全球对话式人工智慧平台软体市场规模（按组件、部署、技术、区域覆盖和预测）

对话式人工智慧平台软体市场规模及预测

对话式人工智慧平台软体市场规模预计在 2024 年达到 2.3482 亿美元，到 2031 年将达到 5.8976 亿美元，2024 年至 2031 年的复合年增长率为 12.2%。

对话式人工智慧平台软体是一个使机器和使用者能够以自然、类似人类的方式进行连接的系统。它利用人工智慧 (AI)、自然语言处理 (NLP) 和机器学习 (ML) 来理解、处理和回应语音和文字等对话形式的使用者输入。这些平台用于创建聊天机器人、虚拟助理和其他人工智慧代理，这些代理可以自动化客户服务、提供建议并协助完成更高级的任务。透过复製人类交互，它们可以改善用户体验、加快交互速度并提高业务效率。

对话式人工智慧平台和软体的未来令人兴奋不已。随着人工智慧技术的进步，这些平台预计将变得更加直观和情境感知，从而实现更丰富、更有意义的对话。它们将嵌入医疗、教育、银行和零售等各行各业，提供客製化服务、预测分析和自动化决策。此外，随着多模态人工智慧（结合语音、文字和视觉输入）的出现，对话式人工智慧将改变我们与科技的互动方式，使虚拟助理更加人性化，并可能在个人和职业环境中都变得不可或缺。

全球对话式人工智慧平台软体市场动态

影响全球对话式人工智慧平台软体市场的关键市场动态是：

关键市场驱动因素

人工智慧客户服务解决方案的采用率不断提高：对有效客户服务的需求不断增长，推动了对话式人工智慧技术的采用。预计 70% 的客户接触点将包括机器学习应用程式、聊天机器人和行动传讯等新兴技术，高于 2018 年的 15%。这一显着成长反映了人工智慧对话系统在客户支援领域的快速应用。

个人化使用者体验需求日益增长：对话式人工智慧解决方案使企业能够与客户进行更具针对性的互动。 91% 的消费者更倾向于选择能够识别他们、记住他们并提供相关优惠和推荐的品牌。这项数据凸显了对话式人工智慧技术能够成功实现个人化的价值。

降低成本，提升营运效率：对话式人工智慧平台的实施将大幅降低营运成本。光是聊天机器人一项，预计到2022年每年就能节省超过80亿美元，而2017年仅需2,000万美元。如此庞大的成本节约正鼓励企业采用对话式人工智慧技术，因为它有可能实现日常客户互动的自动化，最大限度地减少对人工客服的依赖，并提高处理大量询问的效率。这些平台能够实现更快的反应速度和全天候服务，在提升客户体验的同时降低成本。

主要挑战

资料隐私与安全：对话式人工智慧平台管理着大量敏感的用户数据，包括个人资讯和财务资讯。随着《一般资料保护规范》（GDPR）和《加州消费者隐私法案》（CCPA）等法规日益严格，确保合规至关重要。为了避免资料洩露，人工智慧系统需要强大的加密和安全措施。即使是微小的安全漏洞也可能损害公司品牌，削弱用户信任，并因法律后果而限制其采用。安全问题往往会在拥有强大法律体制的行业（例如医疗保健和金融）引发摩擦。

响应准确性和自然度：为了创造价值，人工智慧系统必须产生准确且自然的响应。训练不足的模型可能导致误解、错误答案和尴尬的交互作用。挑战在于使用多样化、高品质的资料来训练人工智慧模型，以捕捉人类语言的细微差别。管理多种语言和方言尤其具有挑战性。不一致的回应会造成糟糕的使用者体验，阻碍参与度，削弱对平台的信任，并阻碍其在客户服务、电子商务和其他行业的应用。

与旧有系统整合：许多公司仍在使用未考虑人工智慧设计的旧有系统。将对话式人工智慧平台整合到如此过时的基础设施中，会带来巨大的技术挑战，包括相容性、资料存取和工作流程。公司必须投资系统现代化或创建API来弥合新旧技术之间的差距。此类整合挑战可能会延迟人工智慧的采用、增加成本并限制其潜在优势，所有这些都会影响市场成长。

主要趋势：

自然语言处理 (NLP) 的应用日益广泛：自然语言处理 (NLP) 的进步正在推动对话式人工智慧平台的日臻完善。 NLP 帮助人工智慧理解人类对话的脉络、意图和细微差别，从而实现更准确、更自然的对话。这一趋势正推动市场向前发展，因为它使人工智慧更易于使用，最大限度地减少沟通误传，并提升消费者体验。通用预测 (GPT) 等深度学习模型的兴起进一步增强了这种能力，使人工智慧能够产生更接近人类的反应，从而实现更广泛的应用。

