查看购物车
  • Traditional Chinese
  • English
  • Japanese
封面
市场调查报告书
商品编码
1850257

神经网路软体：市场占有率分析、产业趋势、统计数据和成长预测（2025-2030 年）

Neural Network Software - Market Share Analysis, Industry Trends & Statistics, Growth Forecasts (2025 - 2030)
出版日期: | 出版商: Mordor Intelligence | 英文 120 Pages | 商品交期: 2-3个工作天内

价格

※ 本网页内容可能与最新版本有所差异。详细情况请与我们联繫。

简介目录

预计到 2025 年，神经网路软体市场规模将达到 347.6 亿美元，到 2030 年将达到 1,398.6 亿美元，预测期（2025-2030 年）的复合年增长率为 32.10%。

神经网路软体市场-IMG1

在自主人工智慧专案、底层模型生态系统以及降低采用门槛的云端平台的支援下，随着企业从概念验证转向全面部署，人工智慧的扩张速度正在加快。 OpenAI 的收益预计将从 2024 年 12 月的 55 亿美元飙升至 2025 年 6 月的 100 亿美元，这表明市场对大规模神经网路部署的商业需求日益增长。亚太地区是成长最快的地区，中国、日本、印度和韩国正在将大规模语言模式在地化并建构人工智慧云端。虽然软体工具仍占据大部分市场份额，但随着企业寻求整合和优化方面的专业知识，服务也在加速扩张。云端超大规模云端超大规模资料中心业者、企业软体供应商和人工智慧专家竞相在模型效率、管治和垂直解决方案方面脱颖而出，竞争日益激烈。

全球神经网路软体市场趋势与洞察

云端基础的AI平台实现了存取的民主化。

到 2025 年，企业在生成式人工智慧方面的支出将增加 30%，因为中型企业正在采用能够消除资本障碍的託管平台。红帽公司收购 Neural Magic 后，在其混合云产品中新增了一个最佳化的推理库，从而能够在私有丛集中高效部署。 Rackspace 的 AI Anywhere 服务以可预测的订阅价格打包预先建立模型，使缺乏内部专业知识的公司也能实现复杂的神经网路架构。谷歌的 Gemini 系列透过将文字到图像和视讯生成 API 整合到其标准云端主机中，进一步扩大了人工智慧的普及范围，使开发人员无需定制基础设施即可测试多模态推理。此类平台措施加快了价值实现速度，并扩大了神经网路软体在新兴企业用户中的市场。

企业对预测分析的需求日益增长

神经网路在故障预测方面达到了94%的准确率，製造业正从被动维护转向主动维护。宝马雷根斯堡工厂透过分析现有零件数据，每年可减少组装停机时间超过500分钟，这在工业领域展现了极高的投资报酬率。通用汽车透过将物联网感测器与人工智慧驱动的调度引擎结合，减少了15%的计画外停机时间，每年节省2,000万美元。金融机构也取得了类似的成果，混合深度学习模型能够侦测出98.7%的诈欺性支付。这些显着的经济效益正在加速软体采购週期，并提高了供应商对快速实施支援的期望。

深度学习 MLOps 人才短缺

仅28%采用人工智慧的公司聘用了专门从事机器学习运维（MLOps）的工程师，而75%的欧洲雇主将在2024年面临人工智慧职位空缺，这凸显了技能缺口的持续存在。儘管科技巨头目前提供认证课程以加速技能提升，但这些课程无法跟上快速变化的框架。如果缺乏足够的从业人员来实施这些模型，部署时间将会延长，业务收益将会上升，即使需求成长，短期内神经网路软体市场的获利能力也会受到限制。

細項分析

至2024年，软体框架、函式库和AutoML套件将占总收入的54.4%，凸显其作为神经网路软体市场结构性支柱的地位。虽然TensorFlow、PyTorch和JAX等核心开发套件仍然必不可少，但对缩短实验週期的承包模组的需求日益增长。随着企业将整合、调优和生命週期管理外包，包括专业咨询和託管营运在内的服务正以35.4%的复合年增长率成长。

