세계의 고객 서비스용 AI 시장 : 최종사용자별, 제품별, 기술별, 고객 인터랙션 채널별, 지역별 - 예측(-2030년)

AI for Customer Service Market by Product Type (AI Agents, Recommendation Systems, Workflow Automation, Content Generation, Customer Journey Analytics, Service Quality Management) - Global Forecast to 2030

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한글목차

고객 서비스용 AI 시장 규모는 2024년 120억 6,000만 달러에서 2030년 478억 2,000만 달러로 성장하고, 예측 기간 동안 25.8%의 연평균 복합 성장률(CAGR)을 나타낼 것으로 예상됩니다.

AI 기반 챗봇과 가상 비서는 효율적이고 개인화된 지원을 제공함으로써 고객 서비스를 혁신적으로 변화시키고 있습니다. 이러한 기술을 통해 기업은 24시간 365일 고객과 소통할 수 있으며, 문의에 즉각적으로 대응하여 대기 시간을 크게 단축하고 만족도를 높일 수 있습니다. 챗봇은 여러 대화를 동시에 처리할 수 있기 때문에 서비스 품질 저하 없이 피크 시 확장성을 확보할 수 있습니다. 또한, 고급 알고리즘을 활용하여 고객 데이터를 분석함으로써 더 깊은 관계를 형성할 수 있는 맞춤형 추천과 상황에 맞는 상호 작용을 가능하게 합니다. 이러한 개인화는 사용자 경험을 향상시킬 뿐만 아니라 고객 충성도를 높일 수 있습니다. 기업들이 이러한 AI 솔루션을 점점 더 많이 채택함에 따라 챗봇은 현대의 고객 참여 전략에서 필수적인 도구가 되어 업무를 간소화하고 전반적인 서비스 품질을 향상시키는 데 도움이 되고 있습니다.

조사 범위
조사 대상 연도	2019-2030년
기준 연도	2023년
예측 기간	2024-2030년
검토 단위	(100만 달러/10달러)
부문별	최종사용자별, 제품별, 기술별, 고객 상호작용 채널별, 지역별
대상 지역	북미, 유럽, 아시아태평양, 중동/아프리카, 라틴아메리카, 기타 지역

헬스케어 및 생명과학 분야는 혁신적인 인게이지먼트 전략으로 고객 서비스 시장을 선도하고 있습니다. 개인화된 인터랙션과 디지털 채널을 결합하여 고객 경험을 향상시키는 하이브리드 인게이지먼트 모델이 부상하고 있습니다. 기업들은 AI 기술을 활용하여 맞춤형 커뮤니케이션, 셀프 서비스 분석, 지능형 환자 서비스를 제공하고 보다 신속한 대응 환경을 조성하기 위해 AI 기술을 활용하고 있습니다. 디지털 전환으로 전환하면서 원격 진료와 가상 방문이 보편화되어 환자가 의료진과 편리하게 소통할 수 있는 환경이 조성되고 있습니다. 또한, 조직은 개인화된 인사이트와 맞춤형 케어 여정에 중점을 두어 환자의 요구가 효과적으로 충족될 수 있도록 하고 있습니다. 이러한 진화는 서비스 제공을 개선할 뿐만 아니라 급변하는 상황에서 환자의 전반적인 만족도와 충성도를 높이는 데에도 도움이 될 수 있습니다.

아시아태평양은 빠른 기술 도입, 대규모 소비자 기반, 고객 경험 향상에 대한 수요 증가, 전자상거래, 모바일 서비스의 부상, 소매, 은행, 통신 등 다양한 산업의 디지털 혁신 노력으로 인해 AI를 활용한 고객 서비스 시장을 선도하고 있습니다. 디지털 전환에 대한 노력은 보다 효율적이고 개인화된 고객 대응의 필요성을 높이고 있습니다. 이러한 추세를 주도하고 있는 국가는 인도와 중국입니다. 인도에서는 서비스 제공 개선과 비용 절감에 초점을 맞추고 있으며, 중국에서는 AI가 음성 비서 및 챗봇과 같은 스마트한 고객 서비스 솔루션에 통합되어 수백만 명의 고객에게 서비스를 제공합니다. 이러한 혁신은 고객 만족도를 높이고, 업무를 간소화하며, 소비자와 기업 모두의 높아진 기대에 부응하고 있습니다.

세계의 고객 서비스용 AI 시장에 대해 조사했으며, 최종사용자별, 제품별, 기술별, 고객 상호작용 채널별, 지역별 동향, 시장 진출기업 프로파일 등의 정보를 정리하여 전해드립니다.

목차

제1장 서론

제2장 조사 방법

제3장 주요 요약

제4장 프리미엄 인사이트

제5장 시장 개요와 업계 동향

• 서론
• 시장 역학
• 업계 동향
  • 고객 서비스용 AI 시장 발전
  • 사례 연구 분석
  • 생태계 분석
  • 기술 분석
  • 규제 상황
  • 공급망 분석
  • Porter의 Five Forces 분석
  • 주요 컨퍼런스 및 이벤트(2025년-2026년)
  • 주요 이해관계자와 구입 기준
  • 가격 분석
  • 특허 분석
  • 고객의 비즈니스에 영향을 미치는 동향/혼란
  • 투자 상황과 자금조달 시나리오
  • 생성형 AI가 고객 서비스용 AI 시장에 미치는 영향

제6장 고객 서비스용 AI 시장(최종사용자별)

