Summary

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.
“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.

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Table of Contents

1 INTRODUCTION 34
1.1 STUDY OBJECTIVES 34
1.2 MARKET DEFINITION 34
1.2.1 INCLUSIONS & EXCLUSIONS 35
1.3 MARKET SCOPE 35
1.3.1 MARKET SEGMENTATION & REGIONS COVERED 36
1.3.2 YEARS CONSIDERED 37
1.4 CURRENCY CONSIDERED 37
1.5 STAKEHOLDERS 38
2 RESEARCH METHODOLOGY 39
2.1 RESEARCH DATA 39
2.1.1 SECONDARY DATA 40
2.1.2 PRIMARY DATA 40
2.1.2.1 Breakup of primary profiles 41
2.1.2.2 Key industry insights 41
2.2 DATA TRIANGULATION 42
2.3 MARKET SIZE ESTIMATION 43
2.3.1 TOP-DOWN APPROACH 43
2.3.2 BOTTOM-UP APPROACH 44
2.4 MARKET FORECAST 47
2.5 RESEARCH ASSUMPTIONS 48
2.6 RISK ASSESSMENT 49
2.7 RESEARCH LIMITATIONS 49
3 EXECUTIVE SUMMARY 50
4 PREMIUM INSIGHTS 55
4.1 ATTRACTIVE OPPORTUNITIES FOR PLAYERS IN AI FOR CUSTOMER SERVICE MARKET 55
4.2 AI FOR CUSTOMER SERVICE MARKET: TOP THREE CUSTOMER SERVICE DELIVERY MODES 56
4.3 NORTH AMERICA: AI FOR CUSTOMER SERVICE MARKET, BY DEPLOYMENT MODE
AND FUNCTIONAL AREA 56
4.4 AI FOR CUSTOMER SERVICE MARKET: BY REGION 57
 
5 MARKET OVERVIEW AND INDUSTRY TRENDS 58
5.1 INTRODUCTION 58
5.2 MARKET DYNAMICS 58
5.2.1 DRIVERS 59
5.2.1.1 Improved customer engagement with omni-channel
self-service options 59
5.2.1.2 Maximizing agent efficiency through AI integration 60
5.2.1.3 Enhancing efficiency and satisfaction with intelligent routing 60
5.2.2 RESTRAINTS 60
5.2.2.1 Mitigating deepfake threats in customer service 60
5.2.3 OPPORTUNITIES 61
5.2.3.1 Transforming customer service with generative AI innovations 61
5.2.3.2 Empowering proactive customer service with AI solutions 61
5.2.4 CHALLENGES 61
5.2.4.1 Threats of job displacements in customer service 61
5.3 INDUSTRY TRENDS 62
5.3.1 EVOLUTION OF AI FOR CUSTOMER SERVICE MARKET 62
5.3.2 CASE STUDY ANALYSIS 63
5.3.2.1 Smokeball enhanced efficiency and satisfaction with
BrainFish AI help center 63
5.3.2.2 Philip Morris enhances customer engagement with Tovie
AI’s Mark Chatbot 64
5.3.2.3 Qapital achieves 24/7 service and automation with Ada's AI solution 65
5.3.2.4 Gorgias helped Everyday Dose streamline customer support to manage high ticket volumes 65
5.3.2.5 RingCentral unified Corteva's communication for global collaboration success 66
5.3.2.6 Jardim Exótico enhances customer support with Tovie AI's chatbot solution 67
5.3.2.7 Orange Spain streamlines operations with UiPath's RPA solution 68
5.3.3 ECOSYSTEM ANALYSIS 68
5.3.3.1 Chatbots and virtual assistant providers 71
5.3.3.1.1 Rule-based chatbots 71
5.3.3.1.2 Conversational bots 72
5.3.3.1.3 Voice assistants 72
5.3.3.2 AI-driven ticketing system providers 72
5.3.3.2.1 Automated ticket routing 72
5.3.3.2.2 Self-service portals 72
5.3.3.2.3 Case resolution assistant 73
5.3.3.3 Sentiment and feedback analysis tools 73
5.3.3.3.1 Sentiment & emotion detection 73
