자연 언어 이해(NLU) 시장 : 규모, 점유율, 성장 분석 : 제공별, 유형별, 용도별-산업예측(-2029년)

The global natural language understanding (NLU) market is valued at USD 19.2 billion in 2024 and is estimated to reach USD 62.9 billion in 2029, registering a CAGR of 26.8% during the forecast period. The evolution of consumer expectations towards personalized and sophisticated interactions has significantly shaped the market demand for Natural Language Understanding (NLU) tools. This shift is evident in the fact that approximately 20% of Google searches are conducted via voice, highlighting the growing preference for intuitive and conversational interfaces. Businesses that fail to integrate NLU tools into their operations risk constraining the level of customer experience they can offer. NLU empowers organizations to understand and respond to the nuances of individual customer inputs, whether through voice commands, text-based queries, or social media interactions.

"By offering, the solution segment is projected to hold the largest market size during the forecast period."

The solution segment, comprising platforms and software tools & frameworks, offers comprehensive offerings and versatility. NLU platforms offer end-to-end solutions that encompass data preprocessing, model training, deployment, and analytics. This makes them highly suitable for businesses seeking integrated and scalable NLU capabilities. These platforms often come equipped with pre-built models and APIs, which expedite development and facilitate the rapid deployment of NLU applications across various domains. On the other hand, software tools & frameworks offer developers the flexibility to create customized NLU solutions that cater to specific use cases and requirements. They provide a wide range of features, including natural language processing (NLP) libraries, sentiment analysis tools, and speech recognition capabilities, empowering developers to develop innovative NLU applications.

"By type, hybrid segment is registered to grow at the highest CAGR during the forecast period."

Hybrid NLU, which combines statistical and rule-based approaches, is growing rapidly in the NLU market due to its ability to combine the strengths of both approaches. Rule-based NLU relies on predefined rules and models to interpret language, providing accuracy but limited adaptability to new data and contexts. In contrast, statistical NLU utilizes machine learning algorithms to learn patterns and relationships from data, providing flexibility but requiring significant quantities of labeled data for training. Hybrid NLU utilizes rule-based logic to interpret structured data with statistical models to handle unstructured and nuanced language input. This combination approach improves accuracy, scalability, and adaptability, making it suitable for complex use cases such as virtual assistants, sentiment analysis, and conversational AI.

"Asia Pacific is projected to witness the highest CAGR during the forecast period."

The Asia Pacific region is currently undergoing rapid expansion and is emerging as the most rapidly growing market in the natural language understanding (NLU) sector. This growth is being fueled by various factors, such as the increasing utilization of AI and machine learning technologies in industries like healthcare, finance, retail, and customer service. Countries like China, India, Japan, and South Korea are observing substantial investments in NLU research and development, resulting in the creation of sophisticated language processing capabilities customized for regional languages and dialects. Furthermore, the growing need for personalized customer experiences, effective communication platforms, and automation in businesses is propelling the adoption of NLU solutions in the Asia Pacific region.

Breakdown of primaries

In-depth interviews were conducted with Chief Executive Officers (CEOs), innovation and technology directors, system integrators, and executives from various key organizations operating in the NLU market.

• By Company: Tier I: 35%, Tier II: 45%, and Tier III: 20%
• By Designation: C-Level Executives: 35%, Directors: 25%, and Others: 40%
• By Region: North America: 45%, Europe: 30%, Asia Pacific: 20%, RoW: 5%

Major vendors offering NLU solutions and services across the globe are Microsoft (US), Google (US), IBM (US), AWS (US), Meta (US), SAS Institute, Oracle (US), Salesforce (US), OpenAI (US), SoundHound AI (US), IQVIA (US), LivePerson (US), Haptik (India), Kapiche (Australia), Rasa (US), MindMeld (US), Hugging Face (US), Conversica (US), Expert.ai (Italy), Verbio Technologies (Spain), Wolfram (US), Cortical.io (Austria), Omilia (Cyprus), Cognigy (Germany), Plasticity (US), Afforai (US), Tune AI (US), Vebrit.ai (US), Synthesys (UK), Picovoice (Canada), Symbl.ai (US), Tisane Labs (Singapore), Prosa.ai (Indonesia), Abacus.AI (US), Forethought (US).