• 서론
• 은행/금융서비스/보험(BFSI)
• 미디어 및 엔터테인먼트
• 통신
• 정부 및 공공 부문
• 헬스케어 및 생명과학
• 제조
• 소매 및 E-Commerce
• 테크놀러지 및 소프트웨어
• 여행 및 호스피탈리티
• 운송 및 물류
• 기타

제7장 고객 서비스용 AI 시장(제품별)

• 서론
• 유형
• 전개 모드별
• 고객 서비스 제공 모드별
• 기능 분야별

제8장 고객 서비스용 AI 시장(기술별)

• 서론
  • 생성형 AI
  • 기타

제9장 고객 서비스용 AI 시장(고객 인터랙션 채널별)

• 서론
• 텍스트 및 메일
• 음성
• 비디오 및 비주얼
• 옴니채널

제10장 고객 서비스용 AI 시장(지역별)

• 서론
• 북미
  • 북미 : 고객 서비스용 AI 시장 성장 촉진요인
  • 북미 : 거시경제에 대한 영향
  • 미국
  • 캐나다
• 유럽
  • 유럽 : 고객 서비스용 AI 시장 성장 촉진요인
  • 유럽 : 거시경제에 대한 영향
  • 영국
  • 독일
  • 프랑스
  • 이탈리아
  • 스페인
  • 기타
• 아시아태평양
  • 아시아태평양 : 고객 서비스용 AI 시장 성장 촉진요인
  • 아시아태평양 : 거시경제에 대한 영향
  • 중국
  • 일본
  • 인도
  • 한국
  • 호주 및 뉴질랜드
  • ASEAN 국가
  • 기타
• 중동 및 아프리카
  • 중동 및 아프리카 : 고객 서비스용 AI 시장 성장 촉진요인
  • 중동 및 아프리카 : 거시경제에 대한 영향
  • 중동
  • 아프리카
• 라틴아메리카
  • 라틴아메리카 : 고객 서비스용 AI 시장 성장 촉진요인
  • 라틴아메리카 : 거시경제에 대한 영향
  • 브라질
  • 멕시코
  • 아르헨티나
  • 기타

제11장 경쟁 구도

• 개요
• 주요 시장 진출기업의 전략/강점, 2020년-2024년
• 매출 분석, 2019년-2023년
• 시장 점유율 분석, 2023년
• 제품 유형별 제품 비교 분석
• 주요 벤더 기업 평가와 재무 지표
• 기업 평가 매트릭스 : 주요 시장 진출기업, 2023년
• 기업 평가 매트릭스 : 스타트업/중소기업, 2023년
• 경쟁 시나리오

제12장 기업 개요

• 서론
• 주요 시장 진출기업
  • MICROSOFT
  • IBM
  • GOOGLE
  • AWS
  • SALESFORCE
  • ATLASSIAN
  • SERVICENOW
  • ZENDESK
  • SAP
  • SPRINKLR
  • OPENAI
  • AISERA
  • UIPATH
  • HUBSPOT
  • NICE
  • INTERCOM
  • QUALTRICS
  • FRESHWORKS
  • LIVEPERSON
  • HELPSHIFT
  • YELLOW.AI
  • COGITO
  • SMARTACTION
  • TALKDESK
  • FIVE9
  • RINGCENTRAL
  • NEXTIVA
  • KORE.AI
  • DYNAMIC YIELD
  • JIOHAPTIK
  • ORACLE
  • AFINITI
• 스타트업/중소기업
  • KOMMUNICATE
  • HELP SCOUT
  • GORGIAS
  • ATERA
  • ADA
  • KUSTOMER
  • LEVITY
  • COGNIGY
  • ENGAGEWARE
  • NETOMI
  • LEVELAI
  • SYBILL AI
  • ONE AI
  • BRAINFISH
  • SENTISUM
  • BALTO
  • TOVIE AI
  • GURU
  • TIDIO
  • QUIQ
  • AIRCALL
  • ONEREACH.AI
  • CRESTA
  • DEEPDESK
  • FRONT
  • FULLVIEW
  • CRESCENDO AI
  • GRIDSPACE

제13장 인접 시장과 관련 시장

제14장 부록

LSH

영문 목차

영문목차

The AI for customer service market is projected to grow from USD 12.06 billion in 2024 to USD 47.82 billion by 2030, at a compound annual growth rate (CAGR) of 25.8% during the forecast period. AI-powered chatbots and virtual assistants are transforming customer service by providing efficient, personalized support. These technologies enable businesses to engage customers 24/7, offering instant responses to inquiries, which significantly reduces wait times and enhances satisfaction. Chatbots can handle multiple conversations simultaneously, allowing for scalability during peak periods without compromising service quality. Additionally, they utilize advanced algorithms to analyze customer data, enabling tailored recommendations and contextual interactions that foster deeper connections. This personalization not only improves user experience but also drives customer loyalty. As companies increasingly adopt these AI solutions, chatbots are becoming essential tools in modern customer engagement strategies, streamlining operations and enhancing overall service quality.

Scope of the Report
Years Considered for the Study	2019-2030
Base Year	2023
Forecast Period	2024-2030
Units Considered	(USD million/billion)
Segments	By Product, Technology, Customer Interaction Channel, and End user.
Regions covered	North America, Europe, Asia Pacific, Middle East & Africa, Latin America

"By end user, healthcare & life sciences segment will lead the market during the forecast period."