到2024年，託管服务将占据神经网路软体市场35.4%的份额，这主要得益于云端服务供应商将人工智慧专家纳入订阅套餐，并加快产品上市速度。此外，专注于特定领域需求（例如医疗影像合规性）的专业服务团队也进一步提升了其服务份额。在预测期内，供应商之间的差异化将取决于其在特定领域的深度、基于结果的定价以及授权模式。

至2024年，公共云端将占据神经网路软体市场61.3%的份额。企业可以按需利用GPU丛集，避免前期投资。然而，主权、延迟和监管要求正在推动市场成长转向混合部署，预计到2030年，混合部署的复合年增长率将达到34.8%。

在混合架构中，资料储存在本地或私有云端中，而模型则在可扩展的公共环境中进行训练。金融服务和医疗保健提供者正在采用这种拓扑结构，以在利用云端规模的同时保护敏感资料。机密运算和联邦学习的日益普及将进一步推动对混合架构的需求，并重塑供应商的资源规划。

神经网路软体市场按组件（软体工具、平台、服务）、部署模式（云端、本地部署、混合部署）、类型（资料探勘和归檔、分析软体、其他）、应用（诈欺侦测、硬体诊断、财务预测、其他）、最终用户产业（银行、金融服务和保险、医疗保健、其他）以及地区进行细分。市场预测以美元计价。

区域分析

北美拥有成熟的创业投资生态系统、先进的云端基础设施和丰富的人才储备，预计到2024年营收将成长38.06%。 OpenAI的年度经常性收益翻倍至100亿美元，凸显了其商业性成熟度，而超大规模资料中心营运商也持续拓展其託管人工智慧业务。加拿大正利用蒙特娄和多伦多的学术丛集，但其对亚洲晶片製造的依赖限制了其自主运算能力的提升。墨西哥则利用近岸外包将神经网路解决方案整合到物流和汽车生产中，加强了区域供应链。

亚太地区预计将以35.7%的复合年增长率成长，到2030年，随着中国、日本、印度和韩国采用国家级人工智慧云端平台，神经网路软体市场规模预计将达到3,000亿美元。中国在44个重点研发领域中领先37个，并投入国家资金用于产业人工智慧升级。日本在印太地区开设了OpenAI的首个办事处，旨在满足当地对尊重语言细微差别和资料居住法的企业级GPT解决方案的需求。印度正透过政府沙盒孵化Start-Ups，而澳洲和新加坡则在安全和管治研究方面进行投资，从而创造了多元化的区域机会。

欧洲正透过其「主权人工智慧计画」（Sovereign AI 计划）追求技术自主。英伟达（NVIDIA）正向欧洲资料中心合作伙伴提供其3000百亿亿次浮点运算能力的Blackwell丛集，为受监管的人工智慧工作负载建构覆盖整个欧洲大陆的脊椎。德国的工业人工智慧云端和法国通讯业者主导的模式託管中心正在蓬勃发展。然而，人才短缺问题依然存在，75%的就业人员无法胜任人工智慧相关职位，这导致薪资上涨和跨境移民。严格的GDPR以及即将推出的人工智慧法律法规对提供管治工具的供应商有利，并正在影响采购优先事项。

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

第一章 引言

  • 研究假设和市场定义
  • 调查范围

第二章调查方法

第三章执行摘要

第四章 市场情势

  • 市场概况
  • 市场驱动因素
    • 云端基础的AI平台使神经网路普及化
    • 企业对预测分析的需求日益增长
    • 巨量资料与GPU日益普及
    • 基础模型创造了对新型工具链的需求
    • 开放原始码模型市场加速采用
    • 自主人工智慧倡议需要本地神经网路堆迭
  • 市场限制
    • 深度学习MLOps人才短缺
    • 资料隐私和管治的负担
    • GPU供应链不稳定导致成本上升
    • 训练负荷的能源和ESG审查
  • 产业价值链分析
  • 监管格局
  • 技术展望
  • 产业吸引力－波特五力分析
    • 新进入者的威胁
    • 买方的议价能力
    • 供应商的议价能力
    • 替代品的威胁
    • 竞争对手之间的竞争
  • 影响市场的宏观经济因素

