サマリー

世界の自然言語処理市場は、2023年に189億米ドルと評価され、予測期間中に29.3％のCAGRを記録し、2028年までに681億米ドルに達すると推定されている。企業は、ソーシャルメディアサイトや顧客とのやり取りなど、さまざまなソースから膨大な量の複雑なデータを収集している。しかし、こうしたデータは構造化されていないことが多く、そこから意味を導き出すのは困難である。NLPテクノロジーは機械に人間の言語を理解する能力を提供し、企業が非構造化データを構造化されたフォーマットに変換することを可能にする。センチメント分析技術を使用することで、NLPは人間のテキストや音声の背後にあるセンチメントを理解することもできます。この技術により、企業は顧客をよりよく理解し、カスタマーサービスへのアプローチを改善できるようになった。多くの企業は、NLPの高度なツールとアプリケーションを使用して、独自の音声駆動型インターフェースを作成することさえできるようになりました。これは、顧客からの問い合わせを理解し、タイムリーで自動化された応答を提供するのに役立っている。また、NLPテクノロジーによって、企業はビジネス・インテリジェンス・ソフトウェアの利用をさまざまな部門に拡大し、重要なデータの洞察を得ることができるようになった。
予測期間中、ソリューション部門が最大の市場規模を占めると予測される
AIソリューションの採用は、その潜在的な利点に対する人々の認識が高まるにつれて、世界的に増加している。NLPは、非構造化データの処理とマイニングを扱うAIの一分野である。テキスト、音声、動画コンテンツの分析に一般的に使用され、AIエージェントが人間の言語のニュアンスや文脈を理解できるようにする。IBM、マイクロソフト、グーグルなどの企業は、センチメント分析、テキスト分類、要約、音声認識などの革新的な機能を備えたNLPソリューションを提供している。一部のベンダーは、市場の個々のユーザーの需要に合わせてカスタマイズされた機能を持つ、洗練されたNLPソフトウェア・ツールやAPIを提供している。
タイプ別では、ハイブリッド・セグメントが予測期間中に最も高いCAGRで成長すると予測されている。
ハイブリッドNLPは、より正確な言語理解と処理を提供するために、ルールベースと統計的NLP手法の長所を組み合わせた高度なアプローチである。この融合は、事前に定義された言語ルールを統計モデルやML手法と統合することで、膨大なデータのより良い分析を可能にします。ハイブリッドNLPは、特にユーザーが適切なデータセットを持っておらず、最小限のデータセットで統計的手法を実装する必要がある場合に、いくつかの利点を提供します。例えば、文法修正システムでは、モジュールが複数の単語表現を識別し、次にルールベースの手法を使って誤ったパターンを識別し、正しいパターンを生成する。ハイブリッドNLPは、正確なルールベース処理が不可欠でありながら、統計的アプローチの柔軟性や適応性からも恩恵を受けるようなシナリオで特に効果的である。ハイブリッドNLPは、チャットボット、バーチャルアシスタント、感情分析、テキスト分類など、さまざまなNLPアプリケーションで広く使用されており、言語理解と生成の多様な課題に取り組むための汎用的なソリューションを提供しています。また、eCRM、センチメント分析、機械翻訳、レポート生成などにも利用されている。
ソリューション別では、ソフトウェア・ツール分野が予測期間中に最大の市場規模を占めると予測されている。
NLP市場で提供されるソフトウェア・ツールは、SDK、API、フレームワークの形態で提供され、ユーザーが既存のソフトウェアにNLP機能を統合することを可能にする。NLP市場は、柔軟なソフトウェアとSDKキットによる著しい発展を目撃している。このようなソフトウェア・ツールは、テキスト分析や音声分析など、さまざまなタスクを実行するために他のソリューションとともに使用される。また、NLUベースのビジネス・アプリケーションは、通信業界やその他の業界において、対話型音声応答（IVR）やバーチャル・アシスタントの利用が増加している。統計的技術により、ベンダーは自己学習機能を統合し、システムがユーザーのコマンドに基づいて学習し続け、将来的にそれに従って行動することを保証する。このような技術は、精度を向上させ、システムが適切な応答を提供するのにも役立っている。例えば、GoogleはCloud Natural Language APIを提供しており、エンティティ抽出、感情分析、構文分析、分類アプリケーションに重点を置いている。
アジア太平洋地域は、予測期間中に最も高いCAGRを目撃すると予測されている。
アジア太平洋地域の自然言語処理市場には、中国、日本、インド、ASEAN諸国、スリランカ、バングラデシュ、ミャンマーなどの国々で構成されるRest of Asia Pacificなどの国が含まれる。同地域では、AIやML技術の商業化とともに、政府のイニシアティブ、政策、投資により、NLPソフトウェアやサービスの採用が大きく伸びると予想されている。同地域は世界人口の50％以上を擁するため、AIによってもたらされるような技術シフトは同地域の将来を形成すると予想される。中国、インド、日本など多くのアジア諸国は、情報集約的なAI技術を活用しており、会話AIは主要な技術トレンドのひとつである。
プライマリーの内訳
自然言語処理市場で事業を展開する様々な主要組織の最高経営責任者（CEO）、イノベーション・技術責任者、システム・インテグレーター、経営幹部に対して詳細なインタビューを実施。
 企業別：ティアI：35％、ティアII：45％、ティアIII：20
 役職別Cレベルのエグゼクティブ：35%, 取締役：25%、その他40%
 地域別北米：45%、アジア太平洋：30%、ヨーロッパ：20%、RoW：5
世界中で自然言語処理ソリューションとサービスを提供している主なベンダーは、IBM（米国）、Microsoft（米国）、Google（米国）、AWS（米国）、Meta（米国）、3M（米国）、Baidu（中国）、Apple（米国）、SAS Institute（米国）、IQVIA（英国）、Oracle（米国）、セールスフォース（米）、OpenAI（米）、Inbenta（米）、LivePerson（米）、SoundHound AI（米）、MindMeld（米）、Veritone（米）、Dolbey（米）、Automated Insights（米）、Bitext（米）、Conversica（米）、UiPath（米）、Addepto（米）、RaGaVeRa（インド）、Observe.ai（米国）、Eigen（米国）、Gnani.ai（インド）、Crayon Data（シンガポール）、Narrativa（米国）、deepset（米国）、Ellipsis Health（米国）、DheeYantra（米国）、Verbit.ai（米国）、Rasa（米国）、MonkeyLearn（米国）、TextRazor（英国）、Cohere（カナダ）。
調査範囲
この市場調査は、セグメントにわたる自然言語処理を対象としている。市場規模や、提供、タイプ、アプリケーション、テクノロジー、業種、地域など、さまざまなセグメントにわたる成長の可能性を推定することを目的としています。市場の主要企業の詳細な競合分析、企業プロフィール、製品および事業提供に関する主な見解、最近の動向、主要な市場戦略も含まれています。
レポート購入の主な利点
本レポートは、自然言語処理市場全体とそのサブセグメントにおける収益数の最も近い近似値に関する情報を、本市場の市場リーダー/新規参入者に提供します。本レポートは、ステークホルダーが競合状況を理解し、自社のビジネスを位置付け、適切な市場参入戦略を計画するためのより良い洞察を得るのに役立ちます。また、利害関係者が市場の鼓動を理解するのに役立ち、主要な市場促進要因、阻害要因、課題、機会に関する情報を提供します。
本レポートでは、以下のポイントに関する洞察を提供しています：

- 主な促進要因（テキスト分析コンピュータプログラムの進歩、より良い顧客体験のための業務合理化を目的とした企業向けソリューションへのニーズの高まり、全体的なコスト削減と拡張性の向上を目的としたクラウドベースのNLPソリューションへの需要の急増、リスク削減と成長機会の特定を目的とした予測分析への需要）、阻害要因（曖昧さにつながる文脈理解の欠如、NLPソリューション実装時のコード混在言語使用による複雑さ、ニューラルネットワークを使用したNLP技術開発の限界）の分析、自然言語処理市場の成長に影響を与える機会（NLP市場を変革する触媒として機能するジェネレーティブAI、実用的なビジネスインテリジェンスのためのビッグデータ技術開発の必要性、ヘルスケア全体における効果的なデータ管理と高度なデータ分析に対する需要の増加）、課題（多言語能力の欠如、データセキュリティに対する規制とプライバシーへの懸念、NLPアルゴリズムの展開における相互運用性と信頼性の問題）。

- 製品開発/イノベーション：自然言語処理市場における今後の技術、研究開発活動、新製品・サービス発表に関する詳細な洞察。

- 市場開発：有利な市場に関する包括的な情報 - 当レポートでは、さまざまな地域の自然言語処理市場を分析しています。

- 市場の多様化：新製品＆サービス、未開拓の地域、最近の開発、自然言語処理市場戦略への投資に関する網羅的な情報; また、ステークホルダーが自然言語処理市場の鼓動を理解するのに役立ち、主要な市場促進要因、阻害要因、課題、および機会に関する情報を提供します。

- 競争力の評価：自然言語処理市場におけるIBM（米国）、Microsoft（米国）、Google（米国）、AWS（米国）、Meta（米国）、3M（米国）などの主要企業の市場シェア、成長戦略、サービス内容を詳細に評価。

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目次

1 INTRODUCTION 53
1.1 STUDY OBJECTIVES 53
1.2 MARKET DEFINITION 53
