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市場調查報告書

商品編碼

1425034

對話AI市場－2024年至2029年預測

Conversational AI Market - Forecasts from 2024 to 2029

出版日期: 2024年01月16日 | 出版商:

Knowledge Sourcing Intelligence | 英文 140 Pages | 商品交期: 最快1-2個工作天內

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簡介目錄

對話式人工智慧市場預計在預測期內複合年成長率為 33.26%。

對話式人工智慧是一種人工推理，賦予電腦掌握、處理和創造人類語言的能力。對話式 AI 將 NLP 和 ML 與聊天機器人等傳統語言技術相結合，使電腦能夠理解、處理和生成人類語言。 NLP 和 ML 用於使聊天機器人能夠以模仿人類互動的方式回應使用者。對話式人工智慧聊天機器人通常是基於規則的，它們的對話由預先定義的答案引導，將使用者引導至特定資訊。 NLP 讓 PC 理解話語和文字並與人對話。基於電腦的會話智慧在重現真實人類討論的能力方面受到限制，並且無意欺騙任何人。然而，對話式人工智慧存在倫理問題，包括偏見、缺乏隱私和安全以及剽竊。

介紹

對話式人工智慧 (CAI) 是一個快速發展的領域，它使用自然語言處理 (NLP) 和機器學習 (ML) 使電腦能夠理解、處理和產生人類語言。 CAI 主要表現為聊天機器人，這是一種基於規則的程序，其對話流基於預定義的答案，旨在引導用戶獲取特定資訊。然而，CAI 引發了諸如偏見、隱私和安全漏洞以及抄襲等道德問題。儘管有這些擔憂，隨著企業和組織採用聊天機器人和其他 CAI 技術來增強客戶服務和參與度，CAI 市場預計將繼續擴大。

促進因素

個人化客戶服務的需求
降低離職率：對話式人工智慧可以透過為客戶問題提供快速有效的解決方案來減少客戶流失。
降低營運成本：
繪製和分析客戶行為：對話式人工智慧透過收集和分析客戶互動資料來幫助映射和分析客戶行為。
越來越關注客戶參與和保留率：對話式人工智慧（也稱為對話式運算）是一個快速發展的領域，正在改變企業與客戶互動的方式。透過提供客製化和高效的客戶支持，企業可以進一步提高消費者的忠誠度和信任度。

主要企業提供的產品

Vertex AI 由 Google 提供，是一個為開發人員和資料科學家加速 ML 模型和 AI 開發的平台。 Google Cloud ML Platform 是一個強大且有效率的機器學習平台，包含適用於 ML 生命週期每個階段的一整套工具和服務，從資料準備和特徵工程到模型訓練、配置和監控。
Microsoft 的 Microsoft Power Virtual Agents 是一個低程式碼/無程式碼平台，用於建置和部署對話式 AI 機器人。 Microsoft Power Apps 是 Microsoft Power Platform 中的低程式碼應用開發平台，可讓公司無需編寫程式碼即可建立自訂業務應用程式。
AWS 提供 Lex 對話式 AI。為開發人員提供完全託管的對話式人工智慧服務。它使用與 Amazon Alexa 相同的技術。

對話式人工智慧市場中自然語言處理（NLP）領域的顯著成長：

由於多種因素，對話式人工智慧市場中的自然語言處理 (NLP) 領域正在實現顯著成長。自然語言處理（NLP）主要是人工智慧的一個分支，它允許電腦理解人類的口頭和書面語言。它有廣泛的應用，包括個人助理、客戶支援聊天機器人和情緒分析。隨著公司尋求轉變經營模式並改善客戶服務和參與度，NLP 受到數位轉型興起的推動。然而，NLP仍然存在句法和語義分析困難以及需要深度學習技術等問題。儘管存在這些挑戰，隨著公司擴大採用聊天機器人和其他對話式人工智慧技術，NLP 的受歡迎程度預計將繼續成長。

亞太地區預計將在對話式人工智慧市場中佔據主要佔有率：

由於各種因素，預計亞太地區將在對話式人工智慧市場中佔據很大佔有率。這些因素包括大量人口、不斷成長的智慧型手機普及以及整個行業的數位化，這些因素正在推動對話式人工智慧在韓國、中國、日本和印度等國家的採用。此外，中國領先的 IT 公司正在對話式人工智慧領域進行大量投資，其中聊天機器人和語音助理正在取得重大進展。該地區也為銀行、醫療保健和電子商務等行業的對話式人工智慧應用提供了前景。隨著協會關於最先進的客戶援助管理和進步的資訊的發展，亞太地區可能會經歷重大發展。然而，對話式人工智慧市場預計將在全球範圍內成長，其中北美和歐洲也佔據很大佔有率。