Healthcare and life sciences are increasingly leading the customer service market through innovative engagement strategies. Hybrid engagement models are emerging, combining personalized interactions with digital channels to enhance customer experiences. Companies are leveraging AI technologies for tailored communications, self-service analytics, and intelligent patient services, fostering a more responsive environment. The shift towards digital transformation has made telemedicine and virtual visits commonplace, allowing patients to interact conveniently with healthcare providers. Additionally, organizations are focusing on personalized insights and customized care journeys, ensuring that patient needs are met effectively. This evolution not only improves service delivery but also enhances overall patient satisfaction and loyalty in a rapidly changing landscape.

"By region, Asia Pacific to register the highest CAGR market during the forecast period." Asia Pacific is leading the AI-powered customer service market due to the region's rapid adoption of technology, large consumer bases, and increasing demand for enhanced customer experiences. The rise of e-commerce, mobile services, and digital transformation initiatives across various industries, particularly in retail, banking, and telecommunications, has driven the need for more efficient and personalized customer interactions. India and China are the top countries driving this trend. In India, the focus is on improving service delivery and reducing costs, while in China, AI is being integrated into smart customer service solutions, including voice assistants and chatbots, to serve millions of customers. These innovations enhance customer satisfaction, streamline operations, and meet the growing expectations of both consumers and businesses.

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 AI for customer service market.

• By Company: Tier I: 45%, Tier II: 35%, and Tier III: 20%
• By Designation: C-Level: 40%, Director Level: 35%, and Others: 25%
• By Region: North America: 30%, Europe: 20%, Asia Pacific: 35%, Middle East & Africa: 10%, and Latin America: 5%.

Microsoft (US), IBM (US), Google (US), AWS (US), Salesforce (US), Atlassian (Australia), ServiceNow (US), SAP (Germany), Zendesk (US); are some of the key players in the AI for customer service market.

The study includes an in-depth competitive analysis of these key players in the AI for customer service market, including their company profiles, recent developments, and key market strategies.

Research Coverage

This research report categorizes the AI for customer service market by product type (chatbots and virtual assistants, AI-driven ticketing systems, sentiment and feedback analysis tools, recommendation systems, visual and diagnostic tools, workflow automation, content management, AI agents), by deployment mode (cloud and on-premises), by customer service delivery mode (self-service, agent augmented backend operations automation), by functional area (pre-sales and post-sales), by technology (generative AI and other AI), by customer interaction channel (text and email, voice, video/visual, and omnichannel), by end user (media & entertainment, telecommunications, government & public sector, healthcare & life sciences, manufacturing, retail & ecommerce, technology & software, travel & hospitality, transportation & logistics). The scope of the report covers detailed information regarding the major factors, such as drivers, restraints, challenges, and opportunities, influencing the growth of the AI for customer service market. A detailed analysis of the key industry players has been done to provide insights into their business overview, solutions and services, key strategies, Contracts, partnerships, and agreements. new product & service launches, mergers and acquisitions, and recent developments associated with the AI for customer service market. Competitive analysis of upcoming startups in the AI for customer service market ecosystem is covered in this report.

Key Benefits of Buying the Report

The report will help the market leaders/new entrants in this market with information on the closest approximations of the revenue numbers for the overall AI for customer service market and the subsegments. This report will help stakeholders understand the competitive landscape and gain more insights to position their businesses better and to plan suitable go-to-market strategies. The report 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 (Improved customer engagement with omni-channel self-service options, and enhancing efficiency and satisfaction with intelligent routing), restraints (Mitigating deepfake threats in customer service), opportunities (augmenting customer service efficiency with Gen AI solutions, empowering proactive customer service with ai solutions), and challenges (threat of job displacements in customer service)
• Product Development/Innovation: Detailed insights on upcoming technologies, research & development activities, and new product & service launches in the AI for customer service market
• Market Development: Comprehensive information about lucrative markets - the report analyses the AI for customer service market across varied regions.
• Market Diversification: Exhaustive information about new products & services, untapped geographies, recent developments, and investments in the AI for customer service market
• Competitive Assessment: In-depth assessment of market shares, growth strategies and service offerings of leading players Microsoft (US), IBM (US), Google (US), Oracle (US), AWS (US), Salesforce (US), Atlassian (Australia), ServiceNow (US), SAP (Germany), Zendesk (US), Sprinklr (US), OpenAI (US), Aisera (US), UiPath (US), HubSpot (US), NICE (Israel), Intercom (US), Qualtrics (US) among others in AI for customer service market.

TABLE OF CONTENTS

1 INTRODUCTION

• 1.1 STUDY OBJECTIVES
• 1.2 MARKET DEFINITION
  • 1.2.1 INCLUSIONS & EXCLUSIONS
• 1.3 MARKET SCOPE
  • 1.3.1 MARKET SEGMENTATION & REGIONS COVERED
  • 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 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 RISK ASSESSMENT
• 2.7 RESEARCH LIMITATIONS

3 EXECUTIVE SUMMARY

4 PREMIUM INSIGHTS

• 4.1 ATTRACTIVE OPPORTUNITIES FOR PLAYERS IN AI FOR CUSTOMER SERVICE MARKET
• 4.2 AI FOR CUSTOMER SERVICE MARKET: TOP THREE CUSTOMER SERVICE DELIVERY MODES
• 4.3 NORTH AMERICA: AI FOR CUSTOMER SERVICE MARKET, BY DEPLOYMENT MODE AND FUNCTIONAL AREA
• 4.4 AI FOR CUSTOMER SERVICE MARKET: BY REGION