多模态人工智慧介面的成长：多模态人工智慧融合了语音、文字和视觉互动，正日益普及。用户可透过多种管道与人工智慧互动，包括语音助理、聊天机器人和影像识别，从而提升用户体验。这一趋势源于对跨平台和设备、适应性更强的人工智慧解决方案的需求。多模态人工智慧透过提供更具吸引力和互动性的体验来提升用户幸福感，从而推动其应用范围的扩大，尤其是在零售、医疗保健和客户服务等领域。

语音商务与客户支援：在 Alexa 和 Google Assistant 等智慧助理的推动下，语音商务的兴起正在推动对话式人工智慧平台的需求。企业正在采用人工智慧语音技术来改善客户服务，并提供更流畅的购买体验。这一趋势正推动企业投资对话式人工智慧，以保持竞争力。语音介面支援免持即时互动，这在电子商务中至关重要，它使消费者的互动更加便捷，并带来更高的转换率和客户维繫。

目录

第一章 全球对话式人工智慧平台软体市场简介

• 市场介绍
• 调查范围
• 先决条件

第二章执行摘要

第三章：已验证的市场研究调查方法

• 资料探勘
• 验证
• 第一手资料
• 资料来源列表

第四章 全球对话式人工智慧平台软体市场展望

• 概述
• 市场动态
  • 驱动程式
  • 抑制因素
  • 机会
• 波特五力模型
• 价值链分析

5. 全球对话式人工智慧平台软体市场（按类型）

• 概述
• 云端基础
• 本地部署

6. 全球对话式人工智慧平台软体市场（按应用）

• 概述
• 小型企业
• 大公司

7. 全球对话式人工智慧平台软体市场（按地区）

• 概述
• 北美洲
  • 美国
  • 加拿大
  • 墨西哥
• 欧洲
  • 德国
  • 英国
  • 法国
  • 其他欧洲国家
• 亚太地区
  • 中国
  • 日本
  • 印度
  • 其他亚太地区
• 世界其他地区
  • 拉丁美洲
  • 中东

第八章：全球对话式人工智慧平台软体市场的竞争格局

• 概述
• 各公司市场排名
• 主要发展策略

第九章：公司简介

• Acobot
• ExecVision
• FunnelDash
• Gong.io
• Activechat
• LivePerson
• Marchex
• LiveChat
• Brazen
• Continually

第十章 附录

• 相关调查

Conversational AI Platform Software Market Size And Forecast

Conversational AI platform Software Market size was valued at USD 234.82 Million in 2024 and is projected to reach USD 589.76 Million by 2031, growing at a CAGR of 12.2% from 2024 to 2031.

Conversational AI Platform Software is a system that allows machines and users to connect in a natural, human-like way. It uses artificial intelligence (AI), natural language processing (NLP), and machine learning (ML) to comprehend, process, and reply to user inputs in conversational formats like voice or text. These platforms are used to create chatbots, virtual assistants, and other AI-powered agents that can automate customer service, provide recommendations, and even help with more sophisticated tasks. By replicating human dialogue, they improve user experiences, expedite interactions, and increase corporate operational efficiency.

The future prospects of conversational AI platform software is enormous and intriguing. As AI technology progresses, these platforms are projected to become more intuitive and context-aware, allowing for richer and more meaningful conversations. They will be incorporated into a variety of industries, including healthcare, education, banking, and retail, to automate tailored services, predictive analytics, and decision-making. Furthermore, with the emergence of multimodal AI (which combines voice, text, and visual inputs), conversational AI may alter how we engage with technology, making virtual assistants more human-like and necessary in both personal and professional settings.

Global Conversational AI Platform Software Market Dynamics

The key market dynamics that are shaping the global conversational AI platform software market include:

Key Market Drivers:

Increasing Adoption of AI-Powered Customer Service Solutions: The increasing demand for effective customer service is driving the deployment of conversational AI technologies. 70% of customer contacts were predicted to include emerging technologies such as machine learning apps, chatbots, and mobile messaging, up from 15% in 2018. This huge increase reflects the fast adoption of AI-powered conversational systems in customer support.

Rising Demand for Personalized User Experiences: Conversational AI solutions allow organizations to create more tailored interactions with their customers. 91% of consumers prefer to purchase with brands that identify, remember, and make relevant offers and recommendations. This figure emphasizes the value of personalization, which conversational AI technologies can provide successfully.