5.3.3.3.2 Customer feedback 73
5.3.3.3.3 Social media monitoring 73
5.3.3.4 Recommendation systems 74
5.3.3.4.1 Dynamic FAQs 74
5.3.3.4.2 Knowledge base platforms 74
5.3.3.5 Visual and diagnostic tools 74
5.3.3.5.1 Image recognition tools 75
5.3.3.5.2 Voice-based assistance 75
5.3.3.6 Workflow automation 75
5.3.3.6.1 Robotic process automation 75
5.3.3.6.2 Integrated CRM automation 75
5.3.3.7 Content management 76
5.3.3.7.1 Content distribution 76
5.3.3.7.2 Content generation 76
5.3.3.7.3 Content moderation 76
5.3.3.8 AI agents 77
5.3.3.8.1 Performance analytics 77
5.3.3.8.2 Conversation intelligence 77
5.3.3.9 Customer interaction channels 77
5.3.3.9.1 Text and email 78
5.3.3.9.2 Voice 78
5.3.3.9.3 Video/Visual 78
5.3.3.9.4 Omnichannel 78
5.3.3.10 End users 78
5.3.4 TECHNOLOGY ANALYSIS 79
5.3.4.1 Key technologies 79
5.3.4.1.1 NLP and deep learning 79
5.3.4.1.2 Big data analytics 79
5.3.4.1.3 Generative AI 79
5.3.4.1.3.1 Rule-based models 80
5.3.4.1.3.2 Statistical models 80
5.3.4.1.3.3 Deep learning models 80
5.3.4.1.3.4 Generative Adversarial Networks (GANs) 80
5.3.4.1.3.5 Autoencoders 81
5.3.4.1.3.6 Convolutional Neural Networks (CNNs) 81
5.3.4.1.3.7 Transformer-based Large Language Models (LLMs) 81
5.3.4.1.4 AI agent memory 81
5.3.4.1.4.1 Short-term Memory (STM) 82
5.3.4.1.4.2 Long-term Memory (LTM) Type 1 82
5.3.4.1.4.3 Long-term Memory (LTM) Type 2 82
5.3.4.1.4.4 Long-term Memory (LTM) Type 3 82
5.3.4.1.5 Robotic Process Automation (RPA) 83
5.3.4.2 Adjacent technologies 83
5.3.4.2.1 Cloud computing 83
5.3.4.2.2 Edge computing 83
5.3.4.2.3 Internet of Things 83
5.3.4.2.4 5G and advanced connectivity 83
5.3.4.3 Complementary technologies 84
5.3.4.3.1 Cybersecurity 84
5.3.4.3.2 Augmented Reality (AR) and Virtual Reality (VR) 84
5.3.4.3.3 Blockchain 84
5.3.5 REGULATORY LANDSCAPE 84
5.3.5.1 Regulatory bodies, government agencies, and other organizations 85
5.3.5.2 Regulatory Framework 89
5.3.5.2.1 North America 89
5.3.5.2.1.1 US 89
5.3.5.2.1.2 Canada 90
5.3.5.2.2 Europe 90
5.3.5.2.2.1 Germany 90
5.3.5.2.2.2 UK 90
5.3.5.2.2.3 France 90
5.3.5.2.3 Asia Pacific 91
5.3.5.2.3.1 Australia 91
5.3.5.2.3.2 India 91
5.3.5.2.3.3 China 91
5.3.5.2.4 Middle East & Africa 91
5.3.5.2.4.1 UAE 91
5.3.5.2.4.2 Kenya 91
5.3.5.2.4.3 Africa 92
5.3.5.2.5 Latin America 92
5.3.5.2.5.1 Brazil 92
5.3.5.2.5.2 Mexico 92
5.3.5.2.5.3 Argentina 92
5.3.6 SUPPLY CHAIN ANALYSIS 93
5.3.7 PORTER’S FIVE FORCES ANALYSIS 94
5.3.7.1 Threat of new entrants 95
5.3.7.2 Threat of substitutes 96
5.3.7.3 Bargaining power of suppliers 96
5.3.7.4 Bargaining power of buyers 96
5.3.7.5 Intensity of competitive rivalry 96
5.3.8 KEY CONFERENCES AND EVENTS (2025–2026) 96
5.3.9 KEY STAKEHOLDERS AND BUYING CRITERIA 97
5.3.9.1 Key Stakeholders in Buying Process 97
5.3.9.2 Buying criteria 98
5.3.10 PRICING ANALYSIS 98
5.3.10.1 Indicative pricing analysis, by software type 99
5.3.10.2 Indicative pricing analysis, by product type 100
 