1.2.1 INCLUSIONS AND EXCLUSIONS 54
1.3 MARKET SCOPE 55
1.3.1 MARKET SEGMENTATION 55
1.3.2 REGIONS COVERED 57
1.4 YEARS CONSIDERED 57
1.5 CURRENCY CONSIDERED 58
1.6 STAKEHOLDERS 58
1.7 SUMMARY OF CHANGES 59
1.7.1 RECESSION IMPACT 59
2 RESEARCH METHODOLOGY 60
2.1 RESEARCH DATA 60
FIGURE 1 NATURAL LANGUAGE PROCESSING MARKET: RESEARCH DESIGN 60
2.1.1 SECONDARY DATA 61
2.1.2 PRIMARY DATA 61
TABLE 1 PRIMARY INTERVIEWS WITH EXPERTS 61
2.1.2.1 Breakup of primary profiles 62
FIGURE 2 BREAKUP OF PRIMARY INTERVIEWS: BY COMPANY NAME, DESIGNATION, AND REGION 62
2.1.2.2 Key insights from industry experts 63
2.2 DATA TRIANGULATION AND MARKET BREAKUP 64
FIGURE 3 DATA TRIANGULATION 64
2.3 MARKET SIZE ESTIMATION 65
FIGURE 4 NATURAL LANGUAGE PROCESSING MARKET: TOP-DOWN AND BOTTOM-UP APPROACHES 65
2.3.1 TOP-DOWN APPROACH 65
2.3.2 BOTTOM-UP APPROACH 66
FIGURE 5 MARKET SIZE ESTIMATION METHODOLOGY - APPROACH 1 (SUPPLY-SIDE): FLOWCHART USING REVENUE FROM NLP SOLUTIONS/SERVICES 66
FIGURE 6 MARKET SIZE ESTIMATION METHODOLOGY - APPROACH 2, BOTTOM-UP (SUPPLY-SIDE): COLLECTIVE REVENUE FROM ALL NLP SOLUTION/SERVICE COMPANIES 67
FIGURE 7 MARKET SIZE ESTIMATION METHODOLOGY - APPROACH 3, BOTTOM-UP (SUPPLY-SIDE): REVENUES OF TOP PLAYERS AND SOURCES OF DATA 67
FIGURE 8 MARKET SIZE ESTIMATION METHODOLOGY - APPROACH 4, BOTTOM-UP (DEMAND-SIDE): SHARE THROUGH OVERALL NLP SPENDING 68
2.4 MARKET FORECAST 69
TABLE 2 FACTOR ANALYSIS 69
2.5 RESEARCH ASSUMPTIONS 70
2.6 LIMITATIONS 71
2.7 RECESSION IMPACT ANALYSIS 72
TABLE 3 IMPACT OF RECESSION 72
3 EXECUTIVE SUMMARY 74
TABLE 4 NATURAL LANGUAGE PROCESSING MARKET SIZE AND GROWTH RATE, 2017–2022 (USD MILLION, Y-O-Y) 76
TABLE 5 NATURAL LANGUAGE PROCESSING MARKET SIZE AND GROWTH RATE, 2023–2028 (USD MILLION, Y-O-Y) 76
FIGURE 9 SOLUTIONS SEGMENT TO ACCOUNT FOR LARGER MARKET IN 2023 76
FIGURE 10 SOFTWARE TOOLS SEGMENT TO ACCOUNT FOR LARGER MARKET IN 2023 76
FIGURE 11 PROFESSIONAL SERVICES SEGMENT TO ACCOUNT FOR LARGER MARKET IN 2023 77
FIGURE 12 SYSTEM INTEGRATION & IMPLEMENTATION SEGMENT TO ACCOUNT FOR LARGEST MARKET SHARE IN 2023 77
FIGURE 13 STATISTICAL TYPE SEGMENT TO ACCOUNT FOR LARGEST MARKET IN 2023 77
FIGURE 14 IVR TECHNOLOGY SEGMENT TO ACCOUNT FOR LARGEST MARKET SHARE IN 2023 78
FIGURE 15 SENTIMENT ANALYSIS SEGMENT TO ACCOUNT FOR THE LARGEST APPLICATION IN 2023 78
FIGURE 16 CLOUD DEPLOYMENT SEGMENT TO BE LARGER MARKET IN 2023 78
FIGURE 17 BFSI VERTICAL TO ACCOUNT FOR LARGEST MARKET SHARE IN 2023 79
FIGURE 18 ASIA PACIFIC TO GROW AT HIGHEST CAGR IN MARKET DURING FORECAST PERIOD 79
4 PREMIUM INSIGHTS 80
4.1 ATTRACTIVE OPPORTUNITIES IN NATURAL LANGUAGE PROCESSING MARKET 80
FIGURE 19 SURGING DEMAND FOR VIRTUAL ASSISTANTS AND CHATBOTS POWERED BY GENERATIVE AI TO BOOST ADOPTION OF NLP SOLUTIONS 80
4.2 OVERVIEW OF RECESSION IN GLOBAL NATURAL LANGUAGE PROCESSING MARKET 80
FIGURE 20 NATURAL LANGUAGE PROCESSING MARKET TO WITNESS MINOR DECLINE IN Y-O-Y GROWTH IN 2023 80
4.3 NATURAL LANGUAGE PROCESSING MARKET: TOP THREE APPLICATIONS 81
FIGURE 21 SENTIMENT ANALYSIS APPLICATION TO HOLD LARGEST MARKET SHARE DURING FORECAST PERIOD 81
4.4 NATURAL LANGUAGE PROCESSING MARKET: KEY OFFERING & TOP THREE VERTICALS 81
FIGURE 22 SOLUTIONS AND BFSI VERTICAL TO ACCOUNT FOR LARGEST MARKET SHARES RESPECTIVELY IN 2023 81
4.5 NATURAL LANGUAGE PROCESSING MARKET, BY REGION 82
FIGURE 23 NORTH AMERICA TO ACCOUNT FOR LARGEST MARKET SHARE IN 2023 82
5 MARKET OVERVIEW AND INDUSTRY TRENDS 83
5.1 INTRODUCTION 83
5.2 MARKET DYNAMICS 83
FIGURE 24 MARKET DRIVERS, RESTRAINTS, OPPORTUNITIES, AND CHALLENGES: NATURAL LANGUAGE PROCESSING MARKET 84
5.2.1 DRIVERS 84
5.2.1.1 Advancements in text-analyzing computer programs 84
5.2.1.2 Rising need to streamline business operations for better customer experience 84
5.2.1.3 Surging demand for cloud-based NLP solutions to reduce overall costs and enhance scalability 85
5.2.1.4 Demand for predictive analytics to reduce risks and identify growth opportunities 85
5.2.2 RESTRAINTS 85
5.2.2.1 Lack of contextual understanding leading to ambiguity 85
5.2.2.2 Complexities due to code-mixed language 86
5.2.2.3 Limitations in developing NLP technology using neural networks 86
5.2.3 OPPORTUNITIES 86
5.2.3.1 Generative AI acting as catalyst for transforming NLP market 86
5.2.3.2 Need for developing big data technology for actionable business intelligence 87
5.2.3.3 Increasing demand for effective data management and advanced data analytics in healthcare sector 87