第五章 市场规模及成长预测（数值）

  • 按组件
    • 软体工具
      • 框架和函式库
      • 自动机器学习平台
    • 平台（PaaS）
    • 服务
      • 託管服务
      • 专业服务
  • 透过部署模式
    • 云
    • 本地部署
    • 杂交种
  • 按类型
    • 资料探勘与归檔
    • 分析软体
    • 最佳化软体
    • 视觉化软体
  • 按用途
    • 诈欺侦测
    • 硬体诊断
    • 财务预测
    • 影像优化
    • 预测性维护
    • 自然语言处理
    • 语音辨识
    • 其他的
  • 按最终用户
    • BFSI
    • 卫生保健
    • 零售与电子商务
    • 国防和政府
    • 媒体与娱乐
    • 物流与运输
    • 能源和公共产业
    • 製造业
    • 其他终端使用者区域
  • 按地区
    • 北美洲
      • 美国
      • 加拿大
      • 墨西哥
    • 南美洲
      • 巴西
      • 阿根廷
      • 智利
      • 其他南美
    • 欧洲
      • 德国
      • 英国
      • 法国
      • 义大利
      • 西班牙
      • 俄罗斯
      • 其他欧洲地区
    • 亚太地区
      • 中国
      • 印度
      • 日本
      • 韩国
      • 马来西亚
      • 新加坡
      • 澳洲
      • 其他亚太地区
    • 中东和非洲
      • 中东
      • 阿拉伯聯合大公国
      • 沙乌地阿拉伯
      • 土耳其
      • 其他中东地区
      • 非洲
      • 南非
      • 奈及利亚
      • 其他非洲国家

第六章 竞争情势

  • 市场集中度
  • 策略趋势
  • 市占率分析
  • 公司简介
    • DataRobot Inc.
    • H2O.ai Inc.
    • C3.ai Inc.
    • Hugging Face Inc.
    • DeepMind Technologies Ltd.
    • OpenAI Inc.
    • Clarifai Inc.
    • GMDH LLC
    • Neural Designer（Artelnics SL）
    • Alyuda Research LLC
    • Neural Technologies Ltd.
    • Neuralware LLC
    • AND Corporation
    • Abacus.ai
    • OctoML Inc.
    • Databricks Inc.
    • Seldon Technologies Ltd.
    • Weights and Biases Inc.
    • Comet ML Inc.
    • Run：AI Labs Ltd.
    • Lightning AI Inc.
    • KNIME AG
    • RapidMiner Inc.
    • LatticeFlow AG
    • Pachyderm Inc.

第七章 市场机会与未来趋势

  • 閒置频段与未满足需求评估
简介目录
Product Code: 58819

The Neural Network Software Market size is estimated at USD 34.76 billion in 2025, and is expected to reach USD 139.86 billion by 2030, at a CAGR of 32.10% during the forecast period (2025-2030).

Neural Network Software - Market - IMG1

Expansion is accelerating as enterprises move from proofs of concept to full-scale rollouts, supported by sovereign-AI programs, foundation-model ecosystems, and cloud platforms that lower adoption barriers. OpenAI's revenue jump from USD 5.5 billion in December 2024 to USD 10 billion in June 2025, illustrating rising commercial demand for large-scale neural network deployments. Asia-Pacific is the fastest-growing geography because China, Japan, India, and South Korea are localizing large language models and building national AI clouds. Component trends show software tools retaining the majority share, yet services are expanding faster as enterprises seek integration and optimization expertise. Competition continues to intensify, with cloud hyperscalers, enterprise software vendors, and specialist AI firms racing to differentiate on model efficiency, governance, and vertical solutions.