5.3.11 PATENT ANALYSIS 102
5.3.11.1 Methodology 102
5.3.11.2 Patents filed, by document type 102
5.3.11.3 INNOVATIONS AND PATENT APPLICATIONS 102
5.3.12 TRENDS/DISRUPTIONS IMPACTING CUSTOMER BUSINESS 106
5.3.13 INVESTMENT LANDSCAPE AND FUNDING SCENARIO 108
5.3.14 IMPACT OF GENERATIVE AI ON AI FOR CUSTOMER SERVICE MARKET 108
5.3.14.1 Top use cases & market potential 108
5.3.14.2 Key use cases 109
5.3.14.2.1 Enhanced efficiency and productivity 110
5.3.14.2.2 24/7 availability 110
5.3.14.2.3 Personalized customer interactions 110
5.3.14.2.4 Cost reduction 110
5.3.14.2.5 Proactive customer engagement 110
5.3.14.2.6 Scalability 110
6 AI FOR CUSTOMER SERVICE MARKET, BY END USER 111
6.1 INTRODUCTION 112
6.1.1 END USER: AI FOR CUSTOMER SERVICE MARKET DRIVERS 114
6.2 BFSI 114
6.2.1 ENHANCING BFSI CUSTOMER SERVICE WITH AI-DRIVEN EFFICIENCY AND SECURITY 114
6.3 MEDIA & ENTERTAINMENT 115
6.3.1 PERSONALIZING AUDIENCE ENGAGEMENT WITH AI 115
6.4 TELECOMMUNICATIONS 116
6.4.1 AUTOMATING CUSTOMER SUPPORT FOR FASTER RESOLUTIONS 116
6.5 GOVERNMENT & PUBLIC SECTOR 117
6.5.1 ENHANCING CITIZEN SERVICES WITH AI-DRIVEN ASSISTANCE 117
6.6 HEALTHCARE & LIFE SCIENCES 118
6.6.1 TRANSFORMING PATIENT INTERACTIONS WITH AI-POWERED SUPPORT 118
6.7 MANUFACTURING 119
6.7.1 STREAMLINING TECHNICAL ASSISTANCE AND SUPPLY CHAIN INQUIRIES 119
6.8 RETAIL & E-COMMERCE 120
6.8.1 ELEVATING SHOPPING EXPERIENCES WITH AI-DRIVEN CUSTOMER SERVICE 120
6.9 TECHNOLOGY & SOFTWARE 121
6.9.1 OPTIMIZING USER SUPPORT WITH INTELLIGENT AI SOLUTIONS 121
6.10 TRAVEL & HOSPITALITY 122
6.10.1 REVOLUTIONIZING GUEST SERVICES WITH AI-POWERED INTERACTIONS 122
6.11 TRANSPORTATION & LOGISTICS 123
6.11.1 ENHANCING SHIPMENT TRACKING AND LOGISTICS SUPPORT WITH AI 123
6.12 OTHER END USERS 124
 
7 AI FOR CUSTOMER SERVICE MARKET, BY PRODUCT 126
7.1 INTRODUCTION 127
7.1.1 PRODUCT: AI FOR CUSTOMER SERVICE MARKET DRIVERS 127
7.2 TYPE 127
7.2.1 CHATBOTS AND VIRTUAL ASSISTANTS 129
7.2.1.1 Rule-based chatbots 130
7.2.1.2 AI-powered conversational bots 130
7.2.1.3 Voice assistants & speech analytics 130
7.2.1.4 Other chatbots & virtual assistants 131
7.2.2 AI-DRIVEN TICKETING SYSTEMS 131
7.2.2.1 Automated ticket routing 132
7.2.2.2 Self-service portals 132
7.2.2.3 Case resolution assistance 132
7.2.2.4 Other AI-driven ticketing systems 132
7.2.3 SENTIMENT AND FEEDBACK ANALYSIS TOOLS 132
7.2.3.1 Sentiment & emotion detection 133
7.2.3.2 Customer feedback 133
7.2.3.3 Social media monitoring 134
7.2.3.4 Other sentiment and feedback analysis tools 134
7.2.4 RECOMMENDATION SYSTEMS 134
7.2.4.1 Product recommendation systems 135
7.2.4.2 Dynamic FAQs 135
7.2.4.3 Knowledge base platforms 135
7.2.4.4 Other recommendation systems 136
7.2.5 VISUAL AND DIAGNOSTIC TOOLS 136
7.2.5.1 Image recognition tools 137
7.2.5.2 Video-based assistance 137
7.2.5.3 Other visual and diagnostic tools 137
7.2.6 WORKFLOW AUTOMATION 137
7.2.6.1 Robotic Process Automation (RPA) 138
