tools designed to enhance ultrasound diagnostics. GE intends to integrate these technologies into its ultrasound product portfolio to streamline workflows and improve usability for clinicians.
  • Additionally, GE plans to onboard Intelligent Ultrasound's team of R&D experts to drive advancements in AI-enabled image recognition and innovation for GE HealthCare's Women's Health ultrasound devices and other solutions. With such developments and the wide range of applications in the healthcare sector, the adoption of AI image recognition is expected to grow over the projected period.

North America Holds Largest Market Share

  • The United States maintains a robust innovation ecosystem through strategic federal investments in advanced technology, world-class research institutions, and a diverse pool of scientists and entrepreneurs, driving AI development across North America.
  • AI image recognition systems enable real-time monitoring of people, crowds, and objects to identify accidents or security risks and facilitate rapid response from security services. This functionality motivates AI companies to develop new products and enhance existing solutions to address diverse customer requirements.
  • The National Security Commission on Artificial Intelligence recommended Congress double federal AI R&D funding annually, targeting USD 32 billion by fiscal 2026. The federal R&D budget under the Biden administration's fiscal 2023 plan increased by 28% from FY 2021 to USD 204 billion. The National AI Research Institutes receive funding to facilitate collaboration between industry, academia, and government entities, creating opportunities for image recognition companies to integrate AI capabilities.
  • North America's substantial investment in AI technologies stems from government support and industry-specific benefits. The region benefits from early technology adoption and hosts major AI-based image recognition companies. Key service providers include AWS, IBM Watson, Google Cloud, and Microsoft Azure, with numerous AI startups emerging from the United States and Canada.
  • In March 2024, Google announced plans to invest billions of dollars through late 2024 in the United States and internationally to expand its data center infrastructure and support cloud computing and AI initiatives.
  • Moreover, Canada's 2024 budget unveiled a USD 2.4 billion boost for AI initiatives in a landmark move. This includes a significant allocation of USD 2 billion spread over five years, dedicated to the newly introduced Canadian Sovereign AI Compute Strategy. The aim is to equip Canadian researchers and AI firms with the necessary tools to excel on the global AI stage.
  • Additionally, on September 27, 2023, Cohere underscored its dedication to AI by endorsing Canada's Voluntary Code of Conduct, which emphasizes the responsible development and management of advanced generative AI systems. Such proactive government measures are poised to accelerate further the growth of AI-driven image recognition technologies in Canada.

Artificial Intelligence Image Recognition Industry Overview

Key players in the market consistently innovate their products, securing a sustainable competitive edge. This relentless drive for innovation fuels intense competition among players. As a result, heightened competition is likely to push prices down, impacting the industry's overall profitability.

While Artificial Intelligence (AI) image recognition tools predominantly cater to large organizations, there's untapped potential in reaching out to small and medium-sized enterprises (SMEs). By tailoring tools to fit SME budgets, players intensify the competition.

Some of the major players in the market are Amazon Web Services Inc. (Amazon.Com Inc.), Google LLC (Alphabet Inc.), Clarifai Inc., IBM Corporation, and Intel Corporation, among others.

Gaining customer attention demands significant advertising expenditure. Major players, with their capacity for extensive investment, can leverage this to carve out a competitive edge, intensifying the competition for smaller market players.

Transparency is a hallmark of this market; product and tool information is readily available online. Customers are well-informed, knowing precisely what products they seek from specific companies.

Additional Benefits:

  • The market estimate (ME) sheet in Excel format
  • 3 months of analyst support

TABLE OF CONTENTS

1 INTRODUCTION

  • 1.1 Study Assumptions and Market Definition
  • 1.2 Scope of the Study

2 RESEARCH METHODOLOGY

3 EXECUTIVE SUMMARY

4 MARKET INSIGHTS

  • 4.1 Market Overview
  • 4.2 Industry Attractiveness - Porter's Five Forces Analysis
    • 4.2.1 Bargaining Power of Buyers
    • 4.2.2 Bargaining Power of Suppliers
    • 4.2.3 Threat of New Entrants
    • 4.2.4 Threat of Substitutes
    • 4.2.5 Degree of Competition
  • 4.3 Industry Value Chain Analysis
  • 4.4 Assessment of the Impact of COVID-19 on the Market

5 MARKET DYNAMICS

  • 5.1 Market Drivers
    • 5.1.1 Growing AI Adoption
    • 5.1.2 Increasing Use of Big Data Analytics
    • 5.1.3 Growing Applications of the Technology in the Healthcare Sector
  • 5.2 Market Restraints
    • 5.2.1 Lack of Technical Expertise

6 MARKET SEGMENTATION

  • 6.1 By Type
    • 6.1.1 Hardware
    • 6.1.2 Software
    • 6.1.3 Services
  • 6.2 By End-user Verticals
    • 6.2.1 Automotive
    • 6.2.2 BFSI
    • 6.2.3 Healthcare
    • 6.2.4 Retail
    • 6.2.5 Security
    • 6.2.6 Other End-user Verticals
  • 6.3 By Geography
    • 6.3.1 North America
    • 6.3.2 Europe
    • 6.3.3 Asia
    • 6.3.4 Australia and New Zealand
    • 6.3.5 Latin America
    • 6.3.6 Middle East and Africa

7 COMPETITIVE LANDSCAPE

  • 7.1 Company Profiles
    • 7.1.1 Amazon Web Services Inc. (Amazon.Com Inc.)
    • 7.1.2 Google LLC (Alphabet Inc.)
    • 7.1.3 Clarifai Inc.
    • 7.1.4 IBM Corporation
    • 7.1.5 Intel Corporation
    • 7.1.6 Micron Technologies Inc.
    • 7.1.7 Microsoft Corporation
    • 7.1.8 Nvidia Corporation
    • 7.1.9 Qualcomm Incorporated
    • 7.1.10 Samsung Electronics Co. Ltd.
    • 7.1.11 Xilinx, Inc. (Advanced Micro Devices, Inc.)

8 INVESTMENT ANALYSIS

9 FUTURE OF THE MARKET