主要進展：

2023 年 7 月，Conversica 發布了 Conversica Answers v2。這種人工智慧已經改進為與人類相似，允許公司的收入數位助理(RDA) 透過基於網路的存取、簡訊和由電腦智慧生成的電子郵件與每一位潛在客戶、潛在客戶和客戶進行溝通，而無需腳本。允許您進行對話。

Conversational AI is a kind of man-made reasoning that empowers PCs to grasp, process, and create human language. Conversational AI combines NLP and ML with traditional interactive technologies like chatbots to enable computers to understand, process, and generate human language. NLP and ML are used to enable chatbots to respond to users in a way that mimics human interaction. Conversational AI chatbots are typically rules-based, and their conversations are guided by predefined answers that lead users to specific information. figuring out (NLU) and AI (ML) to hold human-like discussions with clients. NLP permits PCs to appreciate discourse and text so they can speak with people. Conversational computer-based intelligence has limits in its capacity to recreate a genuine human discussion and isn't intended to trick somebody. However, there are ethical concerns associated with conversational AI, including bias, lack of privacy and security, and plagiarism.

Introduction:

Conversational AI (CAI) is a fast-growing field that uses natural language processing (NLP) and machine learning (ML) to allow computers to understand, process, and generate human language.. CAI has primarily manifested as chatbots, rules-based programs with conversation flows based on predefined answers designed to guide users through particular information. However, CAI raises ethical concerns such as bias, privacy and security gaps, and plagiarism. Despite these concerns, the CAI market is anticipated to continue expanding as businesses and organizations adopt chatbots and other CAI technologies to enhance customer service and engagement.

Drivers:

Need for personalized customer service: Conversational AI enables businesses to provide personalized customer service by understanding and responding to customer queries in real-time.
Reduced churn: Conversational AI can help reduce customer churn by providing quick and efficient solutions to customer problems. This can help businesses retain customers and reduce the cost of acquiring new ones.
Reducing operational costs: Conversational AI can reduce operational costs by automating repetitive tasks in customer service and support.
Mapping and analyzing customer behavior: Conversational AI can help businesses map and analyze customer behavior by collecting and analyzing data from customer interactions. This can assist organizations with distinguishing patterns and open doors for development.
Growing focus on customer engagement and retention: Conversational AI, also known as conversational computing, is a rapidly growing field that is transforming the way businesses interact with their customers. By giving customized and productive client support, organizations can further develop consumer loyalty and reliability.

Products offered by key companies:

Google offers Vertex AI which is a platform that accelerates ML model and AI development for developers and data scientists. and more efficiently. Google Cloud ML Platform is a powerful and efficient machine learning platform that provides a complete set of tools and services for all stages of the ML lifecycle., from data preparation and feature engineering to model training, deployment, and monitoring.
Microsoft offers Microsoft Power Virtual Agents which is a low-code/no-code platform for building and deploying conversational AI bots. Microsoft Power Apps is a low-code application development platform within the Microsoft Power Platform that enables organizations to create custom business applications without writing code.
AWS offers Lex Conversational AI Fully managed conversational AI service for developers. It is powered by the same technology that powers Amazon Alexa.

Prominent growth in the Natural Language Processing (NLP) segment within the conversational AI market:

The Natural Language Processing (NLP) segment within the conversational AI market has seen prominent growth due to several factors. Natural language processing (NLP) is mainly a field of artificial intelligence that enables computers to understand human language, both spoken and written. This has a wide range of applications, including personal assistants, customer support chatbots, and sentiment analysis.NLP is driven by the rising digital transformation, as businesses seek to transform their business models and improve customer service and engagement. However, there are still challenges associated with NLP, such as the difficulty of syntactic and semantic analysis, and the need for deep learning techniques. Despite these challenges, NLP is expected to continue to grow in popularity as businesses increasingly adopt chatbots and other conversational AI technologies.

The Asia Pacific region is expected to hold a significant share of the conversational AI market:

The Asia Pacific region is expected to hold a significant share of the conversational AI market due to various factors. These factors include a large population, expanding smartphone penetration, and more digitalization across industries, which are promoting the adoption of conversational AI in countries such as South Korea, China, Japan, and India. Additionally, large IT companies in China are significantly investing in conversational AI, and the sector is seeing tremendous advancements in chatbots and voice assistants. The region also offers prospects for conversational AI applications in industries including banking, healthcare, and e-commerce. Because of associations' developing information on state-of-the-art client assistance administrations and advances, the Asia Pacific might have critical development. However, the conversational AI market is expected to grow globally, with North America and Europe also holding significant shares of the market.