7.2.6.2 Integrated CRM automation 138
7.2.6.3 Other workflow automation tools 138
7.2.7 CONTENT MANAGEMENT 139
7.2.7.1 Content distribution 139
7.2.7.2 Content generation 140
7.2.7.3 Content moderation and filtration 140
7.2.7.4 Other content management 140
7.2.8 AI AGENTS 140
7.2.8.1 Performance analytics 141
7.2.8.2 Conversation intelligence 141
7.2.8.3 Behavior analytics & engagement 142
7.2.8.4 Other AI agents 142
7.2.9 OTHER PRODUCT TYPES 142
7.3 BY DEPLOYMENT MODE 143
7.3.1 CLOUD 145
7.3.1.1 Flexibility, cost-effectiveness, and rapid deployment to drive market 145
7.3.2 ON-PREMISES 146
7.3.2.1 Secure and customized on-premises AI to drive market 146
7.4 BY CUSTOMER SERVICE DELIVERY MODE 147
7.4.1 SELF-SERVICE 148
7.4.1.1 Reduced wait times and operational costs to drive market 148
7.4.2 AGENT AUGMENTED 149
7.4.2.1 Elevating customer service with AI-powered augmented agents 149
7.4.3 BACKEND OPERATIONS AUTOMATION 150
7.4.3.1 Streamlined and optimized service operations to drive market 150
7.5 BY FUNCTIONAL AREA 151
7.5.1 PRE-SALES 152
7.5.1.1 Tailored solutions for improved customer experiences to drive market 152
7.5.2 POST-SALES 153
7.5.2.1 Increased customer satisfaction and support with AI solutions to drive market 153
8 AI FOR CUSTOMER SERVICE MARKET, BY TECHNOLOGY 154
8.1 INTRODUCTION 155
8.1.1 GENERATIVE AI 156
8.1.1.1 Empower dynamic and context-aware interactions with generative AI 156
8.1.2 OTHER AI 157
8.1.2.1 Enhancing customer service: Power of AI technologies 157
9 AI FOR CUSTOMER SERVICE MARKET, BY CUSTOMER
INTERACTION CHANNEL 158
9.1 INTRODUCTION 159
9.2 TEXT AND EMAIL 160
9.2.1 MAXIMIZED ENGAGEMENT WITH ASYNCHRONOUS COMMUNICATION TO DRIVE MARKET 160
9.3 VOICE 161
9.3.1 INCREASED INTEGRATION OF VOICE WITH DIGITAL TOOLS TO DRIVE MARKET 161
9.4 VIDEO/VISUAL 162
9.4.1 ENHANCED CUSTOMER ENGAGEMENT THROUGH VIDEO INTERACTIONS TO DRIVE MARKET 162
9.5 OMNICHANNEL 163
9.5.1 INTEGRATION OF DATA ACROSS CHANNELS FOR ENHANCED PERSONALIZATION TO DRIVE MARKET 163
 
10 AI FOR CUSTOMER SERVICE MARKET, BY REGION 165
10.1 INTRODUCTION 166
10.2 NORTH AMERICA 167
10.2.1 NORTH AMERICA: AI FOR CUSTOMER SERVICE MARKET DRIVERS 168
10.2.2 NORTH AMERICA: MACROECONOMIC IMPACT 168
10.2.3 US 174
10.2.3.1 Rise in need to enhance customer experience using AI-powered chatbots and virtual assistants to drive market 174
10.2.4 CANADA 175
10.2.4.1 Innovations in ethical AI to enhance AI-enabled customer support and drive market 175
10.3 EUROPE 176
10.3.1 EUROPE: AI FOR CUSTOMER SERVICE MARKET DRIVERS 176
10.3.2 EUROPE: MACROECONOMIC IMPACT 177
10.3.3 UK 182
10.3.3.1 Enhancing customer engagement with ethical AI to drive market 182
10.3.4 GERMANY 183
10.3.4.1 Advancing AI-powered customer service to drive market 183
10.3.5 FRANCE 184
10.3.5.1 Advancing ethical AI solutions for customer service to drive market 184
10.3.6 ITALY 185
10.3.6.1 Empowering SMEs and strengthening data privacy to drive market 185