Research Coverage

The market study covers natural language understanding (NLU) across segments. It aims at estimating the market size and the growth potential across different segments, such as offering (solutions [platform and software tools & frameowrks], solutions by deployment mode, and services), type, application, vertical and region. It includes an in-depth competitive analysis of the key players in the market, along with their company profiles, key observations related to product and business offerings, recent developments, and key market strategies.

Key Benefits of Buying the Report

The report would provide the market leaders/new entrants in this market with information on the closest approximations of the revenue numbers for the overall market for NLU and its subsegments. It would help stakeholders understand the competitive landscape and gain more insights better to position their business and plan suitable go-to-market strategies. It also helps stakeholders understand the pulse of the market and provides them with information on key market drivers, restraints, challenges, and opportunities.

The report provides insights on the following pointers:

• Analysis of key drivers (Growing consumer demand for personalized & intuitive interactions, increased productivity & reduced call duration in contact centers, ising demand for brand messaging and exponential growth of unstructured text data), restraints (High costs restrict NLU adoption to larger, well-funded organizations, data sensitivity hampers NLU market growth, necessitating robust security measures), opportunities (Advancements in NLU enable cognitive understanding for enhanced AI capabilities, emotion recognition-based NLU to unlock empathetic AI for personalized user experiences, industry-specific NLU solutions offer an opportunity to revolutionize sector operations), and challenges (Lexical ambiguity challenges NLU accuracy with multiple word meanings and bias in training data can lead to discriminatory predictions in NLU) influencing the growth of the natural language understanding (NLU) market
• Product Development/Innovation: Detailed insights on upcoming technologies, research & development activities, and new product & service launches in the natural language understanding (NLU) market.
• Market Development: Comprehensive information about lucrative markets - the report analyses the natural language understanding (NLU) market across varied regions.
• Market Diversification: Exhaustive information about new products & services, untapped geographies, recent developments, and investments in NLU market strategies; the report also helps stakeholders understand the pulse of the natural language understanding (NLU) market and provides them with information on key market drivers, restraints, challenges, and opportunities.
• Competitive Assessment: In-depth assessment of market shares, growth strategies and service offerings of leading players such as Microsoft (US), Google (US), IBM (US), AWS (US) and Oracle (US) among others in the natural language understanding (NLU) market.

TABLE OF CONTENTS

1 INTRODUCTION

• 1.1 STUDY OBJECTIVES
• 1.2 MARKET DEFINITION
  • 1.2.1 INCLUSIONS AND EXCLUSIONS
• 1.3 MARKET SCOPE
  • 1.3.1 MARKET SEGMENTATION
  • 1.3.2 YEARS CONSIDERED
• 1.4 CURRENCY CONSIDERED
• 1.5 STAKEHOLDERS

2 RESEARCH METHODOLOGY

• 2.1 RESEARCH DATA
  • 2.1.1 SECONDARY DATA
  • 2.1.2 PRIMARY DATA
    • 2.1.2.1 Breakup of primary profiles
    • 2.1.2.2 Key industry insights
• 2.2 MARKET BREAKUP AND DATA TRIANGULATION
• 2.3 MARKET SIZE ESTIMATION
  • 2.3.1 TOP-DOWN APPROACH
  • 2.3.2 BOTTOM-UP APPROACH
• 2.4 MARKET FORECAST
• 2.5 RESEARCH ASSUMPTIONS
• 2.6 RESEARCH LIMITATIONS
• 2.7 IMPLICATION OF RECESSION ON GLOBAL NATURAL LANGUAGE UNDERSTANDING MARKET

3 EXECUTIVE SUMMARY

4 PREMIUM INSIGHTS

• 4.1 ATTRACTIVE OPPORTUNITIES FOR PLAYERS IN NATURAL LANGUAGE UNDERSTANDING MARKET
• 4.2 NATURAL LANGUAGE UNDERSTANDING MARKET, BY TOP 3 VERTICALS
• 4.3 NATURAL LANGUAGE UNDERSTANDING MARKET IN NORTH AMERICA, BY OFFERING AND TOP 3 VERTICALS
• 4.4 NATURAL LANGUAGE UNDERSTANDING MARKET, BY REGION