Key developments:

In March 2023, Google released Bard, a large language model that can generate text, translate languages, write different kinds of creative content, and answer questions in an informative way.
In July 2023, Conversica launched Conversica Answers v2, with human-like AI improvements that will allow the company's Revenue Digital Assistants (RDAs) to engage every lead, prospect, and customer in unscripted conversations through computer-based intelligence-created web-based visit, SMS, and email.

Segments

By Component

Solutions
Managed Services
Professional Services
Training & Consulting
System Integration & Implementation
Support & Maintenance

By Deployment

On-premises
Cloud

By Type

Chatbots
Intelligent Virtual Assistant (IVA)

By Technology

Natural Language Processing (NLP)
ML and Deep Learning
Automatic Speech Recognition (ASR)

By End-user

BFSI
Media & Entertainment
Retail
IT & Telecommunication
Healthcare
Automotive
Travel and Tourism
Food & Beverages
Others

By Geography

North America
United States
Canada
Mexico
South America
Brazil
Argentina
Others
Europe
United Kingdom
Germany
France
Spain
Others
Middle East and Africa
Saudi Arabia
UAE
Israel
Others
Asia Pacific
Japan
China
India
South Korea
Indonesia
Thailand
Others

1. INTRODUCTION

1.1. Market Overview
1.2. Market Definition
1.3. Scope of the Study
1.4. Market Segmentation
1.5. Currency
1.6. Assumptions
1.7. Base, and Forecast Years Timeline

2. RESEARCH METHODOLOGY

2.1. Research Data
2.2. Research Process

3. EXECUTIVE SUMMARY

3.1. Research Highlights

4. MARKET DYNAMICS

4.1. Market Drivers
4.2. Market Restraints
4.3. Porter's Five Force Analysis
- 4.3.1. Bargaining Power of Suppliers
- 4.3.2. Bargaining Power of Buyers
- 4.3.3. Threat of New Entrants
- 4.3.4. Threat of Substitutes
- 4.3.5. Competitive Rivalry in the Industry
4.4. Industry Value Chain Analysis

5. CONVERSATIONAL AI MARKET, BY COMPONENT

5.1. Introduction
5.2. Solutions
5.3. Managed Services
5.4. Professional Services
- 5.4.1. Training & Consulting
- 5.4.2. System Integration & Implementation
- 5.4.3. Support & Maintenance

6. CONVERSATIONAL AI MARKET, BY DEPLOYMENT

6.1. Introduction
6.2. On-premises
6.3. Cloud

7. CONVERSATIONAL AI MARKET, BY TYPE

7.1. Introduction
7.2. Chatbots
7.3. Intelligent Virtual Assistant (IVA)

8. CONVERSATIONAL AI MARKET, BY TECHNOLOGY

8.1. Introduction
8.2. Natural Language Processing (NLP)
8.3. ML and Deep Learning
8.4. Automatic Speech Recognition (ASR)

9. CONVERSATIONAL AI MARKET, BY END-USER

9.1. Introduction
9.2. BFSI
9.3. Media & Entertainment
9.4. Retail
9.5. IT & Telecommunication
9.6. Healthcare
9.7. Automotive
9.8. Travel and Tourism
9.9. Food & Beverages
9.10. Others

10. CONVERSATIONAL AI MARKET, BY GEOGRAPHY

10.1. Introduction
10.2. North America
- 10.2.1. United States
- 10.2.2. Canada
- 10.2.3. Mexico
10.3. South America
- 10.3.1. Brazil
- 10.3.2. Argentina
- 10.3.3. Others
10.4. Europe
- 10.4.1. United Kingdom
- 10.4.2. Germany
- 10.4.3. France
- 10.4.4. Spain
- 10.4.5. Others
10.5. The Middle East and Africa
- 10.5.1. Saudi Arabia
- 10.5.2. UAE
- 10.5.3. Israel
- 10.5.4. Others
10.6. Asia Pacific
- 10.6.1. Japan
- 10.6.2. China
- 10.6.3. India
- 10.6.4. South Korea
- 10.6.5. Indonesia
- 10.6.6. Thailand
- 10.6.7. Others