Cost Reduction and Operational Efficiency: Implementing conversational AI platforms drastically decrease operating expenses, with chatbots alone expected to save enterprises over $8 billion per year by 2022, compared to only $20 million in 2017. This enormous rise in cost savings is prompting organizations to adopt conversational AI technologies due to their potential to automate routine customer interactions, minimize reliance on human agents, and improve efficiency in dealing with high-volume inquiries. These platforms provide faster reaction times and 24/7 service availability, improving customer experience while reducing costs.

Key Challenges:

Data Privacy and Security: Conversational AI platforms manage enormous amounts of sensitive user data, such as personal and financial information. As rules like GDPR and CCPA get more stringent, ensuring compliance is important. To avoid data breaches, AI systems must have strong encryption and security measures. Even modest security flaws can harm a company's brand, erode user trust, and lead to legal ramifications that limit adoption. Security problems frequently cause friction in industries such as healthcare and finance, where strong legal frameworks are in place.

Accuracy and Naturalness of Responses: To deliver value, AI systems must produce accurate and natural-sounding responses. Poorly trained models might result in misinterpretation, erroneous responses, and awkward dialogue. The difficulty is to train AI models with diverse, high-quality data that captures the nuances of human language. It is especially challenging to manage many languages and dialects. Inconsistent responses degrade user experience, impede engagement, and erode trust in the platform, hurting adoption in customer service, e-commerce, and other industries.

Integration with Legacy Systems: Many firms use legacy systems that were not designed with AI in mind. Integrating conversational AI platforms into these older infrastructures presents substantial technological problems, such as compatibility, data access, and workflows. Companies must invest in modernizing their systems or creating APIs to bridge the gap between old and new technologies. These integration issues can cause deployment delays, increase costs, and limit the potential benefits of AI, all of which have an impact on market growth.

Key Trends:

Increased Use of Natural Language Processing (NLP): Advances in Natural Language Processing (NLP) are increasing the sophistication of conversational AI platforms. NLP helps AI to grasp the context, intent, and nuances of human speech, resulting in more accurate and natural conversations. This trend is propelling the market forward by making AI more user-friendly, minimizing miscommunication, and increasing consumer experiences. The rise of deep learning models such as GPT has taken this capability even further, allowing AI to generate more human-like responses, resulting in widespread use.

Growth in Multimodal AI Interfaces: Multimodal AI, which combines speech, text, and visual interactions, is gaining traction. Users can interact with AI through a variety of channels, including voice assistants, chatbots, and image recognition, which improves the user experience. This trend is being driven by the demand for more adaptable and adaptive AI solutions that can work across several platforms and devices. Multimodal AI increases user happiness by providing more engaging and interactive experiences, which leads to better adoption rates, especially in areas such as retail, healthcare, and customer service.

Voice Commerce and Customer Support: The advent of voice commerce, led by smart assistants such as Alexa and Google Assistant, is increasing demand for conversational AI platforms. Businesses are adopting AI-powered voice technologies to improve customer service and deliver more seamless purchasing experiences. This trend is driving corporations to invest in conversational AI in order to remain competitive. Voice interfaces make interactions more convenient for consumers by enabling hands-free and real-time involvement, which is critical in e-commerce, resulting in increased conversion rates and customer retention.

Global Conversational AI Platform Software Market Regional Analysis

Here is a more detailed regional analysis of the global conversational AI platform software market:

North America:

North America continues to dominate the global AI Platform Software market, owing to its strong technological infrastructure, significant expenditures, and widespread usage across numerous sectors. This leadership is supported by major federal funding for AI research, such as the National Science Foundation's $1.9 billion allocation in fiscal year 2023, up from $1.5 billion in 2021. AI adoption is growing, with McKinsey & Company projecting that 56% of North American enterprises would have integrated AI into at least one function by 2021, and the FDA has authorized over 300 AI-enabled medical devices.

North America region benefits from a strong startup ecosystem, as seen by AI startups in the United States obtaining $50 billion in venture capital funding in 2021, up 55% from the previous year. This flood of finance fuels innovation and the creation of new AI applications.

The U.S. Bureau of Labor Statistics predicts that employment in AI-related positions will increase by 15% between 2021 and 2031, highlighting the sector's growing economic importance. In the financial sector, 75% of large US institutions have already implemented AI strategies, highlighting the importance of AI in improving fraud detection, risk management, and tailored services. These factors contribute to North America's sustained leadership and growth in the AI Platform Software market.