5 MARKET OVERVIEW AND INDUSTRY TRENDS

• 5.1 INTRODUCTION
• 5.2 MARKET DYNAMICS
  • 5.2.1 DRIVERS
    • 5.2.1.1 Improved customer engagement with omni-channel self-service options
    • 5.2.1.2 Maximizing agent efficiency through AI integration
    • 5.2.1.3 Enhancing efficiency and satisfaction with intelligent routing
  • 5.2.2 RESTRAINTS
    • 5.2.2.1 Mitigating deepfake threats in customer service
  • 5.2.3 OPPORTUNITIES
    • 5.2.3.1 Transforming customer service with generative AI innovations
    • 5.2.3.2 Empowering proactive customer service with AI solutions
  • 5.2.4 CHALLENGES
    • 5.2.4.1 Threats of job displacements in customer service
• 5.3 INDUSTRY TRENDS
  • 5.3.1 EVOLUTION OF AI FOR CUSTOMER SERVICE MARKET
  • 5.3.2 CASE STUDY ANALYSIS
    • 5.3.2.1 Smokeball enhanced efficiency and satisfaction with BrainFish AI help center
    • 5.3.2.2 Philip Morris enhances customer engagement with Tovie AI's Mark Chatbot
    • 5.3.2.3 Qapital achieves 24/7 service and automation with Ada's AI solution
    • 5.3.2.4 Gorgias helped Everyday Dose streamline customer support to manage high ticket volumes
    • 5.3.2.5 RingCentral unified Corteva's communication for global collaboration success
    • 5.3.2.6 Jardim Exotico enhances customer support with Tovie AI's chatbot solution
    • 5.3.2.7 Orange Spain streamlines operations with UiPath's RPA solution
  • 5.3.3 ECOSYSTEM ANALYSIS
    • 5.3.3.1 Chatbots and virtual assistant providers
      • 5.3.3.1.1 Rule-based chatbots
      • 5.3.3.1.2 Conversational bots
      • 5.3.3.1.3 Voice assistants
    • 5.3.3.2 AI-driven ticketing system providers
      • 5.3.3.2.1 Automated ticket routing
      • 5.3.3.2.2 Self-service portals
      • 5.3.3.2.3 Case resolution assistant
    • 5.3.3.3 Sentiment and feedback analysis tools
      • 5.3.3.3.1 Sentiment & emotion detection
      • 5.3.3.3.2 Customer feedback
      • 5.3.3.3.3 Social media monitoring
    • 5.3.3.4 Recommendation systems
      • 5.3.3.4.1 Dynamic FAQs
      • 5.3.3.4.2 Knowledge base platforms
    • 5.3.3.5 Visual and diagnostic tools
      • 5.3.3.5.1 Image recognition tools
      • 5.3.3.5.2 Voice-based assistance
    • 5.3.3.6 Workflow automation
      • 5.3.3.6.1 Robotic process automation
      • 5.3.3.6.2 Integrated CRM automation
    • 5.3.3.7 Content management
      • 5.3.3.7.1 Content distribution
      • 5.3.3.7.2 Content generation
      • 5.3.3.7.3 Content moderation
    • 5.3.3.8 AI agents
      • 5.3.3.8.1 Performance analytics
      • 5.3.3.8.2 Conversation intelligence
    • 5.3.3.9 Customer interaction channels
      • 5.3.3.9.1 Text and email
      • 5.3.3.9.2 Voice
      • 5.3.3.9.3 Video/Visual
      • 5.3.3.9.4 Omnichannel
    • 5.3.3.10 End users
  • 5.3.4 TECHNOLOGY ANALYSIS
    • 5.3.4.1 Key technologies
      • 5.3.4.1.1 NLP and deep learning
      • 5.3.4.1.2 Big data analytics
      • 5.3.4.1.3 Generative AI
        • 5.3.4.1.3.1 Rule-based models
        • 5.3.4.1.3.2 Statistical models
        • 5.3.4.1.3.3 Deep learning models
        • 5.3.4.1.3.4 Generative Adversarial Networks (GANs)
        • 5.3.4.1.3.5 Autoencoders
        • 5.3.4.1.3.6 Convolutional Neural Networks (CNNs)
        • 5.3.4.1.3.7 Transformer-based Large Language Models (LLMs)
      • 5.3.4.1.4 AI agent memory
        • 5.3.4.1.4.1 Short-term Memory (STM)
        • 5.3.4.1.4.2 Long-term Memory (LTM) Type 1
        • 5.3.4.1.4.3 Long-term Memory (LTM) Type 2
        • 5.3.4.1.4.4 Long-term Memory (LTM) Type 3
      • 5.3.4.1.5 Robotic Process Automation (RPA)
    • 5.3.4.2 Adjacent technologies
      • 5.3.4.2.1 Cloud computing
      • 5.3.4.2.2 Edge computing
      • 5.3.4.2.3 Internet of Things
      • 5.3.4.2.4 5G and advanced connectivity
    • 5.3.4.3 Complementary technologies
      • 5.3.4.3.1 Cybersecurity
      • 5.3.4.3.2 Augmented Reality (AR) and Virtual Reality (VR)
      • 5.3.4.3.3 Blockchain
  • 5.3.5 REGULATORY LANDSCAPE
    • 5.3.5.1 Regulatory bodies, government agencies, and other organizations
    • 5.3.5.2 Regulatory Framework
      • 5.3.5.2.1 North America
        • 5.3.5.2.1.1 US
        • 5.3.5.2.1.2 Canada
      • 5.3.5.2.2 Europe
        • 5.3.5.2.2.1 Germany
        • 5.3.5.2.2.2 UK
        • 5.3.5.2.2.3 France
      • 5.3.5.2.3 Asia Pacific
        • 5.3.5.2.3.1 Australia
        • 5.3.5.2.3.2 India
        • 5.3.5.2.3.3 China
      • 5.3.5.2.4 Middle East & Africa
        • 5.3.5.2.4.1 UAE
        • 5.3.5.2.4.2 Kenya
        • 5.3.5.2.4.3 Africa
      • 5.3.5.2.5 Latin America
        • 5.3.5.2.5.1 Brazil
        • 5.3.5.2.5.2 Mexico
        • 5.3.5.2.5.3 Argentina
  • 5.3.6 SUPPLY CHAIN ANALYSIS
  • 5.3.7 PORTER'S FIVE FORCES ANALYSIS
    • 5.3.7.1 Threat of new entrants
    • 5.3.7.2 Threat of substitutes
    • 5.3.7.3 Bargaining power of suppliers
    • 5.3.7.4 Bargaining power of buyers
    • 5.3.7.5 Intensity of competitive rivalry
  • 5.3.8 KEY CONFERENCES AND EVENTS (2025-2026)
  • 5.3.9 KEY STAKEHOLDERS AND BUYING CRITERIA
    • 5.3.9.1 Key Stakeholders in Buying Process
    • 5.3.9.2 Buying criteria
  • 5.3.10 PRICING ANALYSIS
    • 5.3.10.1 Indicative pricing analysis, by software type
    • 5.3.10.2 Indicative pricing analysis, by product type
  • 5.3.11 PATENT ANALYSIS
    • 5.3.11.1 Methodology
    • 5.3.11.2 Patents filed, by document type
    • 5.3.11.3 INNOVATIONS AND PATENT APPLICATIONS
  • 5.3.12 TRENDS/DISRUPTIONS IMPACTING CUSTOMER BUSINESS
  • 5.3.13 INVESTMENT LANDSCAPE AND FUNDING SCENARIO
  • 5.3.14 IMPACT OF GENERATIVE AI ON AI FOR CUSTOMER SERVICE MARKET
    • 5.3.14.1 Top use cases & market potential
    • 5.3.14.2 Key use cases
      • 5.3.14.2.1 Enhanced efficiency and productivity
      • 5.3.14.2.2 24/7 availability
      • 5.3.14.2.3 Personalized customer interactions
      • 5.3.14.2.4 Cost reduction
      • 5.3.14.2.5 Proactive customer engagement
      • 5.3.14.2.6 Scalability

