자연어 이해(NLU) 시장 예측( -2030년) : 유형별, 제공별, 전개 방식별, 기술별, 용도별, 최종사용자별, 지역별 세계 분석

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