5.2.4 CHALLENGES 88
5.2.4.1 Lack of multilingual proficiency 88
5.2.4.2 Regulatory and privacy concerns over data security 88
5.2.4.3 Interoperability and reliability issues while deploying NLP algorithms 88
5.3 INDUSTRY TRENDS 89
5.3.1 NATURAL LANGUAGE PROCESSING: EVOLUTION 89
FIGURE 25 NATURAL LANGUAGE PROCESSING MARKET: EVOLUTION 89
5.3.2 NATURAL LANGUAGE PROCESSING: ARCHITECTURE 90
FIGURE 26 NATURAL LANGUAGE PROCESSING MARKET: ARCHITECTURE 90
5.3.3 VALUE CHAIN ANALYSIS 91
FIGURE 27 NATURAL LANGUAGE PROCESSING MARKET: VALUE CHAIN ANALYSIS 92
5.3.4 SUPPLY CHAIN ANALYSIS 93
FIGURE 28 NATURAL LANGUAGE PROCESSING MARKET: SUPPLY CHAIN ANALYSIS 93
5.3.5 ECOSYSTEM 93
FIGURE 29 NATURAL LANGUAGE PROCESSING MARKET: ECOSYSTEM 94
TABLE 6 NATURAL LANGUAGE PROCESSING MARKET: PLATFORM PROVIDERS 94
TABLE 7 NATURAL LANGUAGE PROCESSING MARKET: SOFTWARE PROVIDERS 95
TABLE 8 NATURAL LANGUAGE PROCESSING MARKET: SERVICE PROVIDERS 95
TABLE 9 NATURAL LANGUAGE PROCESSING MARKET: FRAMEWORK AND TOOLKIT PROVIDERS 95
TABLE 10 NATURAL LANGUAGE PROCESSING MARKET: REGULATORY BODIES 96
5.3.6 PRICING ANALYSIS 97
5.3.6.1 Selling prices of key players, by application 97
FIGURE 30 SELLING PRICES OF KEY PLAYERS FOR TOP THREE APPLICATIONS 97
TABLE 11 SELLING PRICES OF KEY PLAYERS FOR TOP THREE APPLICATIONS (USD) 97
5.3.6.2 Indicative pricing analysis of NLP software 97
TABLE 12 NATURAL LANGUAGE PROCESSING PRODUCTS: PRICING LEVELS 98
5.4 PORTER’S FIVE FORCES ANALYSIS 99
FIGURE 31 PORTER’S FIVE FORCES ANALYSIS 99
TABLE 13 PORTER’S FIVE FORCES ANALYSIS 99
5.4.1 THREAT OF NEW ENTRANTS 100
5.4.2 THREAT OF SUBSTITUTES 100
5.4.3 BARGAINING POWER OF SUPPLIERS 100
5.4.4 BARGAINING POWER OF BUYERS 100
5.4.5 INTENSITY OF COMPETITIVE RIVALRY 101
5.4.6 TRENDS/DISRUPTIONS IMPACTING BUYER/CLIENT BUSINESS 101
FIGURE 32 NATURAL LANGUAGE PROCESSING MARKET: TRENDS/DISRUPTIONS IMPACTING BUYER/CLIENT BUSINESS 101
5.4.7 TECHNOLOGY ANALYSIS 101
FIGURE 33 NATURAL LANGUAGE PROCESSING MARKET: TECHNOLOGY ANALYSIS 102
5.4.7.1 Key Technologies 102
5.4.7.1.1 AI 102
5.4.7.1.2 Deep Learning 102
5.4.7.1.3 Speech Recognition 103
5.4.7.1.4 Speech-to-Text 104
5.4.7.1.5 Text-to-Speech 104
5.4.7.2 Complementary Technologies 105
5.4.7.2.1 Big Data 105
5.4.7.2.2 Cloud Computing 105
5.4.7.2.3 IoT 106
5.4.7.3 Adjacent Technologies 106
5.4.7.3.1 Blockchain 106
5.4.7.3.2 Cybersecurity 107
5.4.7.3.3 Graph Databases 107
5.4.8 CASE STUDY ANALYSIS 108
5.4.8.1 Banking, financial services, and insurance 108
5.4.8.1.1 Case Study 1: National Bank of Greece modernized its analytics platform with SAS Viya on Azure 108
5.4.8.1.2 Case Study 2: HSBC implemented LivePerson’s conversational AI solutions with intelligent automation 109
5.4.8.1.3 Case Study 3: Observe.AI's Auto QA revolutionized compliance and performance optimization of financial services company 109
5.4.8.2 Healthcare & life sciences 110
5.4.8.2.1 Case Study 4: TGH Urgent Care streamlined operations and improved patient experience with LivePerson's Voice Bot 110
5.4.8.2.2 Case Study 5: Atrius Health created queries to extract clinical data from free-text fields using Linguamatics I2E 111
5.4.8.2.3 Case Study 6: Huntsman Cancer Institute optimized research with Linguamatics NLP platform 111
5.4.8.2.4 Case Study 7: Humana’s Voice Agent reduced costly pre-service calls with conversational AI 112
5.4.8.3 IT & ITeS 113
5.4.8.3.1 Case Study 8: Telenor adapted to rapidly changing customer expectations using SAS Viya 113
5.4.8.4 Retail & eCommerce 114
5.4.8.4.1 Case Study 9: Wehkamp generated high-quality product descriptions while maintaining SEO focus with NLG 114
5.4.8.4.2 Case Study 10: Bitext's Multilingual Synthetic Training Data transformed customer service 115
5.4.8.5 Government & public sector 116
5.4.8.5.1 Case Study 11: Azure Maps Weather forecasted data and SAS Event Stream Processing predicted flooding time 116
5.4.8.6 Media & entertainment 117
5.4.8.6.1 Case Study 12: Sweetwater enhanced customer experience with VoiceBase Conversation Intelligence 117
5.4.8.6.2 Case Study 13: Hearst Newspapers used Google Cloud Natural Language API for content classification 118
5.4.8.7 Travel & hospitality 118
5.4.8.7.1 Case Study 14: SAS gave Foxwoods Resort Casino holistic view of resort operations 118
5.4.9 PATENT ANALYSIS 119
5.4.9.1 Methodology 119
5.4.9.2 Document Type 119
TABLE 14 PATENTS FILED, 2013–2023 119