10.3.7 SPAIN 186
10.3.7.1 Oracle’s USD 1 billion cloud investment to drive AI growth 186
10.3.8 REST OF EUROPE 187
10.4 ASIA PACIFIC 187
10.4.1 ASIA PACIFIC: AI FOR CUSTOMER SERVICE MARKET DRIVERS 188
10.4.2 ASIA PACIFIC: MACROECONOMIC IMPACT 188
10.4.3 CHINA 195
10.4.3.1 Implementation of regulatory approval for generative AI applications to drive market 195
10.4.4 JAPAN 196
10.4.4.1 Regulatory efforts and partnerships to drive AI for customer service 196
10.4.5 INDIA 197
10.4.5.1 Adoption of AI-driven solutions for personalized customer service to drive market 197
10.4.6 SOUTH KOREA 198
10.4.6.1 Increased AI integration for personalized customer support to drive market 198
10.4.7 AUSTRALIA & NEW ZEALAND 199
10.4.7.1 AI revolution in Australia & New Zealand to drive market 199
 
10.4.8 ASEAN COUNTRIES 200
10.4.8.1 Governments strengthening digital infrastructure for AI innovation to drive market 200
10.4.9 REST OF ASIA PACIFIC 201
10.5 MIDDLE EAST & AFRICA 202
10.5.1 MIDDLE EAST & AFRICA: AI FOR CUSTOMER SERVICE MARKET DRIVERS 202
10.5.2 MIDDLE EAST & AFRICA: MACROECONOMIC IMPACT 203
10.5.3 MIDDLE EAST 208
10.5.3.1 KSA 209
10.5.3.1.1 Saudi Arabia’s Vision 2030 for enhancing AI-driven customer engagement to drive market 209
10.5.3.2 UAE 210
10.5.3.2.1 UAE’s digital transformation fuels AI-driven customer service innovation 210
10.5.3.3 Bahrain 211
10.5.3.3.1 Bahrain’s regulatory sandbox drives AI innovation in customer service 211
10.5.3.4 Kuwait 212
10.5.3.4.1 SAP empowering Kuwaiti organizations by embedding AI into business applications for better operational efficiency 212
10.5.3.5 Rest of Middle East 213
10.5.4 AFRICA 214
10.6 LATIN AMERICA 215
10.6.1 LATIN AMERICA: AI FOR CUSTOMER SERVICE MARKET DRIVERS 215
10.6.2 LATIN AMERICA: MACROECONOMIC IMPACT 215
10.6.3 BRAZIL 221
10.6.3.1 Increased customer service innovation with AI-powered chatbots to drive market 221
10.6.4 MEXICO 222
10.6.4.1 Mexico leverages AI for customer service through key partnerships and innovations 222
10.6.5 ARGENTINA 223
10.6.5.1 Strategic partnerships and investment incentives to drive AI growth 223
10.6.6 REST OF LATIN AMERICA 224
11 COMPETITIVE LANDSCAPE 225
11.1 OVERVIEW 225
11.2 KEY PLAYER STRATEGIES/RIGHT TO WIN, 2020–2024 225
11.3 REVENUE ANALYSIS, 2019–2023 228
11.4 MARKET SHARE ANALYSIS, 2023 229
11.4.1 MARKET SHARE ANALYSIS OF KEY PLAYERS 229
11.4.2 MARKET RANKING ANALYSIS 230
 
11.5 PRODUCT COMPARATIVE ANALYSIS, BY PRODUCT TYPE 231
11.5.1 PRODUCT COMPARATIVE ANALYSIS, BY CHATBOTS AND
VIRTUAL ASSISTANTS 231
11.5.1.1 Google Dialogflow 231
11.5.1.2 IBM Watson Assistant 232
11.5.1.3 XO Automation (Kore.ai) 232
11.5.2 PRODUCT COMPARATIVE ANALYSIS, BY AI-DRIVEN TICKETING SYSTEMS 232
11.5.2.1 Freedy AI (Freshdesk) 232
11.5.2.2 AI bot (Zendesk) 232
11.5.2.3 Zia AI (Zoho) 232
11.5.3 PRODUCT COMPARATIVE ANALYSIS, BY RECOMMENDATION SYSTEMS 233
11.5.3.1 Amazon Personalize (AWS) 233
