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1662681

自然语言理解 (NLU) 市场预测至 2030 年：按类型、产品、部署模式、技术、应用、最终用户和地区进行的全球分析

Natural Language Understanding (NLU) Market Forecasts to 2030 - Global Analysis by Type (Rule-Based, Statistical and Hybrid), Offering, Deployment Mode, Technology, Application, End User and By Geography
出版日期: | 出版商: Stratistics Market Research Consulting | 英文 200+ Pages | 商品交期: 2-3个工作天内

价格

根据 Stratistics MRC 的数据，全球自然语言理解（NLU）市场预计在 2024 年达到 224 亿美元，到 2030 年将达到 746 亿美元，预测期内的复合年增长率为 22.2%。自然语言理解 (NLU) 是人工智慧 (AI) 和自然语言处理 (NLP) 的一个分支，旨在使机器人能够以有意义的方式理解、解释和回应人类语言。它透过理解语法、语义、上下文和意图将语音和文字等非结构化语言输入转换为结构化资料。情绪分析、实体辨识、语言翻译和意图侦测都是透过 NLU 实现的任务。

人工智慧应用的采用率不断提高

人工智慧应用程式的使用日益增多，推动了自然语言理解 (NLU) 市场的发展，增加了对虚拟助理、聊天机器人和语音介面等智慧系统的需求。为了提高用户参与度和业务效率，这些应用程式依赖 NLU 来有效地读取和回应人类语言。医疗保健、零售和金融等行业使用人工智慧产品实现自动化和客製化客户互动，进一步推动了 NLU 的整合。

人类语言的复杂性

人类语言的复杂性导致难以正确捕捉不同的语言模式、惯用表达和上下文含义，从而阻碍了自然语言理解 (NLU) 市场的发展。 NLU 模型中的误解和错误可能源自于语言、语调和俚语的变化。这种复杂性需要更大的资料、更复杂的演算法和持续的训练，从而增加了开发成本并减缓了更广泛行业对 NLU 技术的采用。

提高资料可用性

透过利用大量非结构化资料（例如文字、语音和社交媒体）来训练和改进机器学习模型，不断提高资料可用性正在推动自然语言理解 (NLU) 行业的发展。由于丰富的资料，NLU 系统可以更准确地理解上下文、含义和意图。该公司正在利用这些资料来开发复杂的应用程序，如虚拟助理、聊天机器人和情绪分析工具。用户生成内容的稳定成长正在推动 NLU 产业的创新和发展。

实施成本高

高进入成本，特别是对于中小企业而言，阻碍了该行业的发展。实施先进的人工智慧模型、将其整合到现有系统中以及与维护基础设施相关的费用可能会高得令人望而却步。这样的预算障碍通常会阻碍 NLU 技术的广泛采用，尤其是在预算受限的领域，这限制了其在资料分析和客户服务自动化等领域的前景。

COVID-19 的影响

随着企业转向远端营运和数位客户支持，COVID-19 疫情加速了自然语言理解 (NLU) 技术的采用。对聊天机器人、虚拟助理和自动化服务的日益依赖导致对 NLU 解决方案的需求激增。此外，在医疗保健领域，NLU 用于患者互动和资料处理。这场疫情凸显了对高效、可扩展的人工智慧解决方案的需求，从而刺激了 NLU 市场的成长。

预测期内自动编码市场规模预计最大

由于部署 NLU 系统的速度加快以及开发复杂性降低，预计自动编码部分将在预测期内占据最大的市场占有率。这将使语音助理、聊天机器人和情感分析系统等人工智慧产品的整合更加快捷。透过提高效率和可扩展性，自动编码使公司更容易将 NLU 应用于医疗保健和客户服务等各个行业，从而促进更广泛的采用和市场扩展。

预测期内，统计部门预计以最高复合年增长率成长

预计统计部分将在预测期内实现最高成长。这些技术利用大型资料集来识别语言中的模式、机率和关係，为情绪分析、机器翻译和意图识别等 NLU 应用程式提供支援。隐马可夫模型 (HMM) 和条件随机场 (CRF) 等统计模型为理解复杂的语言结构提供了坚实的基础。这种资料驱动的方法将加速创新，使 NLU 系统更加有效和可扩展，从而得到各行业的广泛应用。

比最大的地区

由于医疗保健和客户支援等行业越来越多地采用人工智慧解决方案，预计北美将在预测期内占据最大的市场占有率。先进的聊天机器人、虚拟助理和情绪分析技术对于提高消费者参与和业务效率变得越来越必要。该地区强大的技术基础设施、对人工智慧研究的投资以及对自动化和机器学习创新的早期采用是推动北美 NLU 市场快速成长的进一步因素。