5.4.9.3 Innovation and Patent Applications 120
FIGURE 34 TOTAL NUMBER OF PATENTS GRANTED, 2013–2023 120
5.4.9.3.1 Top applicants 120
FIGURE 35 TOP TEN COMPANIES WITH HIGHEST NUMBER OF PATENT APPLICATIONS, 2013–2023 120
TABLE 15 TOP TWENTY PATENT OWNERS, 2013–2023 121
TABLE 16 LIST OF PATENTS IN NATURAL LANGUAGE PROCESSING MARKET, 2021–2023 121
5.4.10 KEY CONFERENCES & EVENTS, 2023–2024 123
TABLE 17 DETAILED LIST OF CONFERENCES & EVENTS, 2023–2024 123
5.4.11 TARIFFS AND REGULATORY LANDSCAPE 124
5.4.11.1 Regulatory bodies, government agencies, and other organizations 124
TABLE 18 NORTH AMERICA: LIST OF REGULATORY BODIES, GOVERNMENT AGENCIES, AND OTHER ORGANIZATIONS 124
TABLE 19 EUROPE: LIST OF REGULATORY BODIES, GOVERNMENT AGENCIES, AND OTHER ORGANIZATIONS 125
TABLE 20 ASIA PACIFIC: LIST OF REGULATORY BODIES, GOVERNMENT AGENCIES, AND OTHER ORGANIZATIONS 127
TABLE 21 ROW: LIST OF REGULATORY BODIES, GOVERNMENT AGENCIES, AND OTHER ORGANIZATIONS 128
5.4.11.1.1 North America 128
5.4.11.1.1.1 US 128
5.4.11.1.1.2 Canada 128
5.4.11.1.2 Europe 128
5.4.11.1.3 Asia Pacific 128
5.4.11.1.3.1 South Korea 129
5.4.11.1.3.2 China 129
5.4.11.1.3.3 India 129
5.4.11.1.4.1 UAE 129
5.4.11.1.4.2 KSA 129
5.4.11.1.4.3 Bahrain 129
5.4.11.1.5 Latin America 129
5.4.11.1.5.1 Brazil 130
5.4.11.1.5.2 Mexico 130
5.4.12 KEY STAKEHOLDERS AND BUYING CRITERIA 130
FIGURE 36 INFLUENCE OF STAKEHOLDERS ON BUYING PROCESS FOR TOP THREE APPLICATIONS 130
TABLE 22 INFLUENCE OF STAKEHOLDERS ON BUYING PROCESS FOR TOP THREE APPLICATIONS 130
5.4.12.1 Buying Criteria 131
FIGURE 37 KEY BUYING CRITERIA FOR TOP THREE APPLICATIONS 131
TABLE 23 KEY BUYING CRITERIA FOR TOP THREE APPLICATIONS 131
5.4.13 BEST PRACTICES IN NATURAL LANGUAGE PROCESSING MARKET 132
5.4.14 TECHNOLOGY ROADMAP OF NATURAL LANGUAGE PROCESSING MARKET 133
TABLE 24 SHORT-TERM ROADMAP, 2023–2025 133
TABLE 25 MID-TERM ROADMAP, 2026–2028 133
TABLE 26 LONG-TERM ROADMAP, 2029–2030 134
5.4.15 STEPS IN NATURAL LANGUAGE PROCESSING 134
5.4.16 BUSINESS MODELS OF NATURAL LANGUAGE PROCESSING MARKET 136
5.4.16.1 NLP as a Service (NLPaaS) 136
5.4.16.2 NLP Software and Tools Licensing 136
5.4.16.3 NLP Content Generation and Publishing 136
5.4.16.4 NLP Analytics and Insights 136
5.4.16.5 NLP Consulting and Custom Solutions 136
6 NATURAL LANGUAGE PROCESSING MARKET, BY OFFERING 137
6.1 INTRODUCTION 138
6.1.1 OFFERING: NATURAL LANGUAGE PROCESSING MARKET DRIVERS 138
FIGURE 38 SERVICES SEGMENT TO WITNESS HIGHER CAGR DURING FORECAST PERIOD 139
TABLE 27 NATURAL LANGUAGE PROCESSING MARKET, BY OFFERING, 2017–2022 (USD MILLION) 139
TABLE 28 NATURAL LANGUAGE PROCESSING MARKET, BY OFFERING, 2023–2028 (USD MILLION) 139
 
6.2 SOLUTIONS 140
6.2.1 NLP SOLUTIONS TO ANALYZE TEXT, VOICE, AND VIDEO CONTENT, ENABLING AI AGENTS TO UNDERSTAND NUANCES AND CONTEXTS OF HUMAN LANGUAGE 140
FIGURE 39 SOFTWARE TOOLS SEGMENT TO HOLD LARGEST MARKET SIZE DURING FORECAST PERIOD 140
TABLE 29 NATURAL LANGUAGE PROCESSING MARKET, BY SOLUTION, 2017–2022 (USD MILLION) 140
TABLE 30 NATURAL LANGUAGE PROCESSING MARKET, BY SOLUTION, 2023–2028 (USD MILLION) 140
TABLE 31 SOLUTIONS: NATURAL LANGUAGE PROCESSING MARKET, BY REGION, 2017–2022 (USD MILLION) 141
TABLE 32 SOLUTIONS: NATURAL LANGUAGE PROCESSING MARKET, BY REGION, 2023–2028 (USD MILLION) 141
6.2.2 PLATFORMS 141
6.2.2.1 NLP platforms to provide comprehensive tools and infrastructure 141
TABLE 33 PLATFORMS: NATURAL LANGUAGE PROCESSING MARKET, BY REGION, 2017–2022 (USD MILLION) 142
TABLE 34 PLATFORMS: NATURAL LANGUAGE PROCESSING MARKET, BY REGION, 2023–2028 (USD MILLION) 142
6.2.3 SOFTWARE TOOLS 142
6.2.3.1 NLP software tools to enable users to integrate NLP capabilities with existing software 142
TABLE 35 SOFTWARE TOOLS: NATURAL LANGUAGE PROCESSING MARKET, BY REGION, 2017–2022 (USD MILLION) 143
TABLE 36 SOFTWARE TOOLS: NATURAL LANGUAGE PROCESSING MARKET, BY REGION, 2023–2028 (USD MILLION) 143
6.3 BY DEPLOYMENT MODE 143
6.3.1 CLOUD DEPLOYMENT MODE TO DOMINATE MARKET DUE TO ITS SCALABILITY, EASY AVAILABILITY, AND COST SAVINGS 143
FIGURE 40 CLOUD SEGMENT TO HOLD LARGER MARKET SIZE DURING FORECAST PERIOD 144
TABLE 37 NATURAL LANGUAGE PROCESSING MARKET, BY DEPLOYMENT MODE, 2017–2022 (USD MILLION) 144
TABLE 38 NATURAL LANGUAGE PROCESSING MARKET, BY DEPLOYMENT MODE, 2023–2028 (USD MILLION) 144
6.3.2 CLOUD 145
6.3.2.1 Cloud system to offer flexibility for business operations and real-time deployment ease 145