11.5.3.2 Product Recommendation Engines (Salesforce) 233
11.5.3.3 Dynamic Yield 233
11.6 COMPANY VALUATION AND FINANCIAL METRICS OF KEY VENDORS 234
11.7 COMPANY EVALUATION MATRIX: KEY PLAYERS, 2023 235
11.7.1 STARS 235
11.7.2 EMERGING LEADERS 235
11.7.3 PERVASIVE PLAYERS 235
11.7.4 PARTICIPANTS 235
11.7.5 COMPANY FOOTPRINT: KEY PLAYERS 237
11.7.5.1 Company footprint 237
11.7.5.2 Region footprint 238
11.7.5.3 Product type footprint 239
11.7.5.4 Customer interaction channel footprint 240
11.7.5.5 End user footprint 241
11.8 COMPANY EVALUATION MATRIX: STARTUPS/SMES, 2023 242
11.8.1 PROGRESSIVE COMPANIES 243
11.8.2 RESPONSIVE COMPANIES 243
11.8.3 DYNAMIC COMPANIES 243
11.8.4 STARTING BLOCKS 243
11.8.5 COMPETITIVE BENCHMARKING: STARTUPS/SMES, 2023 245
11.8.5.1 Detailed list of key startups/SMEs 245
11.8.5.2 Competitive benchmarking of key startups/SMEs 247
11.9 COMPETITIVE SCENARIO 248
11.9.1 PRODUCT LAUNCHES & ENHANCEMENTS 248
11.9.2 DEALS 251
 
12 COMPANY PROFILES 254
12.1 INTRODUCTION 254
12.2 KEY PLAYERS 254
12.2.1 MICROSOFT 254
12.2.1.1 Business overview 254
12.2.1.2 Products/Solutions/Services offered 256
12.2.1.3 Recent developments 256
12.2.1.3.1 Product launches and enhancements 256
12.2.1.3.2 Deals 257
12.2.1.4 MnM view 258
12.2.1.4.1 Key strengths 258
12.2.1.4.2 Strategic choices 258
12.2.1.4.3 Weaknesses and competitive threats 258
12.2.2 IBM 259
12.2.2.1 Business overview 259
12.2.2.2 Products/Solutions/Services offered 260
12.2.2.3 Recent developments 261
12.2.2.3.1 Product launches and enhancements 261
12.2.2.3.2 Deals 262
12.2.2.4 MnM view 262
12.2.2.4.1 Key strengths 262
12.2.2.4.2 Strategic choices 263
12.2.2.4.3 Weaknesses and competitive threats 263
12.2.3 GOOGLE 264
12.2.3.1 Business overview 264
12.2.3.2 Products/Solutions/Services offered 265
12.2.3.3 Recent developments 267
12.2.3.3.1 Product launches and enhancements 267
12.2.3.3.2 Deals 268
12.2.3.4 MnM view 269
12.2.3.4.1 Key strengths 269
12.2.3.4.2 Strategic choices 269
12.2.3.4.3 Weaknesses and competitive threats 269
12.2.4 AWS 270
12.2.4.1 Business overview 270
12.2.4.2 Products/Solutions/Services offered 271
12.2.4.3 Recent developments 272
12.2.4.3.1 Product launches and enhancements 272
12.2.4.3.2 Deals 273
12.2.4.4 MnM view 274
12.2.4.4.1 Key strengths 274
12.2.4.4.2 Strategic choices 274
12.2.4.4.3 Weaknesses and competitive threats 274
12.2.5 SALESFORCE 275
12.2.5.1 Business overview 275
12.2.5.2 Products/Solutions/Services offered 276
12.2.5.3 Recent developments 277
12.2.5.3.1 Product launches and enhancements 277
12.2.5.4 MnM view 278
12.2.5.4.1 Key strengths 278
12.2.5.4.2 Strategic choices 278
12.2.5.4.3 Weaknesses and competitive threats 278
12.2.6 ATLASSIAN 279
12.2.6.1 Business overview 279
12.2.6.2 Products/Solutions/Services offered 280
12.2.6.3 Recent developments 282
12.2.6.3.1 Product launches and enhancements 282
12.2.7 SERVICENOW 283
12.2.7.1 Business overview 283