复合年增长率最高的地区

预计预测期内亚太地区将呈现最高的复合年增长率。这是因为客户服务、医疗保健和金融等多个领域都需要基于人工智慧的解决方案。随着云端运算、巨量资料分析和机器学习的发展，NLU 功能正在不断提高。聊天机器人、语音助理、自动化客户支援服务的出现以及数位转型支出的增加进一步促进了市场扩张。该地区 NLU 市场的扩张也是政府鼓励人工智慧发展的计划的结果。

提供免费客製化

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  • 公司简介
    • 对其他市场参与企业（最多 3 家公司）进行全面分析
    • 主要企业的 SWOT 分析（最多 3 家公司）
  • 地理细分
    • 根据客户兴趣对主要国家进行市场估计、预测和复合年增长率（註：基于可行性检查）
  • 竞争性基准化分析
    • 根据产品系列、地理分布和策略联盟对主要企业基准化分析

目录

第一章执行摘要

第 2 章 前言

  • 概述
  • 相关利益者
  • 研究范围
  • 调查方法
    • 资料探勘
    • 资料分析
    • 资料检验
    • 研究途径
  • 研究资讯来源
    • 主要研究资讯来源
    • 二手研究资料资讯来源
    • 先决条件

第三章 市场走势分析

  • 介绍
  • 驱动程式
  • 限制因素
  • 机会
  • 威胁
  • 技术分析
  • 应用分析
  • 最终用户分析
  • 新兴市场
  • COVID-19 的影响

第 4 章 波特五力分析

  • 供应商的议价能力
  • 买家的议价能力
  • 替代品的威胁
  • 新进入者的威胁
  • 竞争对手之间的竞争

5. 全球自然语言理解 (NLU) 市场按类型划分

  • 介绍
  • 基于规则
  • 统计数据
  • 杂交种

6. 全球自然语言理解 (NLU) 市场依产品分类

  • 介绍
  • 软体
  • 服务

7. 全球自然语言理解 (NLU) 市场以部署模式划分

  • 介绍
  • 本地
  • 云端基础

8. 全球自然语言理解 (NLU) 市场（按技术划分）

  • 介绍
  • 互动式语音应答
  • 自动编码
  • 文字分析
  • 语音分析
  • 影像和模式识别

9. 全球自然语言理解 (NLU) 市场（按应用）

  • 介绍
  • 客户体验管理
  • 虚拟助理/聊天机器人
  • 社群媒体监控
  • 情绪分析
  • 文字分类和摘要
  • 员工入职和招聘
  • 语言生成
  • 机器翻译
  • 其他的

第 10 章。

  • 介绍
  • IT 和 ITeS
  • 零售与电子商务
  • 医疗保健和生命科学
  • 运输和物流
  • 政府和公共部门
  • 媒体和娱乐
  • 製造业
  • 通讯
  • 其他的

第 11 章。

  • 介绍
  • 北美洲
    • 美国
    • 加拿大
    • 墨西哥
  • 欧洲
    • 德国
    • 英国
    • 义大利
    • 法国
    • 西班牙
    • 欧洲其他地区
  • 亚太地区
    • 日本
    • 中国
    • 印度
    • 澳洲
    • 纽西兰
    • 韩国
    • 其他亚太地区
  • 南美洲
    • 阿根廷
    • 巴西
    • 智利
    • 南美洲其他地区
  • 中东和非洲
    • 沙乌地阿拉伯
    • 阿拉伯聯合大公国
    • 卡达
    • 南非
    • 其他中东和非洲地区

第十二章 重大进展

  • 协议、伙伴关係、合作和合资企业
  • 收购与合併
  • 新产品发布
  • 业务扩展
  • 其他关键策略

第十三章 公司概况

  • OpenAI
  • Google Cloud AI
  • IBM Watson
  • Microsoft Azure Cognitive Services
  • Amazon Web Services（AWS）
  • Baidu Research
  • Facebook AI Research（FAIR）
  • Hugging Face
  • Appen
  • Cohere
  • Tractable
  • Primer
  • Eleos Health
  • PolyAI
  • Rasa Technologies ss
  • Upstage
  • Cognigy
  • Deepgram
  • Kustomer
Product Code: SMRC28542

According to Stratistics MRC, the Global Natural Language Understanding (NLU) Market is accounted for $22.4 billion in 2024 and is expected to reach $74.6 billion by 2030 growing at a CAGR of 22.2% during the forecast period. Natural Language Understanding (NLU) is an area of artificial intelligence (AI) and natural language processing (NLP) that aims to help robots understand, interpret, and respond to human language in meaningful ways. By comprehending syntax, semantics, context, and intent, it transforms unstructured language input-like voice or text-into structured data. Sentiment analysis, entity recognition, language translation, and intent detection are among the tasks made possible by NLU.