TABLE 39 CLOUD: NATURAL LANGUAGE PROCESSING MARKET, BY REGION, 2017–2022 (USD MILLION) 145
TABLE 40 CLOUD: NATURAL LANGUAGE PROCESSING MARKET, BY REGION, 2023–2028 (USD MILLION) 145
6.3.3 ON-PREMISES 146
6.3.3.1 On-premises solutions to help in data validation, standardization, and robust matching 146
TABLE 41 ON-PREMISES: NATURAL LANGUAGE PROCESSING MARKET, BY REGION, 2017–2022 (USD MILLION) 146
TABLE 42 ON-PREMISES: NATURAL LANGUAGE PROCESSING MARKET, BY REGION, 2023–2028 (USD MILLION) 146
6.4 SERVICES 147
6.4.1 SERVICES TO ACHIEVE EFFECTIVE SOFTWARE OPERATIONS AND INCREASE EFFICIENCY 147
FIGURE 41 PROFESSIONAL SERVICES SEGMENT TO HOLD LARGEST MARKET SIZE DURING FORECAST PERIOD 147
TABLE 43 NATURAL LANGUAGE PROCESSING MARKET, BY SERVICE, 2017–2022 (USD MILLION) 147
TABLE 44 NATURAL LANGUAGE PROCESSING MARKET, BY SERVICE, 2023–2028 (USD MILLION) 148
6.4.2 PROFESSIONAL SERVICES 148
6.4.2.1 Professional services to support, maintain, and manage installed software 148
FIGURE 42 TRAINING & CONSULTING SEGMENT TO WITNESS HIGHEST CAGR DURING FORECAST PERIOD 148
TABLE 45 PROFESSIONAL SERVICES: NATURAL LANGUAGE PROCESSING MARKET, BY TYPE, 2017–2022 (USD MILLION) 149
TABLE 46 PROFESSIONAL SERVICES: NATURAL LANGUAGE PROCESSING MARKET, BY TYPE, 2023–2028 (USD MILLION) 149
TABLE 47 PROFESSIONAL SERVICES: NATURAL LANGUAGE PROCESSING MARKET, BY REGION, 2017–2022 (USD MILLION) 149
TABLE 48 PROFESSIONAL SERVICES: NATURAL LANGUAGE PROCESSING MARKET, BY REGION, 2023–2028 (USD MILLION) 149
6.4.2.2 Training & Consulting 150
TABLE 49 TRAINING & CONSULTING: NATURAL LANGUAGE PROCESSING MARKET, BY REGION, 2017–2022 (USD MILLION) 150
TABLE 50 TRAINING & CONSULTING: NATURAL LANGUAGE PROCESSING MARKET, BY REGION, 2023–2028 (USD MILLION) 151
6.4.2.3 System Integration & Implementation 151
TABLE 51 SYSTEM INTEGRATION & IMPLEMENTATION: NATURAL LANGUAGE PROCESSING MARKET, BY REGION, 2017–2022 (USD MILLION) 151
TABLE 52 SYSTEM INTEGRATION & IMPLEMENTATION: NATURAL LANGUAGE PROCESSING MARKET, BY REGION, 2023–2028 (USD MILLION) 152
6.4.2.4 Support & Maintenance 152
TABLE 53 SUPPORT & MAINTENANCE: NATURAL LANGUAGE PROCESSING MARKET, BY REGION, 2017–2022 (USD MILLION) 152
TABLE 54 SUPPORT & MAINTENANCE: NATURAL LANGUAGE PROCESSING MARKET, BY REGION, 2023–2028 (USD MILLION) 153
6.4.3 MANAGED SERVICES 153
6.4.3.1 Managed services to offer specialized skills to maintain and update NLP software and services 153
TABLE 55 MANAGED SERVICES: NATURAL LANGUAGE PROCESSING MARKET, BY REGION, 2017–2022 (USD MILLION) 153
TABLE 56 MANAGED SERVICES: NATURAL LANGUAGE PROCESSING MARKET, BY REGION, 2023–2028 (USD MILLION) 154
6.4.3.2 NLP Model as a Service (MaaS) 154
6.4.3.3 Chatbot as a Service (CaaS) 154
6.4.3.4 Sentiment Analysis as a Service 154
6.4.3.5 Other managed services 155
7 NATURAL LANGUAGE PROCESSING MARKET, BY TYPE 156
7.1 INTRODUCTION 157
7.1.1 TYPE: NATURAL LANGUAGE PROCESSING MARKET DRIVERS 157
FIGURE 43 HYBRID NATURAL LANGUAGE PROCESSING TO WITNESS HIGHEST CAGR DURING FORECAST PERIOD 157
TABLE 57 NATURAL LANGUAGE PROCESSING MARKET, BY TYPE, 2017–2022 (USD MILLION) 158
TABLE 58 NATURAL LANGUAGE PROCESSING MARKET, BY TYPE, 2023–2028 (USD MILLION) 158
7.2 RULE-BASED 158
7.2.1 RULE-BASED NLP TO USE EXTENSIVE LINGUISTIC RULES TO TAG AND CATEGORIZE TEXT MORE ACCURATELY 158
TABLE 59 RULE-BASED: NATURAL LANGUAGE PROCESSING MARKET, BY REGION, 2017–2022 (USD MILLION) 159
TABLE 60 RULE-BASED: NATURAL LANGUAGE PROCESSING MARKET, BY REGION, 2023–2028 (USD MILLION) 159
7.3 STATISTICAL 159
7.3.1 STATISTICAL NLP TO FOCUS ON STATISTICAL MODELS AND PROBABILISTIC ALGORITHMS TO UNDERSTAND AND PROCESS HUMAN LANGUAGE 159
TABLE 61 STATISTICAL: NATURAL LANGUAGE PROCESSING MARKET, BY REGION, 2017–2022 (USD MILLION) 160
TABLE 62 STATISTICAL: NATURAL LANGUAGE PROCESSING MARKET, BY REGION, 2023–2028 (USD MILLION) 160
7.4 HYBRID 160
7.4.1 HYBRID NLP TO PROVIDE VERSATILE SOLUTION TO TACKLE DIVERSE CHALLENGES OF LANGUAGE UNDERSTANDING AND GENERATION 160
TABLE 63 HYBRID: NATURAL LANGUAGE PROCESSING MARKET, BY REGION, 2017–2022 (USD MILLION) 161
TABLE 64 HYBRID: NATURAL LANGUAGE PROCESSING MARKET, BY REGION, 2023–2028 (USD MILLION) 161
8 NATURAL LANGUAGE PROCESSING MARKET, BY APPLICATION 162
8.1 INTRODUCTION 163
8.1.1 APPLICATION: NATURAL LANGUAGE PROCESSING MARKET DRIVERS 163
FIGURE 44 SENTIMENT ANALYSIS APPLICATION TO HOLD LARGEST MARKET SIZE DURING FORECAST PERIOD 164