6 AI FOR CUSTOMER SERVICE MARKET, BY END USER

• 6.1 INTRODUCTION
  • 6.1.1 END USER: AI FOR CUSTOMER SERVICE MARKET DRIVERS
• 6.2 BFSI
  • 6.2.1 ENHANCING BFSI CUSTOMER SERVICE WITH AI-DRIVEN EFFICIENCY AND SECURITY
• 6.3 MEDIA & ENTERTAINMENT
  • 6.3.1 PERSONALIZING AUDIENCE ENGAGEMENT WITH AI
• 6.4 TELECOMMUNICATIONS
  • 6.4.1 AUTOMATING CUSTOMER SUPPORT FOR FASTER RESOLUTIONS
• 6.5 GOVERNMENT & PUBLIC SECTOR
  • 6.5.1 ENHANCING CITIZEN SERVICES WITH AI-DRIVEN ASSISTANCE
• 6.6 HEALTHCARE & LIFE SCIENCES
  • 6.6.1 TRANSFORMING PATIENT INTERACTIONS WITH AI-POWERED SUPPORT
• 6.7 MANUFACTURING
  • 6.7.1 STREAMLINING TECHNICAL ASSISTANCE AND SUPPLY CHAIN INQUIRIES
• 6.8 RETAIL & E-COMMERCE
  • 6.8.1 ELEVATING SHOPPING EXPERIENCES WITH AI-DRIVEN CUSTOMER SERVICE
• 6.9 TECHNOLOGY & SOFTWARE
  • 6.9.1 OPTIMIZING USER SUPPORT WITH INTELLIGENT AI SOLUTIONS
• 6.10 TRAVEL & HOSPITALITY
  • 6.10.1 REVOLUTIONIZING GUEST SERVICES WITH AI-POWERED INTERACTIONS
• 6.11 TRANSPORTATION & LOGISTICS
  • 6.11.1 ENHANCING SHIPMENT TRACKING AND LOGISTICS SUPPORT WITH AI
• 6.12 OTHER END USERS