Global Neural Network Software Market Trends and Insights

Cloud-based AI Platforms Democratize Access

Enterprise generative-AI spending is rising 30% in 2025 as mid-market firms adopt managed platforms that remove capital barriers. Red Hat's purchase of Neural Magic adds optimized inference libraries to its hybrid cloud suite, enabling efficient deployments within private clusters. Rackspace's AI Anywhere service packages pre-built models with predictable subscription pricing, making complex neural network architectures attainable for firms lacking in-house expertise. Google's Gemini family extends democratization by embedding text-to-image and video generation APIs inside standard cloud consoles, letting developers test multimodal inference without bespoke infrastructure. These platform moves reduce time-to-value and expand the neural network software market across new corporate adopters.

Rising Enterprise Demand for Predictive Analytics

Manufacturers are shifting from reactive to proactive maintenance as neural networks reach 94% accuracy in fault prediction. BMW's Regensburg plant prevents over 500 minutes of annual assembly disruption by analyzing existing component data, confirming strong ROI in industrial contexts. General Motors cut unexpected downtime by 15% and saved USD 20 million yearly after linking IoT sensors with AI-driven scheduling engines. Financial institutions see parallel benefits, with hybrid deep-learning models catching 98.7% of fraudulent payments. Such clear economic gains accelerate software procurement cycles and raise expectations for rapid deployment support from vendors.

Shortage of Deep-Learning MLOps Talent

Only 28% of AI adopters employ dedicated MLOps engineers, and 75% of European employers struggled to fill AI roles in 2024, spotlighting a persistent skills gap. Tech giants now deliver certification curricula to accelerate reskilling, yet curricula cannot match rapid framework changes. Without sufficient practitioners to operationalize models, deployment timelines lengthen and service revenues climb, capping short-term neural network software market gains even as demand grows.

Other drivers and restraints analyzed in the detailed report include:

  1. Growing Availability of Big Data and GPUs
  2. Foundation Models Create New Toolchain Demand
  3. Data-Privacy and Governance Burdens

For complete list of drivers and restraints, kindly check the Table Of Contents.

Segment Analysis

Software frameworks, libraries, and AutoML suites delivered 54.4% of 2024 revenue, underscoring their role as the structural backbone of the neural network software market. Core development kits such as TensorFlow, PyTorch, and JAX remain essential, yet buyers increasingly demand turnkey modules that shorten experimentation cycles. Services, including professional consulting and managed operations, are rising at 35.4% CAGR as firms outsource integration, tuning, and lifecycle management.

Managed services captured incremental gains equal to 35.4% of the neural network software market size in 2024 as cloud providers embedded AI specialists within subscription packages to accelerate time-to-production. Professional service teams respond to sector-specific needs-e.g., healthcare imaging compliance-further boosting service share. Over the forecast window, vendor differentiation will hinge on domain depth and outcome-based pricing rather than licensing alone.

Public cloud retained 61.3% of the neural network software market share in 2024 because hyperscalers offer elastic compute for training and inference. Enterprises leverage GPU clusters on demand, avoiding up-front capital outlays. Yet sovereignty, latency, and regulatory requirements are shifting growth toward hybrid deployments, forecast at 34.8% CAGR to 2030.

Hybrid architectures let data reside on-premise or in private clouds while model training happens in scalable public environments. Financial services and healthcare operators adopt this topology to protect sensitive data while exploiting cloud scale. The growing use of confidential computing and federated learning will amplify hybrid demand, reshaping resource planning for vendors.

Neural Network Software Market is Segmented by Component (Software Tools, Platform, and Services), Deployment Mode (Cloud, On-Premise, and Hybrid), Type (Data Mining and Archiving, Analytical Software, and More), Application (Fraud Detection, Hardware Diagnostics, Financial Forecasting, and More), End-User Vertical (BFSI, Healthcare, and More), and Geography. The Market Forecasts are Provided in Terms of Value (USD).

Geography Analysis

North America held 38.06% revenue in 2024 due to an established venture-capital ecosystem, advanced cloud infrastructure, and dense talent pools. OpenAI doubling annual recurring revenue to USD 10 billion highlights commercial maturity, while hyperscalers continually widen managed-AI portfolios. Canada leverages academic clusters in Montreal and Toronto, yet chip fabrication dependence on Asia limits sovereign compute ambitions. Mexico leverages nearshoring to integrate neural network solutions in logistics and automotive production, strengthening regional supply chains.