Asia-Pacific:

The Asia Pacific region is experiencing the growth in the AI Platform Software market, owing to rapid economic expansion, increased digitalization, and significant government assistance. According to International Data Corporation (IDC), the region's AI industry, excluding Japan, is predicted to develop at a compound annual growth rate (CAGR) of 50.6% between 2020 and 2024, reaching $29.3 billion in 2024. China, India, and Japan are important contributors, with China seeking to grow its AI core industry to more than 1 trillion yuan by 2030 and India expected to achieve a $7.8 billion AI market by 2025. The growing adoption of AI across a variety of areas, including healthcare and fintech, is fueling this expansion.

The Asia Pacific region benefits from significant government programs such as China's New Generation Artificial Intelligence Development Plan and India's National Strategy for Artificial Intelligence, both of which give financial and strategic assistance. The availability of competent talent-China produces 50,000 AI grads every year, while India produces over 2.6 million STEM graduates each year-ensures a strong workforce for AI development. Significant expenditures in AI by both governments and the commercial sector, combined with a high rate of AI adoption in industries such as finance and healthcare, demonstrate the region's growing importance in the global AI scene.

Global Conversational AI Platform Software Market: Segmentation Analysis

The Global Conversational AI platform Software Market is Segmented on the basis of Component, Deployment, Technology, And Geography.

Conversational AI Platform Software Market, By Component

Solutions

Services

Based on Component, the market is bifurcated into Solutions and Services. In the Conversational AI platform software market, the Solutions segment is currently dominant and steadily advancing. This section comprises AI-powered chatbots, virtual assistants, and natural language processing tools that improve consumer engagement and automate procedures. The growing use of these technologies by enterprises looking to increase customer service efficiency and personalization fuels their dominance. The Services section, which includes consultancy, integration, and support services, is rapidly growing as a result of the increased demand for specialized skills and ongoing maintenance to maximize AI deployment and performance.

Conversational AI Platform Software Market, By Deployment

Cloud-Based

On-Premises

Based on Deployment, the market is segmented into Cloud-Based and On-Premises. The Cloud-Based deployment sector is dominant and rapidly expanding. This is largely due to the flexibility, scalability, and cost-effectiveness of cloud solutions, which enable organizations to simply scale their AI capabilities and link them with other cloud services. Cloud-based platforms also benefit from frequent updates and improvements, allowing customers to access the most recent features without making large infrastructure investments. The On-Premises deployment category is increasing at a more gradual pace, owing to higher upfront costs and more complex maintenance requirements. It is still relevant for enterprises with severe data security and compliance requirements who wish to keep their AI systems within their IT infrastructure.

Conversational AI Platform Software Market, By Technology

Natural Language Processing (NLP)

Machine Learning (ML)

Text-to-Speech (TTS)

Based on Technology, the market is divided into Natural Language Processing (NLP), Machine Learning (ML), and Text-to-Speech (TTS). Machine Learning (ML) is a major and constantly expanding segment. ML's widespread use in industries such as finance, healthcare, and e-commerce fuels its domination, allowing firms to automate decision-making, increase predictive analytics, and improve operational efficiency. The segment's growth is being driven by algorithm breakthroughs, increased data availability, and significant expenditures in machine learning technology. Natural Language Processing (NLP) is the fastest-expanding segment. NLP's capacity to allow robots to understand, interpret, and synthesize human language is increasingly being used in applications such as chatbots, virtual assistants, and sentiment analysis. The rapid development of NLP capabilities, fueled by advances in deep learning and huge language models, is hastening its adoption and expansion across a wide range of industries.

Conversational AI Platform Software Market, By Geography

North America

Europe

Asia Pacific

Rest of the world

On the basis of geographical analysis, the Global Conversational AI platform Software Market is classified into North America, Europe, Asia Pacific, and Rest of the world. North America is currently leading the AI platform software market, led by tech behemoths like Google, Microsoft, and IBM. However, Asia Pacific is emerging as the fastest-growing area, thanks to high economic expansion, a big population, and increased digitalization. Countries such as China and India are leading the way, with huge investments in AI research and development.

Key Players

The "Global Conversational AI Platform Software Market" study report will provide valuable insight with an emphasis on the global market. The major players in the market are Microsoft (Azure Bot Service), Google (Dialogflow), IBM (Watson Assistant), Amazon Web Services (AWS), Oracle (Digital Assistant), SAP (Conversational AI), Nuance Communications, Rasa, Kore.ai, Haptik, Avaamo, SoundHound AI, Invoca and Boost.ai. The competitive landscape section also includes key development strategies, market share, and market ranking analysis of the above-mentioned players globally.