7 AI FOR CUSTOMER SERVICE MARKET, BY PRODUCT

• 7.1 INTRODUCTION
  • 7.1.1 PRODUCT: AI FOR CUSTOMER SERVICE MARKET DRIVERS
• 7.2 TYPE
  • 7.2.1 CHATBOTS AND VIRTUAL ASSISTANTS
    • 7.2.1.1 Rule-based chatbots
    • 7.2.1.2 AI-powered conversational bots
    • 7.2.1.3 Voice assistants & speech analytics
    • 7.2.1.4 Other chatbots & virtual assistants
  • 7.2.2 AI-DRIVEN TICKETING SYSTEMS
    • 7.2.2.1 Automated ticket routing
    • 7.2.2.2 Self-service portals
    • 7.2.2.3 Case resolution assistance
    • 7.2.2.4 Other AI-driven ticketing systems
  • 7.2.3 SENTIMENT AND FEEDBACK ANALYSIS TOOLS
    • 7.2.3.1 Sentiment & emotion detection
    • 7.2.3.2 Customer feedback
    • 7.2.3.3 Social media monitoring
    • 7.2.3.4 Other sentiment and feedback analysis tools
  • 7.2.4 RECOMMENDATION SYSTEMS
    • 7.2.4.1 Product recommendation systems
    • 7.2.4.2 Dynamic FAQs
    • 7.2.4.3 Knowledge base platforms
    • 7.2.4.4 Other recommendation systems
  • 7.2.5 VISUAL AND DIAGNOSTIC TOOLS
    • 7.2.5.1 Image recognition tools
    • 7.2.5.2 Video-based assistance
    • 7.2.5.3 Other visual and diagnostic tools
  • 7.2.6 WORKFLOW AUTOMATION
    • 7.2.6.1 Robotic Process Automation (RPA)
    • 7.2.6.2 Integrated CRM automation
    • 7.2.6.3 Other workflow automation tools
  • 7.2.7 CONTENT MANAGEMENT
    • 7.2.7.1 Content distribution
    • 7.2.7.2 Content generation
    • 7.2.7.3 Content moderation and filtration
    • 7.2.7.4 Other content management
  • 7.2.8 AI AGENTS
    • 7.2.8.1 Performance analytics
    • 7.2.8.2 Conversation intelligence
    • 7.2.8.3 Behavior analytics & engagement
    • 7.2.8.4 Other AI agents
  • 7.2.9 OTHER PRODUCT TYPES
• 7.3 BY DEPLOYMENT MODE
  • 7.3.1 CLOUD
    • 7.3.1.1 Flexibility, cost-effectiveness, and rapid deployment to drive market
  • 7.3.2 ON-PREMISES
    • 7.3.2.1 Secure and customized on-premises AI to drive market
• 7.4 BY CUSTOMER SERVICE DELIVERY MODE
  • 7.4.1 SELF-SERVICE
    • 7.4.1.1 Reduced wait times and operational costs to drive market
  • 7.4.2 AGENT AUGMENTED
    • 7.4.2.1 Elevating customer service with AI-powered augmented agents
  • 7.4.3 BACKEND OPERATIONS AUTOMATION
    • 7.4.3.1 Streamlined and optimized service operations to drive market
• 7.5 BY FUNCTIONAL AREA
  • 7.5.1 PRE-SALES
    • 7.5.1.1 Tailored solutions for improved customer experiences to drive market
  • 7.5.2 POST-SALES
    • 7.5.2.1 Increased customer satisfaction and support with AI solutions to drive market

8 AI FOR CUSTOMER SERVICE MARKET, BY TECHNOLOGY

• 8.1 INTRODUCTION
  • 8.1.1 GENERATIVE AI
    • 8.1.1.1 Empower dynamic and context-aware interactions with generative AI
  • 8.1.2 OTHER AI
    • 8.1.2.1 Enhancing customer service: Power of AI technologies

9 AI FOR CUSTOMER SERVICE MARKET, BY CUSTOMER INTERACTION CHANNEL

• 9.1 INTRODUCTION
• 9.2 TEXT AND EMAIL
  • 9.2.1 MAXIMIZED ENGAGEMENT WITH ASYNCHRONOUS COMMUNICATION TO DRIVE MARKET
• 9.3 VOICE
  • 9.3.1 INCREASED INTEGRATION OF VOICE WITH DIGITAL TOOLS TO DRIVE MARKET
• 9.4 VIDEO/VISUAL
  • 9.4.1 ENHANCED CUSTOMER ENGAGEMENT THROUGH VIDEO INTERACTIONS TO DRIVE MARKET
• 9.5 OMNICHANNEL
  • 9.5.1 INTEGRATION OF DATA ACROSS CHANNELS FOR ENHANCED PERSONALIZATION TO DRIVE MARKET