Market Dynamics:

Driver:

Growing Adoption of AI-Powered Applications

The increased usage of AI-powered applications is driving the Natural Language Understanding (NLU) market, increasing demand for intelligent systems such as virtual assistants, chatbots, and voice interfaces. In order to improve user engagement and operational efficiency, these apps rely on NLU to efficiently read and react to human language. NLU integration is further fueled by industries like healthcare, retail, and finance that use AI-powered products for automation and tailored client interactions.

Restraint:

Complexity of Human Language

The complexity of human language impedes the Natural Language Understanding (NLU) market by making it difficult to properly grasp various linguistic patterns, idiomatic idioms, and contextual meanings. Misunderstandings and mistakes in NLU models can result from variations in language, tone, and slang. Larger datasets, more complicated algorithms, and ongoing training are necessary for this complexity, which raises development costs and delays the broad industry adoption of NLU technology.

Opportunity:

Increased Data Availability

Increased data availability is driving the Natural Language Understanding (NLU) industry by supplying massive volumes of unstructured data, such as text, audio, and social media material, for training and improving machine learning models. NLU systems can comprehend context, semantics, and intent more accurately thanks to its abundance. Businesses use this data to create sophisticated apps such as virtual assistants, chatbots, and sentiment analysis tools. User-generated content's steady expansion encourages innovation and uptake in the NLU industry.

Threat:

High Implementation Costs

High implementation costs are impeding the growth of the industry, particularly for small and medium-sized organizations (SMEs). The expenditures associated with implementing sophisticated AI models, integrating them into existing systems, and maintaining infrastructure might be prohibitive. These budgetary obstacles frequently prevent NLU technology from being widely used, particularly in sectors with tight budgets, which limits its promise in fields like data analysis and customer service automation.

Covid-19 Impact:

The COVID-19 pandemic accelerated the adoption of Natural Language Understanding (NLU) technologies as businesses shifted to remote operations and digital customer support. Increased reliance on chatbots, virtual assistants, and automated services led to a surge in demand for NLU solutions. Moreover, the healthcare sector leveraged NLU for patient interaction and data processing. The pandemic highlighted the need for efficient, scalable AI solutions, driving growth in the NLU market.

The auto coding segment is expected to be the largest during the forecast period

The auto coding segment is expected to account for the largest market share during the forecast period because this speeds up the deployment of NLU systems and lowers the complexity of their development. It makes it possible to integrate AI-powered products like voice assistants, chatbots, and sentiment analysis systems more quickly. By increasing efficiency and scalability, auto coding makes it easier for companies to apply NLU in a variety of industries, such as healthcare, and customer service, which promotes wider acceptance and market expansion.

The statistical segment is expected to have the highest CAGR during the forecast period

Over the forecast period, the statistical segment is predicted to witness the highest growth as these techniques leverage large datasets to identify patterns, probabilities, and relationships within language, enhancing NLU applications like sentiment analysis, machine translation, and intent recognition. Statistical models, such as Hidden Markov Models (HMM) and Conditional Random Fields (CRF), provide robust foundations for understanding complex linguistic structures. This data-driven approach accelerates innovation, making NLU systems more effective, scalable, and widely adopted across industries.

Region with largest share:

During the forecast period, the North America region is expected to hold the largest market share because AI-powered solutions are increasingly being utilized in industries including healthcare, and customer support. Advanced chatbots, virtual assistants, and sentiment analysis technologies are becoming more necessary to increase consumer engagement and operational efficiency. The region's strong technological infrastructure, investments in AI research, and early adoption of automation and machine learning innovations are further factors contributing to North America's rapid growth in the NLU market.

Region with highest CAGR:

Over the forecast period, the Asia Pacific region is anticipated to exhibit the highest CAGR due to the need for AI-powered solutions across a range of sectors, such as customer service, healthcare, and finance. NLU's capabilities are being improved by developments in cloud computing, big data analytics, and machine learning. Market expansion is further aided by the emergence of chatbots, voice assistants, and automated customer support services as well as rising expenditures in digital transformation. The growing NLU market in the area is also a result of government programs encouraging AI development.

