대화형 AI 시장 예측(-2030년) : 오퍼링별, 도입 모드별, 대화 인터페이스별, 사용 사례별, 기술별, 최종사용자별, 지역별 세계 분석

According to Stratistics MRC, the Global Conversational AI Market is accounted for $11.6 billion in 2024 and is expected to reach $42.2 billion by 2030, growing at a CAGR of 23.9% during the forecast period. Artificial intelligence (AI) that mimics human speech and text interactions is known as conversational AI. It uses machine learning, speech recognition, and natural language processing (NLP) to comprehend user inquiries and provide insightful answers. Virtual assistants, chatbots, and interactive voice response systems are applications that are frequently used in various industries to improve user experiences, expedite communication, and improve customer support. Conversational AI attempts to make interactions between users and systems smooth and interesting by imitating human speech.

According to Gartner, there is an anticipated 24% increase in call center investments in 2024, driven by conversational AI tools.

Market Dynamics:

Driver:

Increasing demand for Ai-driven customer support

Businesses are increasingly adopting conversational AI solutions to automate customer interactions, leading to operational efficiency and cost savings. AI-powered chatbots and virtual assistants can handle high volumes of customer queries 24/7, providing instant responses and personalized experiences. This trend is particularly evident in industries such as retail, banking, and e-commerce, where customer service is crucial. The ability of conversational AI to scale support operations while maintaining quality is driving its widespread adoption.

Restraint:

Limited language and regional capabilities

Most conversational AI products currently offer support for a limited number of languages, with better compatibility for English. This limitation hinders the global adoption of conversational AI solutions, especially in regions where English is not the primary language. The challenge of developing AI models that can understand and respond accurately to various languages, dialects, and cultural nuances is substantial. This constraint can potentially slow down market growth in non-English-speaking regions and limit the effectiveness of conversational AI in diverse global markets.

Opportunity:

Usage of omnichannel communication

Integrating conversational AI across multiple channels, such as websites, mobile apps, social media platforms, and voice-activated devices, enhances the overall customer experience. This approach allows businesses to maintain consistent and contextual interactions with customers across various touchpoints. Omnichannel deployment enables seamless customer journeys, improves engagement, and provides valuable insights into customer behavior. As businesses strive to offer cohesive experiences across all channels, the demand for versatile conversational AI solutions capable of supporting omnichannel strategies is expected to grow substantially.

Threat:

Data privacy

Data privacy concerns pose a significant threat to the conversational AI market. As conversational AI systems collect and process large amounts of personal and potentially sensitive user data, there are growing concerns about data security, privacy breaches, and compliance with data protection regulations. Users may be hesitant to engage with AI-powered systems if they perceive a risk to their personal information. Additionally, stringent data protection laws like GDPR in Europe and CCPA in California require businesses to implement robust data protection measures. Failure to address these concerns adequately could lead to reduced user trust and adoption, potentially hindering market growth.

Covid-19 Impact:

The COVID-19 pandemic had a positive impact on the conversational AI market. As businesses shifted to remote operations and digital interactions, the demand for AI-powered customer support and engagement solutions surged. Conversational AI technologies were rapidly adopted to handle increased customer inquiries, automate processes, and maintain business continuity. The pandemic accelerated digital transformation efforts, leading to increased investments in AI technologies, including conversational AI, to enhance customer experiences and operational efficiency.

The software segment is expected to be the largest during the forecast period

The software segment is predicted to secure the largest market share throughout the forecast period. This dominance can be attributed to the increasing adoption of conversational AI platforms across various industries. Software solutions, including natural language processing (NLP) engines, machine learning algorithms, and dialogue management systems, form the core of conversational AI capabilities. These software components enable businesses to create, deploy, and manage intelligent virtual assistants and chatbots. The flexibility, scalability, and continuous improvements in AI software technologies contribute to its larger market share as organizations seek to enhance customer interactions and automate processes.

The cloud-based segment is expected to have the highest CAGR during the forecast period

The cloud-based segment is projected to have the highest CAGR in the conversational AI market during the extrapolated period. This rapid growth is driven by the numerous advantages offered by cloud-based solutions, including scalability, cost-effectiveness, and ease of deployment. Cloud-based conversational AI platforms allow businesses to quickly implement and scale their AI-powered customer engagement solutions without significant upfront infrastructure investments. The flexibility to integrate with existing systems and the ability to leverage advanced AI capabilities through cloud services contribute to the segment's high growth rate.

Region with largest share:

The Asia Pacific region is projected to account for the largest market share during the forecast period. This dominance is attributed to rapid digitalization, increasing adoption of AI technologies, and the presence of large consumer markets in countries like China and India. The region's strong focus on technological innovation, coupled with government initiatives promoting AI adoption, contributes to its market leadership. The growing e-commerce sector, expanding digital payment systems, and increasing smartphone penetration further drive the demand for conversational AI solutions in customer service and engagement applications across various industries.