5 MARKET OVERVIEW AND INDUSTRY TRENDS

• 5.1 INTRODUCTION
• 5.2 MARKET DYNAMICS
  • 5.2.1 DRIVERS
    • 5.2.1.1 Growing demand for personalized and intuitive interactions
    • 5.2.1.2 Focus on customer-centric approaches and operational efficiency
    • 5.2.1.3 Rising demand for brand messaging driving adoption of robust NLU solutions
    • 5.2.1.4 Exponential growth of unstructured text data fueling demand for NLU
  • 5.2.2 RESTRAINTS
    • 5.2.2.1 High implementation costs and lack of skilled professionals
    • 5.2.2.2 Data sensitivity hampering market growth and necessitating robust security measures
  • 5.2.3 OPPORTUNITIES
    • 5.2.3.1 Advancements in NLU enabling cognitive understanding for enhanced AI capabilities
    • 5.2.3.2 Emotion recognition-based NLU unlocking empathetic AI for personalized user experiences
    • 5.2.3.3 Industry-specific NLU solutions offering opportunity to revolutionize sector operations
  • 5.2.4 CHALLENGES
    • 5.2.4.1 Lexical ambiguity challenging accuracy of NLU with multiple word meanings
    • 5.2.4.2 Societal biases by language models in training data leading to discriminatory predictions in NLU
• 5.3 TRENDS/DISRUPTIONS IMPACTING CUSTOMERS' BUSINESSES
• 5.4 PRICING ANALYSIS
  • 5.4.1 AVERAGE SELLING PRICE TRENDS OF KEY PLAYERS, BY APPLICATION
  • 5.4.2 INDICATIVE PRICING ANALYSIS OF NATURAL LANGUAGE UNDERSTANDING SOLUTIONS, BY OFFERING
• 5.5 SUPPLY CHAIN ANALYSIS
• 5.6 ECOSYSTEM
  • 5.6.1 PLATFORM PROVIDERS
  • 5.6.2 SERVICE PROVIDERS
  • 5.6.3 SOFTWARE TOOL AND FRAMEWORK PROVIDERS
  • 5.6.4 REGULATORY BODIES
• 5.7 TECHNOLOGY ANALYSIS
  • 5.7.1 KEY TECHNOLOGIES
    • 5.7.1.1 Natural Language Processing (NLP)
    • 5.7.1.2 Machine Learning (ML)
    • 5.7.1.3 Deep learning
    • 5.7.1.4 Speech recognition
  • 5.7.2 COMPLEMENTARY TECHNOLOGIES
    • 5.7.2.1 Big data analytics
    • 5.7.2.2 Cloud computing
    • 5.7.2.3 IoT
  • 5.7.3 ADJACENT TECHNOLOGIES
    • 5.7.3.1 Blockchain
    • 5.7.3.2 Cybersecurity
• 5.8 PATENT ANALYSIS
  • 5.8.1 METHODOLOGY
    • 5.8.1.1 Patents type
    • 5.8.1.2 Innovation and patent applications
      • 5.8.1.2.1 Top 10 applicants in natural language understanding market
• 5.9 KEY CONFERENCES AND EVENTS, 2024-2025
• 5.10 REGULATORY LANDSCAPE
  • 5.10.1 REGULATORY BODIES, GOVERNMENT AGENCIES, AND OTHER ORGANIZATIONS
    • 5.10.1.1 North America
      • 5.10.1.1.1 US
      • 5.10.1.1.2 Canada
    • 5.10.1.2 Europe
    • 5.10.1.3 Asia Pacific
      • 5.10.1.3.1 China
      • 5.10.1.3.2 India
      • 5.10.1.3.3 Japan
      • 5.10.1.3.4 South Korea
    • 5.10.1.4 Middle East & Africa
      • 5.10.1.4.1 UAE
      • 5.10.1.4.2 KSA
    • 5.10.1.5 Latin America
      • 5.10.1.5.1 Brazil
      • 5.10.1.5.2 Mexico
• 5.11 PORTER'S FIVE FORCES ANALYSIS
  • 5.11.1 THREAT OF NEW ENTRANTS
  • 5.11.2 THREAT OF SUBSTITUTES
  • 5.11.3 BARGAINING POWER OF SUPPLIERS
  • 5.11.4 BARGAINING POWER OF BUYERS
  • 5.11.5 INTENSITY OF COMPETITION RIVALRY
• 5.12 KEY STAKEHOLDERS AND BUYING CRITERIA
  • 5.12.1 KEY STAKEHOLDERS IN BUYING PROCESS
  • 5.12.2 BUYING CRITERIA
• 5.13 NATURAL LANGUAGE UNDERSTANDING MARKET: EVOLUTION
• 5.14 TECHNOLOGY ROADMAP OF NATURAL LANGUAGE UNDERSTANDING MARKET
• 5.15 PHASES OF NATURAL LANGUAGE UNDERSTANDING
  • 5.15.1 LEXICAL ANALYSIS
  • 5.15.2 SYNTACTIC ANALYSIS (PARSING)
  • 5.15.3 SEMANTIC ANALYSIS
  • 5.15.4 DISCOURSE INTEGRATION
  • 5.15.5 PRAGMATIC ANALYSIS
• 5.16 INVESTMENT AND FUNDING SCENARIO
• 5.17 CASE STUDY ANALYSIS
  • 5.17.1 CLEARSCOPE LEVERAGED IBM WATSON FOR AUTOMATED SEO AND ACHIEVED SIGNIFICANT TRAFFIC GROWTH
  • 5.17.2 VERBIO'S CALL AUTOMATION SOLUTION REVOLUTIONIZED MAJOR SPANISH BANKS' CUSTOMER SERVICE
  • 5.17.3 CORTICAL.IO'S SEMANTICPRO EXTRACT & ANALYZE SOLUTION STREAMLINED RFP PROCESSING AND BOOSTED RESPONSE TIMES AND INSIGHTS
  • 5.17.4 OMILIA'S NLU TECHNOLOGY REVOLUTIONIZED VODAFONE GREECE'S CUSTOMER SERVICE EXPERIENCE
  • 5.17.5 EXPERT.AI AND ASSOCIATED PRESS ELEVATED NEWS DISCOVERY WITH ADVANCED NATURAL LANGUAGE UNDERSTANDING SOLUTIONS