10 AI FOR CUSTOMER SERVICE MARKET, BY REGION

• 10.1 INTRODUCTION
• 10.2 NORTH AMERICA
  • 10.2.1 NORTH AMERICA: AI FOR CUSTOMER SERVICE MARKET DRIVERS
  • 10.2.2 NORTH AMERICA: MACROECONOMIC IMPACT
  • 10.2.3 US
    • 10.2.3.1 Rise in need to enhance customer experience using AI-powered chatbots and virtual assistants to drive market
  • 10.2.4 CANADA
    • 10.2.4.1 Innovations in ethical AI to enhance AI-enabled customer support and drive market
• 10.3 EUROPE
  • 10.3.1 EUROPE: AI FOR CUSTOMER SERVICE MARKET DRIVERS
  • 10.3.2 EUROPE: MACROECONOMIC IMPACT
  • 10.3.3 UK
    • 10.3.3.1 Enhancing customer engagement with ethical AI to drive market
  • 10.3.4 GERMANY
    • 10.3.4.1 Advancing AI-powered customer service to drive market
  • 10.3.5 FRANCE
    • 10.3.5.1 Advancing ethical AI solutions for customer service to drive market
  • 10.3.6 ITALY
    • 10.3.6.1 Empowering SMEs and strengthening data privacy to drive market
  • 10.3.7 SPAIN
    • 10.3.7.1 Oracle's USD 1 billion cloud investment to drive AI growth
  • 10.3.8 REST OF EUROPE
• 10.4 ASIA PACIFIC
  • 10.4.1 ASIA PACIFIC: AI FOR CUSTOMER SERVICE MARKET DRIVERS
  • 10.4.2 ASIA PACIFIC: MACROECONOMIC IMPACT
  • 10.4.3 CHINA
    • 10.4.3.1 Implementation of regulatory approval for generative AI applications to drive market
  • 10.4.4 JAPAN
    • 10.4.4.1 Regulatory efforts and partnerships to drive AI for customer service
  • 10.4.5 INDIA
    • 10.4.5.1 Adoption of AI-driven solutions for personalized customer service to drive market
  • 10.4.6 SOUTH KOREA
    • 10.4.6.1 Increased AI integration for personalized customer support to drive market
  • 10.4.7 AUSTRALIA & NEW ZEALAND
    • 10.4.7.1 AI revolution in Australia & New Zealand to drive market
  • 10.4.8 ASEAN COUNTRIES
    • 10.4.8.1 Governments strengthening digital infrastructure for AI innovation to drive market
  • 10.4.9 REST OF ASIA PACIFIC
• 10.5 MIDDLE EAST & AFRICA
  • 10.5.1 MIDDLE EAST & AFRICA: AI FOR CUSTOMER SERVICE MARKET DRIVERS
  • 10.5.2 MIDDLE EAST & AFRICA: MACROECONOMIC IMPACT
  • 10.5.3 MIDDLE EAST
    • 10.5.3.1 KSA
      • 10.5.3.1.1 Saudi Arabia's Vision 2030 for enhancing AI-driven customer engagement to drive market
    • 10.5.3.2 UAE
      • 10.5.3.2.1 UAE's digital transformation fuels AI-driven customer service innovation
    • 10.5.3.3 Bahrain
      • 10.5.3.3.1 Bahrain's regulatory sandbox drives AI innovation in customer service
    • 10.5.3.4 Kuwait
      • 10.5.3.4.1 SAP empowering Kuwaiti organizations by embedding AI into business applications for better operational efficiency
    • 10.5.3.5 Rest of Middle East
  • 10.5.4 AFRICA
• 10.6 LATIN AMERICA
  • 10.6.1 LATIN AMERICA: AI FOR CUSTOMER SERVICE MARKET DRIVERS
  • 10.6.2 LATIN AMERICA: MACROECONOMIC IMPACT
  • 10.6.3 BRAZIL
    • 10.6.3.1 Increased customer service innovation with AI-powered chatbots to drive market
  • 10.6.4 MEXICO
    • 10.6.4.1 Mexico leverages AI for customer service through key partnerships and innovations
  • 10.6.5 ARGENTINA
    • 10.6.5.1 Strategic partnerships and investment incentives to drive AI growth
  • 10.6.6 REST OF LATIN AMERICA

11 COMPETITIVE LANDSCAPE

• 11.1 OVERVIEW
• 11.2 KEY PLAYER STRATEGIES/RIGHT TO WIN, 2020-2024
• 11.3 REVENUE ANALYSIS, 2019-2023
• 11.4 MARKET SHARE ANALYSIS, 2023
  • 11.4.1 MARKET SHARE ANALYSIS OF KEY PLAYERS
  • 11.4.2 MARKET RANKING ANALYSIS
• 11.5 PRODUCT COMPARATIVE ANALYSIS, BY PRODUCT TYPE
  • 11.5.1 PRODUCT COMPARATIVE ANALYSIS, BY CHATBOTS AND VIRTUAL ASSISTANTS
    • 11.5.1.1 Google Dialogflow
    • 11.5.1.2 IBM Watson Assistant
    • 11.5.1.3 XO Automation (Kore.ai)
  • 11.5.2 PRODUCT COMPARATIVE ANALYSIS, BY AI-DRIVEN TICKETING SYSTEMS
    • 11.5.2.1 Freedy AI (Freshdesk)
    • 11.5.2.2 AI bot (Zendesk)
    • 11.5.2.3 Zia AI (Zoho)
  • 11.5.3 PRODUCT COMPARATIVE ANALYSIS, BY RECOMMENDATION SYSTEMS
    • 11.5.3.1 Amazon Personalize (AWS)
    • 11.5.3.2 Product Recommendation Engines (Salesforce)
    • 11.5.3.3 Dynamic Yield
• 11.6 COMPANY VALUATION AND FINANCIAL METRICS OF KEY VENDORS
• 11.7 COMPANY EVALUATION MATRIX: KEY PLAYERS, 2023
  • 11.7.1 STARS
  • 11.7.2 EMERGING LEADERS
  • 11.7.3 PERVASIVE PLAYERS
  • 11.7.4 PARTICIPANTS
  • 11.7.5 COMPANY FOOTPRINT: KEY PLAYERS
    • 11.7.5.1 Company footprint
    • 11.7.5.2 Region footprint
    • 11.7.5.3 Product type footprint
    • 11.7.5.4 Customer interaction channel footprint
    • 11.7.5.5 End user footprint
• 11.8 COMPANY EVALUATION MATRIX: STARTUPS/SMES, 2023
  • 11.8.1 PROGRESSIVE COMPANIES
  • 11.8.2 RESPONSIVE COMPANIES
  • 11.8.3 DYNAMIC COMPANIES
  • 11.8.4 STARTING BLOCKS
  • 11.8.5 COMPETITIVE BENCHMARKING: STARTUPS/SMES, 2023
    • 11.8.5.1 Detailed list of key startups/SMEs
    • 11.8.5.2 Competitive benchmarking of key startups/SMEs
• 11.9 COMPETITIVE SCENARIO
  • 11.9.1 PRODUCT LAUNCHES & ENHANCEMENTS
  • 11.9.2 DEALS