Asia-Pacific is forecast to grow at 35.7% CAGR, with the neural network software market size jumping to USD 300 billion by 2030 as China, Japan, India, and South Korea implement national AI clouds. China leads 37 of 44 critical R&D disciplines, channelling state financing toward industrial AI upgrades. Japan hosts OpenAI's first Indo-Pacific office, confirming local demand for enterprise GPT solutions that respect linguistic nuance and data-residency laws. India nurtures start-ups through government sandboxes, while Australia and Singapore invest in safety and governance research, creating diversified regional opportunities.

Europe pursues technological autonomy through sovereign-AI projects. NVIDIA is supplying over 3,000 exaflops of Blackwell clusters to European data-center partners, forming a continental spine for regulated AI workloads. Germany's industrial AI cloud and France's telco-led model-hosting hubs add depth. However, talent shortages persist, with 75% of employers unable to staff AI roles, driving wage inflation and cross-border migration. Strict GDPR and forthcoming AI-Act requirements favor vendors offering governance tooling, shaping procurement priorities.

  1. DataRobot Inc.
  2. H2O.ai Inc.
  3. C3.ai Inc.
  4. Hugging Face Inc.
  5. DeepMind Technologies Ltd.
  6. OpenAI Inc.
  7. Clarifai Inc.
  8. GMDH LLC
  9. Neural Designer (Artelnics S.L.)
  10. Alyuda Research LLC
  11. Neural Technologies Ltd.
  12. Neuralware LLC
  13. AND Corporation
  14. Abacus.ai
  15. OctoML Inc.
  16. Databricks Inc.
  17. Seldon Technologies Ltd.
  18. Weights and Biases Inc.
  19. Comet ML Inc.
  20. Run:AI Labs Ltd.
  21. Lightning AI Inc.
  22. KNIME AG
  23. RapidMiner Inc.
  24. LatticeFlow AG
  25. Pachyderm Inc.

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 LANDSCAPE

  • 4.1 Market Overview
  • 4.2 Market Drivers
    • 4.2.1 Cloud-based AI platforms democratize neural networks
    • 4.2.2 Rising enterprise demand for predictive analytics
    • 4.2.3 Growing availability of big-data and GPUs
    • 4.2.4 Foundation models create new toolchain demand
    • 4.2.5 Open-source model marketplaces accelerate adoption
    • 4.2.6 Sovereign-AI initiatives need local NN stacks
  • 4.3 Market Restraints
    • 4.3.1 Shortage of deep-learning MLOps talent
    • 4.3.2 Data-privacy and governance burdens
    • 4.3.3 GPU supply-chain volatility inflates costs
    • 4.3.4 Energy and ESG scrutiny of training workloads
  • 4.4 Industry Value Chain Analysis
  • 4.5 Regulatory Landscape
  • 4.6 Technological Outlook
  • 4.7 Industry Attractiveness - Porter's Five Forces Analysis
    • 4.7.1 Threat of New Entrants
    • 4.7.2 Bargaining Power of Buyers
    • 4.7.3 Bargaining Power of Suppliers
    • 4.7.4 Threat of Substitutes
    • 4.7.5 Intensity of Competitive Rivalry
  • 4.8 Impact of Macroeconomic Factors on the Market