Key players in the market

Some of the key players in Natural Language Understanding (NLU) market include OpenAI, Google Cloud AI, IBM Watson, Microsoft Azure Cognitive Services, Amazon Web Services (AWS), Baidu Research, Facebook AI Research (FAIR), Hugging Face, Appen, Cohere, Tractable, Primer, Eleos Health, PolyAI, Rasa Technologies, Upstage, Cognigy, Deepgram and Kustomer.

Key Developments:

In June 2023, IBM announced a new collaboration with will.i.am and FYI to leverage the transformative power of secure and trustworthy generative AI for creatives.

In May 2023, IBM has established a Center of Excellence for generative AI. It stands alongside IBM Consulting's existing global AI and Automation practice, which includes 21,000 data and AI consultants who have conducted over 40,000 enterprise client engagements.

In April 2021, IBM announced new capabilities for IBM Watson designed to help businesses build trustworthy AI. These capabilities further expand Watson tools designed to help businesses govern and explain AI-led decisions, increase insight accuracy, mitigate risks and meet their privacy and compliance requirements.

Types Covered:

  • Rule-Based
  • Statistical
  • Hybrid

Offerings Covered:

  • Software
  • Services

Deployment Modes Covered:

  • On-Premises
  • Cloud-Based

Technologies Covered:

  • Interactive Voice Response
  • Auto Coding
  • Text Analytics
  • Speech Analytics
  • Image & Pattern Recognition

Applications Covered:

  • Customer Experience Management
  • Virtual Assistants/Chatbots
  • Social Media Monitoring
  • Sentiment Analysis
  • Text Classification & Summarization
  • Employee Onboarding & Recruiting
  • Language Generation
  • Machine Translation
  • Other Applications

End Users Covered:

  • IT & ITeS
  • Retail & eCommerce
  • Healthcare and Life Sciences
  • Transportation and Logistics
  • Government and Public Sector
  • Media & Entertainment
  • Manufacturing
  • Telecom
  • Other End Users

Regions Covered:

  • North America
    • US
    • Canada
    • Mexico
  • Europe
    • Germany
    • UK
    • Italy
    • France
    • Spain
    • Rest of Europe
  • Asia Pacific
    • Japan
    • China
    • India
    • Australia
    • New Zealand
    • South Korea
    • Rest of Asia Pacific
  • South America
    • Argentina
    • Brazil
    • Chile
    • Rest of South America
  • Middle East & Africa
    • Saudi Arabia
    • UAE
    • Qatar
    • South Africa
    • Rest of Middle East & Africa

What our report offers:

  • Market share assessments for the regional and country-level segments
  • Strategic recommendations for the new entrants
  • Covers Market data for the years 2022, 2023, 2024, 2026, and 2030
  • Market Trends (Drivers, Constraints, Opportunities, Threats, Challenges, Investment Opportunities, and recommendations)
  • Strategic recommendations in key business segments based on the market estimations
  • Competitive landscaping mapping the key common trends
  • Company profiling with detailed strategies, financials, and recent developments
  • Supply chain trends mapping the latest technological advancements

Free Customization Offerings:

All the customers of this report will be entitled to receive one of the following free customization options:

  • Company Profiling
    • Comprehensive profiling of additional market players (up to 3)
    • SWOT Analysis of key players (up to 3)
  • Regional Segmentation
    • Market estimations, Forecasts and CAGR of any prominent country as per the client's interest (Note: Depends on feasibility check)
  • Competitive Benchmarking
    • Benchmarking of key players based on product portfolio, geographical presence, and strategic alliances

Table of Contents

1 Executive Summary

2 Preface

  • 2.1 Abstract
  • 2.2 Stake Holders
  • 2.3 Research Scope
  • 2.4 Research Methodology
    • 2.4.1 Data Mining
    • 2.4.2 Data Analysis
    • 2.4.3 Data Validation
    • 2.4.4 Research Approach
  • 2.5 Research Sources
    • 2.5.1 Primary Research Sources
    • 2.5.2 Secondary Research Sources
    • 2.5.3 Assumptions

3 Market Trend Analysis

  • 3.1 Introduction
  • 3.2 Drivers
  • 3.3 Restraints
  • 3.4 Opportunities
  • 3.5 Threats
  • 3.6 Technology Analysis
  • 3.7 Application Analysis
  • 3.8 End User Analysis
  • 3.9 Emerging Markets
  • 3.10 Impact of Covid-19