6 NATURAL LANGUAGE UNDERSTANDING MARKET, BY OFFERING

• 6.1 INTRODUCTION
  • 6.1.1 OFFERING: NATURAL LANGUAGE UNDERSTANDING MARKET DRIVERS
• 6.2 SOLUTIONS
  • 6.2.1 DIVERSE NLU OFFERINGS DRIVE INNOVATION IN LANGUAGE UNDERSTANDING TECHNOLOGIES GLOBALLY
  • 6.2.2 PLATFORMS
  • 6.2.3 SOFTWARE TOOLS & FRAMEWORKS
• 6.3 SOLUTION, BY DEPLOYMENT MODE
  • 6.3.1 NLU MARKET SOLUTIONS ADAPT TO CLOUD AND ON-PREMISES DEPLOYMENT DEMANDS
  • 6.3.2 CLOUD
  • 6.3.3 ON-PREMISES
• 6.4 SERVICES
  • 6.4.1 NLU MARKET SERVICES OPTIMIZE ADOPTION WITH PROFESSIONAL AND MANAGED EXPERTISE
  • 6.4.2 PROFESSIONAL SERVICES
    • 6.4.2.1 Training & consulting
    • 6.4.2.2 System integration & implementation
    • 6.4.2.3 Support & maintenance
  • 6.4.3 MANAGED SERVICES

7 NATURAL LANGUAGE UNDERSTANDING MARKET, BY TYPE

• 7.1 INTRODUCTION
  • 7.1.1 TYPE: NATURAL LANGUAGE UNDERSTANDING MARKET DRIVERS
• 7.2 RULE-BASED
  • 7.2.1 RULE-BASED NLU SYSTEMS DRIVE PRECISION AND COMPLIANCE IN STRUCTURED DATA ENVIRONMENTS
• 7.3 STATISTICAL
  • 7.3.1 STATISTICAL NLU MODELS ADVANCE WITH MACHINE LEARNING FOR NUANCED LANGUAGE UNDERSTANDING
• 7.4 HYBRID
  • 7.4.1 HYBRID NLU MODELS INTEGRATE RULES AND MACHINE LEARNING FOR VERSATILE APPLICATIONS