Our market analysis also entails a section solely dedicated to such major players wherein our analysts provide an insight into the financial statements of all the major players, along with product benchmarking and SWOT analysis. The competitive landscape section also includes key development strategies, market share, and market ranking analysis of the above-mentioned players globally.

TABLE OF CONTENTS

1 INTRODUCTION OF GLOBAL CONVERSATIONAL AI PLATFORM SOFTWARE MARKET

• 1.1 Introduction of the Market
• 1.2 Scope of Report
• 1.3 Assumptions

2 EXECUTIVE SUMMARY

3 RESEARCH METHODOLOGY OF VERIFIED MARKET RESEARCH

• 3.1 Data Mining
• 3.2 Validation
• 3.3 Primary Interviews
• 3.4 List of Data Sources

4 GLOBAL CONVERSATIONAL AI PLATFORM SOFTWARE MARKET OUTLOOK

• 4.1 Overview
• 4.2 Market Dynamics
  • 4.2.1 Drivers
  • 4.2.2 Restraints
  • 4.2.3 Opportunities
• 4.3 Porters Five Force Model
• 4.4 Value Chain Analysis

5 GLOBAL CONVERSATIONAL AI PLATFORM SOFTWARE MARKET, BY TYPE

• 5.1 Overview
• 5.2 Cloud-based
• 5.3 On-Premises

6 GLOBAL CONVERSATIONAL AI PLATFORM SOFTWARE MARKET, BY APPLICATION

• 6.1 Overview
• 6.2 Small And Medium Enterprises
• 6.3 Large Enterprises

7 GLOBAL CONVERSATIONAL AI PLATFORM SOFTWARE MARKET, BY GEOGRAPHY

• 7.1 Overview
• 7.2 North America
  • 7.2.1 U.S.
  • 7.2.2 Canada
  • 7.2.3 Mexico
• 7.3 Europe
  • 7.3.1 Germany
  • 7.3.2 U.K.
  • 7.3.3 France
  • 7.3.4 Rest of Europe
• 7.4 Asia Pacific
  • 7.4.1 China
  • 7.4.2 Japan
  • 7.4.3 India
  • 7.4.4 Rest of Asia Pacific
• 7.5 Rest of the World
  • 7.5.1 Latin America
  • 7.5.2 Middle East

8 GLOBAL CONVERSATIONAL AI PLATFORM SOFTWARE MARKET COMPETITIVE LANDSCAPE

• 8.1 Overview
• 8.2 Company Market Ranking
• 8.3 Key Development Strategies

9 COMPANY PROFILES

• 9.1 Acobot
  • 9.1.1 Overview
  • 9.1.2 Financial Performance
  • 9.1.3 Product Outlook
  • 9.1.4 Key Developments
• 9.2 ExecVision
  • 9.2.1 Overview
  • 9.2.2 Financial Performance
  • 9.2.3 Product Outlook
  • 9.2.4 Key Developments
• 9.3 FunnelDash
  • 9.3.1 Overview
  • 9.3.2 Financial Performance
  • 9.3.3 Product Outlook
  • 9.3.4 Key Developments
• 9.4 Gong.io
  • 9.4.1 Overview
  • 9.4.2 Financial Performance
  • 9.4.3 Product Outlook
  • 9.4.4 Key Developments
• 9.5 Activechat
  • 9.5.1 Overview
  • 9.5.2 Financial Performance
  • 9.5.3 Product Outlook
  • 9.5.4 Key Developments
• 9.6 LivePerson
  • 9.6.1 Overview
  • 9.6.2 Financial Performance
  • 9.6.3 Product Outlook
  • 9.6.4 Key Developments
• 9.7 Marchex
  • 9.7.1 Overview
  • 9.7.2 Financial Performance
  • 9.7.3 Product Outlook
  • 9.7.4 Key Developments
• 9.8 LiveChat
  • 9.8.1 Overview
  • 9.8.2 Financial Performance
  • 9.8.3 Product Outlook
  • 9.8.4 Key Developments
• 9.9 Brazen
  • 9.9.1 Overview
  • 9.9.2 Financial Performance
  • 9.9.3 Product Outlook
  • 9.9.4 Key Developments
• 9.10 Continually
  • 9.10.1 Overview
  • 9.10.2 Financial Performance
  • 9.10.3 Product Outlook
  • 9.10.4 Key Developments

10 Appendix

• 10.1 Related Research