4 Porters Five Force Analysis

  • 4.1 Bargaining power of suppliers
  • 4.2 Bargaining power of buyers
  • 4.3 Threat of substitutes
  • 4.4 Threat of new entrants
  • 4.5 Competitive rivalry

5 Global Natural Language Understanding (NLU) Market, By Type

  • 5.1 Introduction
  • 5.2 Rule-Based
  • 5.3 Statistical
  • 5.4 Hybrid

6 Global Natural Language Understanding (NLU) Market, By Offering

  • 6.1 Introduction
  • 6.2 Software
  • 6.3 Services

7 Global Natural Language Understanding (NLU) Market, By Deployment Mode

  • 7.1 Introduction
  • 7.2 On-Premises
  • 7.3 Cloud-Based

8 Global Natural Language Understanding (NLU) Market, By Technology

  • 8.1 Introduction
  • 8.2 Interactive Voice Response
  • 8.3 Auto Coding
  • 8.4 Text Analytics
  • 8.5 Speech Analytics
  • 8.6 Image & Pattern Recognition

9 Global Natural Language Understanding (NLU) Market, By Application

  • 9.1 Introduction
  • 9.2 Customer Experience Management
  • 9.3 Virtual Assistants/Chatbots
  • 9.4 Social Media Monitoring
  • 9.5 Sentiment Analysis
  • 9.6 Text Classification & Summarization
  • 9.7 Employee Onboarding & Recruiting
  • 9.8 Language Generation
  • 9.9 Machine Translation
  • 9.10 Other Applications

10 Global Natural Language Understanding (NLU) Market, By End User

  • 10.1 Introduction
  • 10.2 IT & ITeS
  • 10.3 Retail & eCommerce
  • 10.4 Healthcare and Life Sciences
  • 10.5 Transportation and Logistics
  • 10.6 Government and Public Sector
  • 10.7 Media & Entertainment
  • 10.8 Manufacturing
  • 10.9 Telecom
  • 10.10 Other End Users

11 Global Natural Language Understanding (NLU) Market, By Geography

  • 11.1 Introduction
  • 11.2 North America
    • 11.2.1 US
    • 11.2.2 Canada
    • 11.2.3 Mexico
  • 11.3 Europe
    • 11.3.1 Germany
    • 11.3.2 UK
    • 11.3.3 Italy
    • 11.3.4 France
    • 11.3.5 Spain
    • 11.3.6 Rest of Europe
  • 11.4 Asia Pacific
    • 11.4.1 Japan
    • 11.4.2 China
    • 11.4.3 India
    • 11.4.4 Australia
    • 11.4.5 New Zealand
    • 11.4.6 South Korea
    • 11.4.7 Rest of Asia Pacific
  • 11.5 South America
    • 11.5.1 Argentina
    • 11.5.2 Brazil
    • 11.5.3 Chile
    • 11.5.4 Rest of South America
  • 11.6 Middle East & Africa
    • 11.6.1 Saudi Arabia
    • 11.6.2 UAE
    • 11.6.3 Qatar
    • 11.6.4 South Africa
    • 11.6.5 Rest of Middle East & Africa

12 Key Developments

  • 12.1 Agreements, Partnerships, Collaborations and Joint Ventures
  • 12.2 Acquisitions & Mergers
  • 12.3 New Product Launch
  • 12.4 Expansions
  • 12.5 Other Key Strategies

13 Company Profiling

  • 13.1 OpenAI
  • 13.2 Google Cloud AI
  • 13.3 IBM Watson
  • 13.4 Microsoft Azure Cognitive Services
  • 13.5 Amazon Web Services (AWS)
  • 13.6 Baidu Research
  • 13.7 Facebook AI Research (FAIR)
  • 13.8 Hugging Face
  • 13.9 Appen
  • 13.10 Cohere
  • 13.11 Tractable
  • 13.12 Primer
  • 13.13 Eleos Health
  • 13.14 PolyAI
  • 13.15 Rasa Technologies ss
  • 13.16 Upstage
  • 13.17 Cognigy
  • 13.18 Deepgram
  • 13.19 Kustomer