TABLE 65 NATURAL LANGUAGE PROCESSING MARKET, BY APPLICATION, 2017–2022 (USD MILLION) 164
TABLE 66 NATURAL LANGUAGE PROCESSING MARKET, BY APPLICATION, 2023–2028 (USD MILLION) 165
8.2 CUSTOMER EXPERIENCE MANAGEMENT 165
8.2.1 CUSTOMER EXPERIENCE MANAGEMENT TO OVERSEE, ORGANIZE, AND MONITOR CUSTOMER INTERACTIONS 165
TABLE 67 CUSTOMER EXPERIENCE MANAGEMENT: NATURAL LANGUAGE PROCESSING MARKET, BY REGION, 2017–2022 (USD MILLION) 166
TABLE 68 CUSTOMER EXPERIENCE MANAGEMENT: NATURAL LANGUAGE PROCESSING MARKET, BY REGION, 2023–2028 (USD MILLION) 166
8.3 VIRTUAL ASSISTANTS/CHATBOTS 166
8.3.1 CHATBOTS TO FACILITATE CONVERSATIONS BETWEEN HUMANS AND COMPUTERS IN EVERYDAY BUSINESS PROCESSES 166
TABLE 69 VIRTUAL ASSISTANTS/CHATBOTS: NATURAL LANGUAGE PROCESSING MARKET, BY REGION, 2017–2022 (USD MILLION) 167
TABLE 70 VIRTUAL ASSISTANTS/CHATBOTS: NATURAL LANGUAGE PROCESSING MARKET, BY REGION, 2023–2028 (USD MILLION) 167
8.3.2 VOICE-ACTIVATED VIRTUAL ASSISTANTS 167
8.3.2.1 Voice-powered Virtual Assistants 168
8.3.2.2 Enterprise Virtual Assistants Chatbots 168
8.3.3 ML-BASED CHATBOTS 168
8.3.3.1 Intent Recognition 168
8.3.3.2 Dialog Management 169
8.3.4 RULE-BASED CHATBOTS 169
8.3.4.1 Decision Tree-based Chatbots 169
8.3.4.2 Scripted Chatbots 170
8.4 SOCIAL MEDIA MONITORING 170
8.4.1 SOCIAL MEDIA MONITORING TO ENABLE CONNECTING WITH CUSTOMERS, PROVIDING CUSTOMER SUPPORT, AND MEASURING SOCIAL MEDIA REACH 170
TABLE 71 SOCIAL MEDIA MONITORING: NATURAL LANGUAGE PROCESSING MARKET, BY REGION, 2017–2022 (USD MILLION) 171
TABLE 72 SOCIAL MEDIA MONITORING: NATURAL LANGUAGE PROCESSING MARKET, BY REGION, 2023–2028 (USD MILLION) 171
8.5 SENTIMENT ANALYSIS 171
8.5.1 SENTIMENT ANALYSIS TO IDENTIFY TEXT EXPRESSIONS, GAIN INSIGHTS FROM SOCIAL MEDIA COMMENTS, AND DETECT SENTIMENTS 171
TABLE 73 SENTIMENT ANALYSIS: NATURAL LANGUAGE PROCESSING MARKET, BY REGION, 2017–2022 (USD MILLION) 172
TABLE 74 SENTIMENT ANALYSIS: NATURAL LANGUAGE PROCESSING MARKET, BY REGION, 2023–2028 (USD MILLION) 172
8.5.2 AUTOMATED SENTIMENT ANALYSIS 172
8.5.3 FINE-GRAINED ANALYSIS 173
8.6 TEXT CLASSIFICATION & SUMMARIZATION 173
8.6.1 TEXT CLASSIFICATION TO ANALYZE TEXT AND ASSIGN PRE-DEFINED TAGS OR CATEGORIES BASED ON ITS CONTENT 173
TABLE 75 TEXT CLASSIFICATION & SUMMARIZATION: NATURAL LANGUAGE PROCESSING MARKET, BY REGION, 2017–2022 (USD MILLION) 174
TABLE 76 TEXT CLASSIFICATION & SUMMARIZATION: NATURAL LANGUAGE PROCESSING MARKET, BY REGION, 2023–2028 (USD MILLION) 174
8.7 EMPLOYEE ONBOARDING & RECRUITING 174
8.7.1 NATURAL LANGUAGE PROCESSING TO PERFORM THEME ANALYSIS, SHORTLIST BEST APPLICANTS AND JOBS, AND IMPROVE HR EFFICIENCY AND CANDIDATE EXPERIENCE 174
TABLE 77 EMPLOYEE ONBOARDING & RECRUITING: NATURAL LANGUAGE PROCESSING MARKET, BY REGION, 2017–2022 (USD MILLION) 175
TABLE 78 EMPLOYEE ONBOARDING & RECRUITING: NATURAL LANGUAGE PROCESSING MARKET, BY REGION, 2023–2028 (USD MILLION) 175
8.8 LANGUAGE GENERATION & SPEECH RECOGNITION 175
8.8.1 LANGUAGE GENERATION AND SPEECH RECOGNITION TO IMPROVE COMMUNICATION, AUTOMATION, AND CUSTOMER ENGAGEMENT 175
TABLE 79 LANGUAGE GENERATION & SPEECH RECOGNITION: NATURAL LANGUAGE PROCESSING MARKET, BY REGION, 2017–2022 (USD MILLION) 176
TABLE 80 LANGUAGE GENERATION & SPEECH RECOGNITION: NATURAL LANGUAGE PROCESSING MARKET, BY REGION, 2023–2028 (USD MILLION) 176
8.8.2 GENERATIVE PRETRAINED TRANSFORMER 176
8.8.2.1 Fine-tuned Models 177
8.8.2.2 Creative Content Generation 177
8.8.3 NATURAL LANGUAGE GENERATION 177
8.8.3.1 Content Templates 178
8.8.3.2 Data-to-Text Generation 178
8.8.4 AUTOMATIC SPEECH RECOGNITION (ASR) 179
8.8.4.1 Speaker Recognition 179
8.8.4.2 Speech-to-Text Conversation 180
8.8.5 SPEECH SYNTHESIS 180
8.8.5.1 Text-To-Speech (TTS) Conversion 180
8.8.5.2 Emotive & Expressive TTS 181
8.9 MACHINE TRANSLATION 181
8.9.1 MACHINE TRANSLATION TO FACILITATE COMMUNICATION AND BREAK DOWN LANGUAGE BARRIERS ACROSS VARIOUS DOMAINS 181
TABLE 81 MACHINE TRANSLATION: NATURAL LANGUAGE PROCESSING MARKET, BY REGION, 2017–2022 (USD MILLION) 182
TABLE 82 MACHINE TRANSLATION: NATURAL LANGUAGE PROCESSING MARKET, BY REGION, 2023–2028 (USD MILLION) 182
8.9.2 NEURAL MACHINE TRANSLATION (NMT) 182
8.9.2.1 Language Pair-specific NMT 183
8.9.2.2 Domain-specific NMT 183
8.9.3 STATISTICAL MACHINE TRANSLATION (SMT) 183
8.9.3.1 Phrase-based SMT 184
8.9.3.2 Rule-based SMT 184
8.10 OTHER APPLICATIONS 184