Region with highest CAGR:

The Asia Pacific region is projected to achieve the highest CAGR during the forecast period. This rapid growth is fueled by factors such as the increasing awareness of AI technologies, rising investments in digital transformation, and the growing demand for automated customer service solutions. The region's large and tech-savvy population, coupled with the rapid expansion of online businesses, creates fertile ground for conversational AI adoption. Additionally, government initiatives supporting AI development and the presence of numerous tech startups contribute to the region's accelerated growth in the conversational AI market.

Key players in the market

Some of the key players in Conversational AI Market include Microsoft, IBM, Google, Amazon Web Services (AWS), SAP, Oracle, Nuance Communications, Artificial Solutions, Kore.ai, LivePerson, Avaamo, Conversica, Haptik, Yellow.ai, Cognigy.AI, Amelia, Verint, and Boost.ai.

Key Developments:

In October 2024, at the 10th edition of the Google for India event, Google announced Hindi support for Google Gemini Live, a more sophisticated version of its Gemini AI chatbot. Gemini Live will soon expand to include eight additional Indian languages. Google also revealed that Indian users listen to AI Overview responses more frequently than users in other countries.

In August 2024, AWS has entered into a Strategic Collaboration Agreement with PolyAI, a leader in customer-led conversational AI solutions. This collaboration aims to accelerate the adoption of generative voice AI capabilities within enterprise contact centers. PolyAI will leverage Amazon SageMaker and Amazon Bedrock to train and fine-tune an integrated suite of speech recognition, large language models (LLMs), and text-to-speech models.

Offerings Covered:

• Software
• Services

Deployment Modes Covered:

• On-Premises
• Cloud

Conversational Interfaces Covered:

• Chatbots
• Intelligent Virtual Assistants (IVAs)
• Interactive Voice Response (IVR) Systems

Use Cases Covered:

• Customer Support & Engagement
• Personal Assistants
• Branding & Marketing
• Employee Communication
• Contact Centers
• Sales & E-commerce
• Other Use Cases

Technologies Covered:

• Natural Language Processing (NLP)
• Automated Speech Recognition (ASR)
• Machine Learning (ML)
• Deep Learning
• Other Technologies

End Users Covered:

• Banking, Financial Services, & Insurance (BFSI)
• Retail & E-commerce
• Healthcare
• Media & Entertainment
• Automotive
• Telecom
• Travel & Hospitality
• Government
• 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 End User Analysis
• 3.8 Emerging Markets
• 3.9 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 Conversational AI Market, By Offering

• 5.1 Introduction
• 5.2 Software
• 5.3 Services

6 Global Conversational AI Market, By Deployment Mode

• 6.1 Introduction
• 6.2 On-Premises
• 6.3 Cloud

7 Global Conversational AI Market, By Conversational Interface

• 7.1 Introduction
• 7.2 Chatbots
• 7.3 Intelligent Virtual Assistants (IVAs)
• 7.4 Interactive Voice Response (IVR) Systems

8 Global Conversational AI Market, By Use Case

• 8.1 Introduction
• 8.2 Customer Support & Engagement
• 8.3 Personal Assistants
• 8.4 Branding & Marketing
• 8.5 Employee Communication
• 8.6 Contact Centers
• 8.7 Sales & E-commerce
• 8.8 Other Use Cases

9 Global Conversational AI Market, By Technology

• 9.1 Introduction
• 9.2 Natural Language Processing (NLP)
• 9.3 Automated Speech Recognition (ASR)
• 9.4 Machine Learning (ML)
• 9.5 Deep Learning
• 9.6 Other Technologies

10 Global Conversational AI Market, By End User

• 10.1 Introduction
• 10.2 Banking, Financial Services, & Insurance (BFSI)
• 10.3 Retail & E-commerce
• 10.4 Healthcare
• 10.5 Media & Entertainment
• 10.6 Automotive
• 10.7 Telecom
• 10.8 Travel & Hospitality
• 10.9 Government
• 10.10 Other End Users

11 Global Conversational AI 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 Microsoft
• 13.2 IBM
• 13.3 Google
• 13.4 Amazon Web Services (AWS)
• 13.5 SAP
• 13.6 Oracle
• 13.7 Nuance Communications
• 13.8 Artificial Solutions
• 13.9 Kore.ai
• 13.10 LivePerson
• 13.11 Avaamo
• 13.12 Conversica
• 13.13 Haptik
• 13.14 Yellow.ai
• 13.15 Cognigy.AI
• 13.16 Amelia
• 13.17 Verint
• 13.18 Boost.ai