8 NATURAL LANGUAGE UNDERSTANDING MARKET, BY APPLICATION

• 8.1 INTRODUCTION
  • 8.1.1 APPLICATION: NATURAL LANGUAGE UNDERSTANDING MARKET DRIVERS
• 8.2 CHATBOTS & VIRTUAL ASSISTANTS
  • 8.2.1 NLU-POWERED CHATBOTS AND VIRTUAL ASSISTANTS TO STREAMLINE CUSTOMER INTERACTIONS AND TASKS
• 8.3 CUSTOMER EXPERIENCE MANAGEMENT
  • 8.3.1 RISING DEMAND FOR PERSONALIZED CUSTOMER INTERACTIONS TO DRIVE NLU SOLUTIONS
• 8.4 TEXT ANALYSIS
  • 8.4.1 GROWING DEMAND FOR ACTIONABLE INSIGHTS FROM UNSTRUCTURED TEXT TO DRIVE NLU ADOPTION
• 8.5 SENTIMENT ANALYSIS
  • 8.5.1 REAL-TIME SENTIMENT INSIGHTS DRIVE STRATEGIC DECISIONS AND ENHANCE CUSTOMER ENGAGEMENT
• 8.6 IVR & MESSAGE ROUTING
  • 8.6.1 EFFICIENT CALL ROUTING AND 24/7 SERVICE DRIVE ADOPTION OF NLU-ENHANCED IVR SYSTEMS
• 8.7 DATA CAPTURE
  • 8.7.1 EFFICIENT DATA ENTRY AUTOMATION DRIVES ADOPTION OF NLU-POWERED DATA CAPTURE
• 8.8 MACHINE TRANSLATION
  • 8.8.1 IMPROVED GLOBAL COMMUNICATION THROUGH ACCURATE, CONTEXT-AWARE MACHINE TRANSLATIONS
• 8.9 OTHER APPLICATIONS

9 NATURAL LANGUAGE UNDERSTANDING MARKET, BY VERTICAL

• 9.1 INTRODUCTION
  • 9.1.1 VERTICAL: NATURAL LANGUAGE UNDERSTANDING MARKET DRIVERS
• 9.2 BFSI
  • 9.2.1 INTEGRATION OF AI-DRIVEN NLU TO ENHANCE CUSTOMER INTERACTIONS IN BFSI
  • 9.2.2 FRAUD DETECTION & PREVENTION
  • 9.2.3 ALGORITHMIC TRADING
  • 9.2.4 RISK ASSESSMENT
  • 9.2.5 COMPLIANCE & REGULATORY MONITORING
  • 9.2.6 INSURANCE CLAIMS PROCESSING
• 9.3 HEALTHCARE & LIFE SCIENCES
  • 9.3.1 NLU TO ENHANCE HEALTHCARE DIAGNOSTICS AND RESEARCH THROUGH ADVANCED DATA ANALYSIS
  • 9.3.2 CLINICAL DOCUMENTATION
  • 9.3.3 DISEASE DETECTION & SURVEILLANCE
  • 9.3.4 CLINICAL DECISION SUPPORT
  • 9.3.5 DRUG DISCOVERY & DEVELOPMENT
  • 9.3.6 HEALTHCARE DATA MINING AND QUERY UNDERSTANDING
• 9.4 RETAIL & ECOMMERCE
  • 9.4.1 GROWING DEMAND FOR PERSONALIZED SHOPPING EXPERIENCES TO DRIVE NLU ADOPTION
  • 9.4.2 CUSTOMER SUPPORT & ENGAGEMENT
  • 9.4.3 SENTIMENT ANALYSIS
  • 9.4.4 PERSONALIZED RECOMMENDATION
  • 9.4.5 SEARCH ENGINE OPTIMIZATION
  • 9.4.6 SUPPLY CHAIN MANAGEMENT
• 9.5 IT & ITES
  • 9.5.1 ADVANCED NLU SOLUTIONS TO STREAMLINE IT OPERATIONS AND CUSTOMER ENGAGEMENT
  • 9.5.2 IT HELP DESK AUTOMATION
  • 9.5.3 KNOWLEDGE MANAGEMENT
  • 9.5.4 SOFTWARE DEVELOPMENT
  • 9.5.5 PROJECT MANAGEMENT
• 9.6 TRANSPORTATION & LOGISTICS
  • 9.6.1 NLU TO TRANSFORM LOGISTICS OPERATIONS WITH REAL-TIME INTELLIGENCE AND AUTOMATION
  • 9.6.2 ROUTE OPTIMIZATION
  • 9.6.3 FLEET MANAGEMENT
  • 9.6.4 INVENTORY VISIBILITY
  • 9.6.5 CUSTOMER SUPPORT AND TRACKING
• 9.7 GOVERNMENT & PUBLIC SECTOR
  • 9.7.1 NLU TO DRIVE EFFICIENCY AND CITIZEN ENGAGEMENT IN GOVERNMENT SERVICES
  • 9.7.2 PUBLIC SERVICES
  • 9.7.3 SECURITY & INTELLIGENCE
  • 9.7.4 COMPLIANCE & LEGAL DOCUMENT MANAGEMENT
  • 9.7.5 INTELLIGENCE ANALYSIS & THREAT DETECTION
• 9.8 MEDIA & ENTERTAINMENT
  • 9.8.1 DEMAND FOR PERSONALIZED CONTENT EXPERIENCES TO DRIVE NLU ADOPTION
  • 9.8.2 CONTENT PERSONALIZATION
  • 9.8.3 NEWS & CONTENT ANALYSIS
  • 9.8.4 AUDIENCE SENTIMENT ANALYSIS
  • 9.8.5 AUTOMATED CONTENT TAGGING AND CLASSIFICATION
• 9.9 MANUFACTURING
  • 9.9.1 DEMAND FOR OPERATIONAL EFFICIENCY AND PREDICTIVE MAINTENANCE DRIVES NLU ADOPTION IN MANUFACTURING
  • 9.9.2 SUPPLY CHAIN OPTIMIZATION
  • 9.9.3 PRODUCTION OPTIMIZATION
  • 9.9.4 MAINTENANCE & PREDICTIVE ANALYTICS
  • 9.9.5 QUALITY CONTROL & DEFECT DETECTION
• 9.10 TELECOMMUNICATION
  • 9.10.1 NLU ENHANCES TELECOM EFFICIENCY BY AUTOMATING CUSTOMER SUPPORT AND NETWORK MANAGEMENT
  • 9.10.2 AUTOMATED CUSTOMER SERVICE
  • 9.10.3 NETWORK MANAGEMENT
  • 9.10.4 VIRTUAL CALL CENTERS
  • 9.10.5 VOICE COMMAND AND CONTROL
• 9.11 OTHER VERTICALS