12.2.7.2 Products/Solutions/Services offered 284
12.2.7.3 Recent developments 286
12.2.7.3.1 Product launches and enhancements 286
12.2.8 ZENDESK 287
12.2.8.1 Business overview 287
12.2.8.2 Products/Solutions/Services offered 288
12.2.8.3 Recent developments 290
12.2.8.3.1 Product launches and enhancements 290
12.2.8.3.2 Deals 290
12.2.9 SAP 291
12.2.9.1 Business overview 291
12.2.9.2 Products/Solutions/Services offered 292
12.2.9.3 Recent developments 293
12.2.9.3.1 Deals 293
12.2.10 SPRINKLR 294
12.2.10.1 Business overview 294
12.2.10.2 Products/Solutions/Services offered 295
12.2.10.3 Recent developments 298
12.2.10.3.1 Deals 298
12.2.11 OPENAI 299
12.2.11.1 Business overview 299
12.2.11.2 Products/Solutions/Services offered 300
12.2.11.3 Recent developments 301
12.2.11.3.1 Product Launches and Enhancements 301
12.2.11.3.2 Deals 302
12.2.12 AISERA 303
12.2.13 UIPATH 304
12.2.14 HUBSPOT 305
12.2.15 NICE 306
12.2.16 INTERCOM 307
12.2.17 QUALTRICS 308
12.2.18 FRESHWORKS 309
12.2.19 LIVEPERSON 310
12.2.20 HELPSHIFT 311
12.2.21 YELLOW.AI 312
12.2.22 COGITO 313
12.2.23 SMARTACTION 314
12.2.24 TALKDESK 315
12.2.25 FIVE9 316
12.2.26 RINGCENTRAL 317
12.2.27 NEXTIVA 318
12.2.28 KORE.AI 319
12.2.29 DYNAMIC YIELD 320
12.2.30 JIOHAPTIK 321
12.2.31 ORACLE 322
12.2.32 AFINITI 322
12.3 STARTUPS/SMES 323
12.3.1 KOMMUNICATE 323
12.3.2 HELP SCOUT 324
12.3.3 GORGIAS 325
12.3.4 ATERA 325
12.3.5 ADA 326
12.3.6 KUSTOMER 327
12.3.7 LEVITY 328
12.3.8 COGNIGY 328
12.3.9 ENGAGEWARE 329
12.3.10 NETOMI 329
12.3.11 LEVELAI 330
12.3.12 SYBILL AI 331
12.3.13 ONE AI 332
12.3.14 BRAINFISH 333
12.3.15 SENTISUM 334
12.3.16 BALTO 335
12.3.17 TOVIE AI 336
12.3.18 GURU 337
12.3.19 TIDIO 338
12.3.20 QUIQ 339
12.3.21 AIRCALL 340
12.3.22 ONEREACH.AI 340
12.3.23 CRESTA 341
12.3.24 DEEPDESK 342
12.3.25 FRONT 342
12.3.26 FULLVIEW 343
12.3.27 CRESCENDO AI 343
12.3.28 GRIDSPACE 344
13 ADJACENT AND RELATED MARKETS 345
13.1 INTRODUCTION 345
13.2 CONVERSATIONAL AI MARKET – GLOBAL FORECAST TO 2030 345
13.2.1 MARKET DEFINITION 345
13.2.2 MARKET OVERVIEW 345
13.2.2.1 Conversational AI market, by offering 346
13.2.2.2 Conversational AI market, by service 347
13.2.2.3 Conversational AI market, by business function 348
13.2.2.4 Conversational AI market, by conversational agent type 348
13.2.2.5 Conversational AI market, by integration mode 349
13.2.2.6 Conversational AI market, by vertical 350
13.2.2.7 Conversational AI market, by region 351
13.3 AI AGENTS MARKET 352
13.3.1 MARKET DEFINITION 352
13.3.2 MARKET OVERVIEW 353
13.3.2.1 AI agents market, by agent system 353
13.3.2.2 AI agents market, by product type 354
13.3.2.3 AI agents market, by agent role 354
13.3.2.4 AI agents market, by end user 356
13.3.2.5 AI agents market, by region 356
14 APPENDIX 358
14.1 DISCUSSION GUIDE 358
14.2 KNOWLEDGESTORE: MARKETSANDMARKETS’ SUBSCRIPTION PORTAL 365
14.3 CUSTOMIZATION OPTIONS 367
14.4 RELATED REPORTS 367
14.5 AUTHOR DETAILS 368