5 MARKET SIZE AND GROWTH FORECASTS (VALUES)

  • 5.1 By Component
    • 5.1.1 Software Tools
      • 5.1.1.1 Frameworks and Libraries
      • 5.1.1.2 AutoML Platforms
    • 5.1.2 Platform (PaaS)
    • 5.1.3 Services
      • 5.1.3.1 Managed Services
      • 5.1.3.2 Professional Services
  • 5.2 By Deployment Mode
    • 5.2.1 Cloud
    • 5.2.2 On-premise
    • 5.2.3 Hybrid
  • 5.3 By Type
    • 5.3.1 Data Mining and Archiving
    • 5.3.2 Analytical Software
    • 5.3.3 Optimization Software
    • 5.3.4 Visualization Software
  • 5.4 By Application
    • 5.4.1 Fraud Detection
    • 5.4.2 Hardware Diagnostics
    • 5.4.3 Financial Forecasting
    • 5.4.4 Image Optimization
    • 5.4.5 Predictive Maintenance
    • 5.4.6 Natural Language Processing
    • 5.4.7 Speech Recognition
    • 5.4.8 Others
  • 5.5 By End-user Vertical
    • 5.5.1 BFSI
    • 5.5.2 Healthcare
    • 5.5.3 Retail and E-Commerce
    • 5.5.4 Defense and Government
    • 5.5.5 Media and Entertainment
    • 5.5.6 Logistics and Transportation
    • 5.5.7 Energy and Utilities
    • 5.5.8 Manufacturing
    • 5.5.9 Other End-user Verticals
  • 5.6 By Geography
    • 5.6.1 North America
      • 5.6.1.1 United States
      • 5.6.1.2 Canada
      • 5.6.1.3 Mexico
    • 5.6.2 South America
      • 5.6.2.1 Brazil
      • 5.6.2.2 Argentina
      • 5.6.2.3 Chile
      • 5.6.2.4 Rest of South America
    • 5.6.3 Europe
      • 5.6.3.1 Germany
      • 5.6.3.2 United Kingdom
      • 5.6.3.3 France
      • 5.6.3.4 Italy
      • 5.6.3.5 Spain
      • 5.6.3.6 Russia
      • 5.6.3.7 Rest of Europe
    • 5.6.4 Asia-Pacific
      • 5.6.4.1 China
      • 5.6.4.2 India
      • 5.6.4.3 Japan
      • 5.6.4.4 South Korea
      • 5.6.4.5 Malaysia
      • 5.6.4.6 Singapore
      • 5.6.4.7 Australia
      • 5.6.4.8 Rest of Asia-Pacific
    • 5.6.5 Middle East and Africa
      • 5.6.5.1 Middle East
      • 5.6.5.1.1 United Arab Emirates
      • 5.6.5.1.2 Saudi Arabia
      • 5.6.5.1.3 Turkey
      • 5.6.5.1.4 Rest of Middle East
      • 5.6.5.2 Africa
      • 5.6.5.2.1 South Africa
      • 5.6.5.2.2 Nigeria
      • 5.6.5.2.3 Rest of Africa

6 COMPETITIVE LANDSCAPE

  • 6.1 Market Concentration
  • 6.2 Strategic Moves
  • 6.3 Market Share Analysis
  • 6.4 Company Profiles (includes Global level Overview, Market level overview, Core Segments, Financials as available, Strategic Information, Market Rank/Share for key companies, Products and Services, and Recent Developments)
    • 6.4.1 DataRobot Inc.
    • 6.4.2 H2O.ai Inc.
    • 6.4.3 C3.ai Inc.
    • 6.4.4 Hugging Face Inc.
    • 6.4.5 DeepMind Technologies Ltd.
    • 6.4.6 OpenAI Inc.
    • 6.4.7 Clarifai Inc.
    • 6.4.8 GMDH LLC
    • 6.4.9 Neural Designer (Artelnics S.L.)
    • 6.4.10 Alyuda Research LLC
    • 6.4.11 Neural Technologies Ltd.
    • 6.4.12 Neuralware LLC
    • 6.4.13 AND Corporation
    • 6.4.14 Abacus.ai
    • 6.4.15 OctoML Inc.
    • 6.4.16 Databricks Inc.
    • 6.4.17 Seldon Technologies Ltd.
    • 6.4.18 Weights and Biases Inc.
    • 6.4.19 Comet ML Inc.
    • 6.4.20 Run:AI Labs Ltd.
    • 6.4.21 Lightning AI Inc.
    • 6.4.22 KNIME AG
    • 6.4.23 RapidMiner Inc.
    • 6.4.24 LatticeFlow AG
    • 6.4.25 Pachyderm Inc.

7 MARKET OPPORTUNITIES AND FUTURE TRENDS

  • 7.1 White-Space and Unmet-Need Assessment