10 NATURAL LANGUAGE UNDERSTANDING MARKET, BY REGION

• 10.1 INTRODUCTION
• 10.2 NORTH AMERICA
  • 10.2.1 MARKET DRIVERS
  • 10.2.2 RECESSION IMPACT
  • 10.2.3 US
    • 10.2.3.1 Strong presence of leading tech companies to fuel market
  • 10.2.4 CANADA
    • 10.2.4.1 Government investment in AI adoption to drive technological advancement and competitiveness
• 10.3 EUROPE
  • 10.3.1 MARKET DRIVERS
  • 10.3.2 RECESSION IMPACT
  • 10.3.3 UK
    • 10.3.3.1 UK's stringent AI regulations and supportive policies to drive NLU innovation
  • 10.3.4 GERMANY
    • 10.3.4.1 Robust R&D investments to drive market
  • 10.3.5 FRANCE
    • 10.3.5.1 Increased funding and government support to drive market
  • 10.3.6 SPAIN
    • 10.3.6.1 Collaboration between government and tech giants to drive NLU market
  • 10.3.7 ITALY
    • 10.3.7.1 Increased adoption of AI-driven solutions across Italian industries to drive market
  • 10.3.8 REST OF EUROPE
• 10.4 ASIA PACIFIC
  • 10.4.1 MARKET DRIVERS
  • 10.4.2 RECESSION IMPACT
  • 10.4.3 CHINA
    • 10.4.3.1 Rapid development of AI-powered chatbots to drive market
  • 10.4.4 JAPAN
    • 10.4.4.1 Japan's robust AI ecosystem and advanced technological infrastructure to enhance NLU adoption
  • 10.4.5 INDIA
    • 10.4.5.1 Increased government initiatives and diverse linguistic challenges to drive market
  • 10.4.6 SOUTH KOREA
    • 10.4.6.1 Robust AI infrastructure and government support to drive NLU innovation
  • 10.4.7 ASEAN
    • 10.4.7.1 Proactive AI strategies and robust digital economies to drive regional growth
  • 10.4.8 REST OF ASIA PACIFIC
• 10.5 MIDDLE EAST & AFRICA
  • 10.5.1 MARKET DRIVERS
  • 10.5.2 RECESSION IMPACT
  • 10.5.3 MIDDLE EAST
    • 10.5.3.1 UAE
      • 10.5.3.1.1 National AI strategy to drive NLU technology growth
    • 10.5.3.2 Saudi Arabia
      • 10.5.3.2.1 Vision 2030 and strategic AI partnerships to drive NLU growth
    • 10.5.3.3 Turkey
      • 10.5.3.3.1 Increasing awareness of shipping companies to effectively manage complex shipping operations
    • 10.5.3.4 Qatar
      • 10.5.3.4.1 National AI strategy and robust startup ecosystem to drive NLU market
    • 10.5.3.5 Rest of Middle East
  • 10.5.4 AFRICA
• 10.6 LATIN AMERICA
  • 10.6.1 MARKET DRIVERS
  • 10.6.2 RECESSION IMPACT
  • 10.6.3 BRAZIL
    • 10.6.3.1 National AI strategy and regulatory framework to drive NLU market
  • 10.6.4 MEXICO
    • 10.6.4.1 Government initiatives toward technological advancements to boost growth
  • 10.6.5 ARGENTINA
    • 10.6.5.1 Robust tech ecosystem and governmental support to drive growth
  • 10.6.6 REST OF LATIN AMERICA