TABLE 83 OTHER APPLICATIONS: NATURAL LANGUAGE PROCESSING MARKET, BY REGION, 2017–2022 (USD MILLION) 185
TABLE 84 OTHER APPLICATIONS: NATURAL LANGUAGE PROCESSING MARKET, BY REGION, 2023–2028 (USD MILLION) 185
 
9 NATURAL LANGUAGE PROCESSING MARKET, BY TECHNOLOGY 186
9.1 INTRODUCTION 187
9.1.1 TECHNOLOGY: NATURAL LANGUAGE PROCESSING MARKET DRIVERS 187
FIGURE 45 IMAGE & PATTERN RECOGNITION SEGMENT TO GROW AT HIGHEST CAGR DURING FORECAST PERIOD 187
TABLE 85 NATURAL LANGUAGE PROCESSING MARKET, BY TECHNOLOGY, 2017–2022 (USD MILLION) 188
TABLE 86 NATURAL LANGUAGE PROCESSING MARKET, BY TECHNOLOGY, 2023–2028 (USD MILLION) 188
9.2 OPTICAL CHARACTER RECOGNITION 188
9.2.1 OPTICAL CHARACTER RECOGNITION TO REVOLUTIONIZE TEXT ANALYSIS AND INFORMATION EXTRACTION 188
TABLE 87 OPTICAL CHARACTER RECOGNITION: NATURAL LANGUAGE PROCESSING MARKET, BY REGION, 2017–2022 (USD MILLION) 189
TABLE 88 OPTICAL CHARACTER RECOGNITION: NATURAL LANGUAGE PROCESSING MARKET, BY REGION, 2023–2028 (USD MILLION) 189
9.3 INTERACTIVE VOICE RESPONSE 189
9.3.1 INTERACTIVE VOICE RESPONSE TO ENHANCE CUSTOMER SERVICE AND USER EXPERIENCES 189
TABLE 89 INTERACTIVE VOICE RESPONSE: NATURAL LANGUAGE PROCESSING MARKET, BY REGION, 2017–2022 (USD MILLION) 190
TABLE 90 INTERACTIVE VOICE RESPONSE: NATURAL LANGUAGE PROCESSING MARKET, BY REGION, 2023–2028 (USD MILLION) 190
9.4 AUTO CODING 190
9.4.1 AUTO CODING TO STREAMLINE DATA ANALYSIS AND INFORMATION RETRIEVAL 190
TABLE 91 AUTO CODING: NATURAL LANGUAGE PROCESSING MARKET, BY REGION, 2017–2022 (USD MILLION) 191
TABLE 92 AUTO CODING: NATURAL LANGUAGE PROCESSING MARKET, BY REGION, 2023–2028 (USD MILLION) 191
9.5 TEXT ANALYTICS 191
9.5.1 TEXT ANALYTICS TO EMPOWER INFORMED DECISION-MAKING WITH TEXT MINING 191
TABLE 93 TEXT ANALYTICS: NATURAL LANGUAGE PROCESSING MARKET, BY REGION, 2017–2022 (USD MILLION) 192
TABLE 94 TEXT ANALYTICS: NATURAL LANGUAGE PROCESSING MARKET, BY REGION, 2023–2028 (USD MILLION) 192
9.5.2 ENTITY RECOGNITION 192
9.5.2.1 Named Entity Recognition (NER) 192
9.5.2.2 Entity Linking and Disambiguation 193
9.5.3 TOPIC MODELING 193
9.5.3.1 Latent Dirichlet Allocation (LDA) 194
9.5.3.2 Non-negative Matrix Factorization (NMF) 194
9.5.4 TEXT CLASSIFICATION 194
9.5.4.1 Binary Classification 195
9.5.4.2 Multi-class Classification 195
9.6 SPEECH ANALYTICS 196
9.6.1 SPEECH ANALYTICS TO TRANSFORM CUSTOMER SERVICE AND BUSINESS INTELLIGENCE 196
TABLE 95 SPEECH ANALYTICS: NATURAL LANGUAGE PROCESSING MARKET, BY REGION, 2017–2022 (USD MILLION) 196
TABLE 96 SPEECH ANALYTICS: NATURAL LANGUAGE PROCESSING MARKET, BY REGION, 2023–2028 (USD MILLION) 197
9.7 IMAGE & PATTERN RECOGNITION 197
9.7.1 IMAGE & PATTERN RECOGNITION TO BRIDGE GAP BETWEEN TEXT AND IMAGES 197
TABLE 97 IMAGE & PATTERN RECOGNITION: NATURAL LANGUAGE PROCESSING MARKET, BY REGION, 2017–2022 (USD MILLION) 197
TABLE 98 IMAGE & PATTERN RECOGNITION: NATURAL LANGUAGE PROCESSING MARKET, BY REGION, 2023–2028 (USD MILLION) 198
9.8 SIMULATION & MODELING 198
9.8.1 SIMULATION & MODELING TO ENABLE CREATION OF VIRTUAL LANGUAGE-BASED ENVIRONMENT 198
TABLE 99 SIMULATION & MODELLING: NATURAL LANGUAGE PROCESSING MARKET, BY REGION, 2017–2022 (USD MILLION) 198
TABLE 100 SIMULATION & MODELLING: NATURAL LANGUAGE PROCESSING MARKET, BY REGION, 2023–2028 (USD MILLION) 199
10 NATURAL LANGUAGE PROCESSING MARKET, BY VERTICAL 200
10.1 INTRODUCTION 201
10.1.1 VERTICAL: NATURAL LANGUAGE PROCESSING MARKET DRIVERS 201
TABLE 101 MAJOR USE CASES, BY VERTICAL 202
FIGURE 46 HEALTHCARE & LIFE SCIENCES VERTICAL TO REGISTER HIGHEST CAGR DURING FORECAST PERIOD 203
TABLE 102 NATURAL LANGUAGE PROCESSING MARKET, BY VERTICAL, 2017–2022 (USD MILLION) 204
TABLE 103 NATURAL LANGUAGE PROCESSING MARKET, BY VERTICAL, 2023–2028 (USD MILLION) 204
10.2 BFSI 205
TABLE 104 BFSI: NATURAL LANGUAGE PROCESSING MARKET, BY REGION, 2017–2022 (USD MILLION) 205
TABLE 105 BFSI: NATURAL LANGUAGE PROCESSING MARKET, BY REGION, 2023–2028 (USD MILLION) 205
10.2.1 FRAUD DETECTION 206
10.2.1.1 Transaction Fraud Detection 206
10.2.1.2 Identity Fraud Detection 206
10.2.2 ALGORITHMIC TRADING 207
10.2.2.1 Stock Price Prediction Diagnosis 207
10.2.2.2 Trading Strategy Optimization 208
10.2.3 RISK ASSESSMENT 208
10.2.3.1 Credit Scoring 208
10.2.3.2 Insurance Underwriting 208
10.3 IT & ITES 209
TABLE 106 IT & ITES: NATURAL LANGUAGE PROCESSING MARKET, BY REGION, 2017–2022 (USD MILLION) 209
TABLE 107 IT & ITES: NATURAL LANGUAGE PROCESSING MARKET, BY REGION, 2023–2028 (USD MILLION) 209