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
      • 12.2.1.3.1 Product launches and enhancements
      • 12.2.1.3.2 Deals
    • 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 IBM
    • 12.2.2.1 Business overview
    • 12.2.2.2 Products/Solutions/Services offered
    • 12.2.2.3 Recent developments
      • 12.2.2.3.1 Product launches and enhancements
      • 12.2.2.3.2 Deals
    • 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 GOOGLE
    • 12.2.3.1 Business overview
    • 12.2.3.2 Products/Solutions/Services offered
    • 12.2.3.3 Recent developments
      • 12.2.3.3.1 Product launches and enhancements
      • 12.2.3.3.2 Deals
    • 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
      • 12.2.4.3.1 Product launches and enhancements
      • 12.2.4.3.2 Deals
    • 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 SALESFORCE
    • 12.2.5.1 Business overview
    • 12.2.5.2 Products/Solutions/Services offered
    • 12.2.5.3 Recent developments
      • 12.2.5.3.1 Product launches and enhancements
    • 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 ATLASSIAN
    • 12.2.6.1 Business overview
    • 12.2.6.2 Products/Solutions/Services offered
    • 12.2.6.3 Recent developments
      • 12.2.6.3.1 Product launches and enhancements
  • 12.2.7 SERVICENOW
    • 12.2.7.1 Business overview
    • 12.2.7.2 Products/Solutions/Services offered
    • 12.2.7.3 Recent developments
      • 12.2.7.3.1 Product launches and enhancements
  • 12.2.8 ZENDESK
    • 12.2.8.1 Business overview
    • 12.2.8.2 Products/Solutions/Services offered
    • 12.2.8.3 Recent developments
      • 12.2.8.3.1 Product launches and enhancements
      • 12.2.8.3.2 Deals
  • 12.2.9 SAP
    • 12.2.9.1 Business overview
    • 12.2.9.2 Products/Solutions/Services offered
    • 12.2.9.3 Recent developments
      • 12.2.9.3.1 Deals
  • 12.2.10 SPRINKLR
    • 12.2.10.1 Business overview
    • 12.2.10.2 Products/Solutions/Services offered
    • 12.2.10.3 Recent developments
      • 12.2.10.3.1 Deals
  • 12.2.11 OPENAI
    • 12.2.11.1 Business overview
    • 12.2.11.2 Products/Solutions/Services offered
    • 12.2.11.3 Recent developments
      • 12.2.11.3.1 Product Launches and Enhancements
      • 12.2.11.3.2 Deals
  • 12.2.12 AISERA
  • 12.2.13 UIPATH
  • 12.2.14 HUBSPOT
  • 12.2.15 NICE
  • 12.2.16 INTERCOM
  • 12.2.17 QUALTRICS
  • 12.2.18 FRESHWORKS
  • 12.2.19 LIVEPERSON
  • 12.2.20 HELPSHIFT
  • 12.2.21 YELLOW.AI
  • 12.2.22 COGITO
  • 12.2.23 SMARTACTION
  • 12.2.24 TALKDESK
  • 12.2.25 FIVE9
  • 12.2.26 RINGCENTRAL
  • 12.2.27 NEXTIVA
  • 12.2.28 KORE.AI
  • 12.2.29 DYNAMIC YIELD
  • 12.2.30 JIOHAPTIK
  • 12.2.31 ORACLE
  • 12.2.32 AFINITI
• 12.3 STARTUPS/SMES
  • 12.3.1 KOMMUNICATE
  • 12.3.2 HELP SCOUT
  • 12.3.3 GORGIAS
  • 12.3.4 ATERA
  • 12.3.5 ADA
  • 12.3.6 KUSTOMER
  • 12.3.7 LEVITY
  • 12.3.8 COGNIGY
  • 12.3.9 ENGAGEWARE
  • 12.3.10 NETOMI
  • 12.3.11 LEVELAI
  • 12.3.12 SYBILL AI
  • 12.3.13 ONE AI
  • 12.3.14 BRAINFISH
  • 12.3.15 SENTISUM
  • 12.3.16 BALTO
  • 12.3.17 TOVIE AI
  • 12.3.18 GURU
  • 12.3.19 TIDIO
  • 12.3.20 QUIQ
  • 12.3.21 AIRCALL
  • 12.3.22 ONEREACH.AI
  • 12.3.23 CRESTA
  • 12.3.24 DEEPDESK
  • 12.3.25 FRONT
  • 12.3.26 FULLVIEW
  • 12.3.27 CRESCENDO AI
  • 12.3.28 GRIDSPACE

13 ADJACENT AND RELATED MARKETS

• 13.1 INTRODUCTION
• 13.2 CONVERSATIONAL AI MARKET - GLOBAL FORECAST TO 2030
  • 13.2.1 MARKET DEFINITION
  • 13.2.2 MARKET OVERVIEW
    • 13.2.2.1 Conversational AI market, by offering
    • 13.2.2.2 Conversational AI market, by service
    • 13.2.2.3 Conversational AI market, by business function
    • 13.2.2.4 Conversational AI market, by conversational agent type
    • 13.2.2.5 Conversational AI market, by integration mode
    • 13.2.2.6 Conversational AI market, by vertical
    • 13.2.2.7 Conversational AI market, by region
• 13.3 AI AGENTS MARKET
  • 13.3.1 MARKET DEFINITION
  • 13.3.2 MARKET OVERVIEW
    • 13.3.2.1 AI agents market, by agent system
    • 13.3.2.2 AI agents market, by product type
    • 13.3.2.3 AI agents market, by agent role
    • 13.3.2.4 AI agents market, by end user
    • 13.3.2.5 AI agents 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

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