11 COMPETITIVE LANDSCAPE

• 11.1 OVERVIEW
• 11.2 KEY PLAYER STRATEGIES
• 11.3 REVENUE ANALYSIS
• 11.4 MARKET SHARE ANALYSIS
  • 11.4.1 MARKET RANKING ANALYSIS
• 11.5 BRAND/PRODUCT COMPARATIVE ANALYSIS
• 11.6 COMPANY EVALUATION MATRIX: KEY PLAYERS, 2023
  • 11.6.1 STARS
  • 11.6.2 EMERGING LEADERS
  • 11.6.3 PERVASIVE PLAYERS
  • 11.6.4 PARTICIPANTS
  • 11.6.5 COMPANY FOOTPRINT: KEY PLAYERS, 2023
    • 11.6.5.1 Company footprint
    • 11.6.5.2 Region footprint
    • 11.6.5.3 Offering footprint
    • 11.6.5.4 Application footprint
    • 11.6.5.5 Vertical footprint
• 11.7 COMPANY EVALUATION MATRIX: STARTUPS/SMES, 2023
  • 11.7.1 PROGRESSIVE COMPANIES
  • 11.7.2 RESPONSIVE COMPANIES
  • 11.7.3 DYNAMIC COMPANIES
  • 11.7.4 STARTING BLOCKS
  • 11.7.5 COMPETITIVE BENCHMARKING: STARTUPS/SMES, 2023
    • 11.7.5.1 Detailed list of key startups/SMEs
    • 11.7.5.2 Competitive benchmarking of key startups/SMEs
• 11.8 COMPETITIVE SCENARIOS AND TRENDS
  • 11.8.1 PRODUCT LAUNCHES & ENHANCEMENTS
  • 11.8.2 DEALS
• 11.9 COMPANY VALUATION AND FINANCIAL METRICS OF KEY VENDORS