List of Tables

  • Table 1 Global Natural Language Understanding (NLU) Market Outlook, By Region (2022-2030) ($MN)
  • Table 2 Global Natural Language Understanding (NLU) Market Outlook, By Type (2022-2030) ($MN)
  • Table 3 Global Natural Language Understanding (NLU) Market Outlook, By Rule-Based (2022-2030) ($MN)
  • Table 4 Global Natural Language Understanding (NLU) Market Outlook, By Statistical (2022-2030) ($MN)
  • Table 5 Global Natural Language Understanding (NLU) Market Outlook, By Hybrid (2022-2030) ($MN)
  • Table 6 Global Natural Language Understanding (NLU) Market Outlook, By Offering (2022-2030) ($MN)
  • Table 7 Global Natural Language Understanding (NLU) Market Outlook, By Software (2022-2030) ($MN)
  • Table 8 Global Natural Language Understanding (NLU) Market Outlook, By Services (2022-2030) ($MN)
  • Table 9 Global Natural Language Understanding (NLU) Market Outlook, By Deployment Mode (2022-2030) ($MN)
  • Table 10 Global Natural Language Understanding (NLU) Market Outlook, By On-Premises (2022-2030) ($MN)
  • Table 11 Global Natural Language Understanding (NLU) Market Outlook, By Cloud-Based (2022-2030) ($MN)
  • Table 12 Global Natural Language Understanding (NLU) Market Outlook, By Technology (2022-2030) ($MN)
  • Table 13 Global Natural Language Understanding (NLU) Market Outlook, By Interactive Voice Response (2022-2030) ($MN)
  • Table 14 Global Natural Language Understanding (NLU) Market Outlook, By Auto Coding (2022-2030) ($MN)
  • Table 15 Global Natural Language Understanding (NLU) Market Outlook, By Text Analytics (2022-2030) ($MN)
  • Table 16 Global Natural Language Understanding (NLU) Market Outlook, By Speech Analytics (2022-2030) ($MN)
  • Table 17 Global Natural Language Understanding (NLU) Market Outlook, By Image & Pattern Recognition (2022-2030) ($MN)
  • Table 18 Global Natural Language Understanding (NLU) Market Outlook, By Application (2022-2030) ($MN)
  • Table 19 Global Natural Language Understanding (NLU) Market Outlook, By Customer Experience Management (2022-2030) ($MN)
  • Table 20 Global Natural Language Understanding (NLU) Market Outlook, By Virtual Assistants/Chatbots (2022-2030) ($MN)
  • Table 21 Global Natural Language Understanding (NLU) Market Outlook, By Social Media Monitoring (2022-2030) ($MN)
  • Table 22 Global Natural Language Understanding (NLU) Market Outlook, By Sentiment Analysis (2022-2030) ($MN)
  • Table 23 Global Natural Language Understanding (NLU) Market Outlook, By Text Classification & Summarization (2022-2030) ($MN)
  • Table 24 Global Natural Language Understanding (NLU) Market Outlook, By Employee Onboarding & Recruiting (2022-2030) ($MN)
  • Table 25 Global Natural Language Understanding (NLU) Market Outlook, By Language Generation (2022-2030) ($MN)
  • Table 26 Global Natural Language Understanding (NLU) Market Outlook, By Machine Translation (2022-2030) ($MN)
  • Table 27 Global Natural Language Understanding (NLU) Market Outlook, By Other Applications (2022-2030) ($MN)
  • Table 28 Global Natural Language Understanding (NLU) Market Outlook, By End User (2022-2030) ($MN)
  • Table 29 Global Natural Language Understanding (NLU) Market Outlook, By IT & ITeS (2022-2030) ($MN)
  • Table 30 Global Natural Language Understanding (NLU) Market Outlook, By Retail & eCommerce (2022-2030) ($MN)
  • Table 31 Global Natural Language Understanding (NLU) Market Outlook, By Healthcare and Life Sciences (2022-2030) ($MN)
  • Table 32 Global Natural Language Understanding (NLU) Market Outlook, By Transportation and Logistics (2022-2030) ($MN)
  • Table 33 Global Natural Language Understanding (NLU) Market Outlook, By Government and Public Sector (2022-2030) ($MN)
  • Table 34 Global Natural Language Understanding (NLU) Market Outlook, By Media & Entertainment (2022-2030) ($MN)
  • Table 35 Global Natural Language Understanding (NLU) Market Outlook, By Manufacturing (2022-2030) ($MN)
  • Table 36 Global Natural Language Understanding (NLU) Market Outlook, By Telecom (2022-2030) ($MN)
  • Table 37 Global Natural Language Understanding (NLU) Market Outlook, By Other End Users (2022-2030) ($MN)

Note: Tables for North America, Europe, APAC, South America, and Middle East & Africa Regions are also represented in the same manner as above.