10.3.1 HELP DESK & IT SUPPORT SERVICES 210
10.3.2 CODE REVIEW & DOCUMENTATION 210
10.4 RETAIL & ECOMMERCE 211
TABLE 108 RETAIL & ECOMMERCE: NATURAL LANGUAGE PROCESSING MARKET, BY REGION, 2017–2022 (USD MILLION) 211
TABLE 109 RETAIL & ECOMMERCE: NATURAL LANGUAGE PROCESSING MARKET, BY REGION, 2023–2028 (USD MILLION) 211
10.4.1 PRODUCT RECOMMENDATION 212
10.4.1.1 Personalized Product Recommendation 212
10.4.1.2 Cross-selling and Upselling 212
10.4.2 SEARCH ENGINE OPTIMIZATION 213
10.4.2.1 Enhanced Search Algorithm 213
10.4.2.2 Voice-enabled Shopping 213
10.4.3 CUSTOMER SUPPORT & ENGAGEMENT 214
10.4.3.1 Chatbots for Customer Queries 214
10.4.3.2 Personalized Shopping Assistance 214
10.4.4 INVENTORY MANAGEMENT 215
10.4.4.1 Demand Forecasting 215
10.4.4.2 Stock-level Optimization 215
10.4.5 MARKET RESEARCH & COMPETITIVE ANALYSIS 216
10.4.5.1 Consumer Sentiment Analysis 216
10.4.5.2 Competitor Price Monitoring 216
10.5 HEALTHCARE & LIFE SCIENCES 217
TABLE 110 HEALTHCARE & LIFE SCIENCES: NATURAL LANGUAGE PROCESSING MARKET, BY REGION, 2017–2022 (USD MILLION) 217
TABLE 111 HEALTHCARE & LIFE SCIENCES: NATURAL LANGUAGE PROCESSING MARKET, BY REGION, 2023–2028 (USD MILLION) 217
10.5.1 CLINICAL DOCUMENTATION 218
10.5.1.1 EHR Analysis 218
10.5.1.2 Medical Coding 218
10.5.2 MEDICAL DIAGNOSIS 219
10.5.2.1 Disease Diagnosis 219
10.5.2.2 Treatment Recommendation 219
10.5.3 PHARMACEUTICALS 219
10.5.3.1 Drug Discovery 220
10.5.3.2 Pharmacovigilance & Drug Safety 220
10.5.4 PATIENT CARE 220
10.5.4.1 Virtual Health Assistants 221
10.5.4.2 Telemedicine Support 221
10.6 TRANSPORTATION & LOGISTICS 221
TABLE 112 TRANSPORTATION & LOGISTICS: NATURAL LANGUAGE PROCESSING MARKET, BY REGION, 2017–2022 (USD MILLION) 222
TABLE 113 TRANSPORTATION & LOGISTICS: NATURAL LANGUAGE PROCESSING MARKET, BY REGION, 2023–2028 (USD MILLION) 222
10.6.1 ROUTE OPTIMIZATION 222
10.6.1.1 Efficient Logistics Planning 222
10.6.1.2 Traffic Analysis 223
10.6.2 FLEET MANAGEMENT 223
10.6.2.1 Predictive Maintenance 223
10.6.2.2 Driver Behavior Analysis 223
10.7 GOVERNMENT & PUBLIC SECTOR 224
TABLE 114 GOVERNMENT & PUBLIC SECTOR: NATURAL LANGUAGE PROCESSING MARKET, BY REGION, 2017–2022 (USD MILLION) 224
TABLE 115 GOVERNMENT & PUBLIC SECTOR: NATURAL LANGUAGE PROCESSING MARKET, BY REGION, 2023–2028 (USD MILLION) 224
10.7.1 PUBLIC SERVICES 225
10.7.1.1 Citizen Interaction & Support 225
10.7.1.2 Administrative Document Processing 225
10.7.2 SECURITY & INTELLIGENCE 225
10.7.2.1 Text Analysis for Threat Detection 226
10.7.2.2 Intelligent Report Summarization 226
10.8 MEDIA & ENTERTAINMENT 226
TABLE 116 MEDIA & ENTERTAINMENT: NATURAL LANGUAGE PROCESSING MARKET, BY REGION, 2017–2022 (USD MILLION) 227
TABLE 117 MEDIA & ENTERTAINMENT: NATURAL LANGUAGE PROCESSING MARKET, BY REGION, 2023–2028 (USD MILLION) 227
10.8.1 CONTENT PERSONALIZATION 227
10.8.1.1 Recommendation Engine 228
10.8.1.2 Content Tagging & Curation 228
10.8.2 NEWS & CONTENT ANALYSIS 228
10.8.2.1 Automated News Summarization 228
10.8.2.2 Trend Analysis 229
10.9 MANUFACTURING 229
TABLE 118 MANUFACTURING: NATURAL LANGUAGE PROCESSING MARKET, BY REGION, 2017–2022 (USD MILLION) 229
TABLE 119 MANUFACTURING: NATURAL LANGUAGE PROCESSING MARKET, BY REGION, 2023–2028 (USD MILLION) 230
10.9.1 QUALITY CONTROL 230
10.9.1.1 Defect Detection in Production 230
10.9.1.2 Automated Inspection 230
10.9.2 SUPPLY CHAIN OPTIMIZATION 231
10.9.2.1 Demand Forecasting 231
10.9.2.2 Supplier Communication 231
10.10 TELECOM 232
TABLE 120 TELECOM: NATURAL LANGUAGE PROCESSING MARKET, BY REGION, 2017–2022 (USD MILLION) 232
TABLE 121 TELECOM: NATURAL LANGUAGE PROCESSING MARKET, BY REGION, 2023–2028 (USD MILLION) 232
10.10.1 NETWORK MONITORING & MAINTENANCE 233
10.10.2 AUTOMATED CUSTOMER SERVICE 233
10.11 OTHER VERTICALS 233
TABLE 122 OTHER VERTICALS: NATURAL LANGUAGE PROCESSING MARKET, BY REGION, 2017–2022 (USD MILLION) 234
TABLE 123 OTHER VERTICALS: NATURAL LANGUAGE PROCESSING MARKET, BY REGION, 2023–2028 (USD MILLION) 234
11 NATURAL LANGUAGE PROCESSING MARKET, BY REGION 235
11.1 INTRODUCTION 236
FIGURE 47 INDIA TO WITNESS HIGHEST CAGR DURING FORECAST PERIOD 236
FIGURE 48 ASIA PACIFIC TO ACCOUNT FOR HIGHEST CAGR DURING FORECAST PERIOD 237
TABLE 124 NATURAL LANGUAGE PROCESSING MARKET, BY REGION, 2017–2022 (USD MILLION) 237
TABLE 125 NATURAL LANGUAGE PROCESSING MARKET, BY REGION, 2023–2028 (USD MILLION) 237