12 COMPANY PROFILES

• 12.1 INTRODUCTION
• 12.2 KEY PLAYERS
  • 12.2.1 MICROSOFT
    • 12.2.1.1 Business overview
    • 12.2.1.2 Products/Solutions/Services offered
    • 12.2.1.3 Recent developments
    • 12.2.1.4 MnM view
      • 12.2.1.4.1 Key strengths
      • 12.2.1.4.2 Strategic choices
      • 12.2.1.4.3 Weaknesses and competitive threats
  • 12.2.2 GOOGLE
    • 12.2.2.1 Business overview
    • 12.2.2.2 Products/Solutions/Services offered
    • 12.2.2.3 Recent developments
    • 12.2.2.4 MnM view
      • 12.2.2.4.1 Key strengths
      • 12.2.2.4.2 Strategic choices
      • 12.2.2.4.3 Weaknesses and competitive threats
  • 12.2.3 IBM
    • 12.2.3.1 Business overview
    • 12.2.3.2 Products/Solutions/Services offered
    • 12.2.3.3 Recent developments
    • 12.2.3.4 MnM view
      • 12.2.3.4.1 Key strengths
      • 12.2.3.4.2 Strategic choices
      • 12.2.3.4.3 Weaknesses and competitive threats
  • 12.2.4 AWS
    • 12.2.4.1 Business overview
    • 12.2.4.2 Products/Solutions/Services offered
    • 12.2.4.3 Recent developments
    • 12.2.4.4 MnM view
      • 12.2.4.4.1 Key strengths
      • 12.2.4.4.2 Strategic choices
      • 12.2.4.4.3 Weaknesses and competitive threats
  • 12.2.5 ORACLE
    • 12.2.5.1 Business overview
    • 12.2.5.2 Products/Solutions/Services offered
    • 12.2.5.3 Recent developments
    • 12.2.5.4 MnM view
      • 12.2.5.4.1 Key strengths
      • 12.2.5.4.2 Strategic choices
      • 12.2.5.4.3 Weaknesses and competitive threats
  • 12.2.6 SALESFORCE
    • 12.2.6.1 Business overview
    • 12.2.6.2 Products/Solutions/Services offered
    • 12.2.6.3 Recent developments
  • 12.2.7 SAS INSTITUTE
    • 12.2.7.1 Business overview
    • 12.2.7.2 Products/Solutions/Services offered
    • 12.2.7.3 Recent developments
  • 12.2.8 OPENAI
    • 12.2.8.1 Business overview
    • 12.2.8.2 Products/Solutions/Services offered
    • 12.2.8.3 Recent developments
  • 12.2.9 META
    • 12.2.9.1 Business overview
    • 12.2.9.2 Products/Solutions/Services offered
    • 12.2.9.3 Recent developments
  • 12.2.10 SOUNDHOUND AI
    • 12.2.10.1 Business overview
    • 12.2.10.2 Products/Solutions/Services offered
    • 12.2.10.3 Recent developments
• 12.3 KEY PLAYERS
  • 12.3.1 IQVIA
  • 12.3.2 LIVEPERSON
  • 12.3.3 HAPTIK
  • 12.3.4 KAPICHE
  • 12.3.5 RASA
  • 12.3.6 MINDMELD
  • 12.3.7 HUGGING FACE
  • 12.3.8 CONVERSICA
  • 12.3.9 EXPERT.AI
  • 12.3.10 VERBIO TECHNOLOGIES
  • 12.3.11 WOLFRAM
  • 12.3.12 CORTICAL.IO
  • 12.3.13 OMILIA
  • 12.3.14 COGNIGY
  • 12.3.15 PLASTICITY
• 12.4 STARTUPS/SMES
  • 12.4.1 AFFORAI
  • 12.4.2 TUNE AI
  • 12.4.3 VERBIT.AI
  • 12.4.4 SYNTHESYS
  • 12.4.5 PICOVOICE
  • 12.4.6 SYMBL.AI
  • 12.4.7 TISANE LABS
  • 12.4.8 PROSA.AI
  • 12.4.9 ABACUS.AI
  • 12.4.10 FORETHOUGHT

13 ADJACENT AND RELATED MARKETS

• 13.1 INTRODUCTION
• 13.2 NATURAL LANGUAGE PROCESSING MARKET-GLOBAL FORECAST TO 2028
  • 13.2.1 MARKET DEFINITION
  • 13.2.2 MARKET OVERVIEW
    • 13.2.2.1 Natural language processing market, by offering
    • 13.2.2.2 Natural language processing market, by type
    • 13.2.2.3 Natural language processing market, by application
    • 13.2.2.4 Natural language processing market, by technology
    • 13.2.2.5 Natural language processing market, by vertical
    • 13.2.2.6 Natural language processing market, by region
• 13.3 CONVERSATIONAL AI MARKET-GLOBAL FORECAST TO 2030
  • 13.3.1 MARKET DEFINITION
  • 13.3.2 MARKET OVERVIEW
    • 13.3.2.1 Conversational AI market, by offering
    • 13.3.2.2 Conversational AI market, by business function
    • 13.3.2.3 Conversational AI market, by agent type
    • 13.3.2.4 Conversational AI market, by integration mode
    • 13.3.2.5 Conversational AI market, by vertical
    • 13.3.2.6 Conversational AI market, by region

14 APPENDIX

• 14.1 DISCUSSION GUIDE
• 14.2 KNOWLEDGESTORE: MARKETSANDMARKETS' SUBSCRIPTION PORTAL
• 14.3 CUSTOMIZATION OPTIONS
• 14.4 RELATED REPORTS
• 14.5 AUTHOR DETAILS