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AI for Customer Service - Company Evaluation Report, 2025 (Abridged Report)

Publisher MarketsandMarkets
Published Jul 01, 2025
Length 175 Pages
SKU # MKMK20244442

Description

The AI for Customer Service Companies Quadrant is a comprehensive industry analysis that provides valuable insights into the global market for AI for Customer Service. This quadrant offers a detailed evaluation of key market players, technological advancements, product innovations, and emerging trends shaping the industry. MarketsandMarkets 360 Quadrants evaluated over 100 companies, of which the Top 32 AI for Customer Service Companies were categorized and recognized as quadrant leaders.

AI for customer service leverages artificial intelligence technologies to enhance all facets of customer support by enabling organizations to automate experiences, streamline processes, and boost agent productivity. AI-powered tools—such as chatbots, voice bots, workflow automation, recommendation engines, and diagnostic systems—offer round-the-clock, personalized, data-driven support designed to elevate the agent and customer experience. These solutions analyze data from customer interactions to resolve or assist with queries in real time. AI-based agent assistance tools empower support teams within major enterprises to deliver faster, more efficient resolutions, while also generating customized responses for individual customers. The emergence of generative AI (Gen AI) in customer service further enhances this landscape by enabling more natural, personalized interactions and real-time, tailored communication.

Another critical area where AI is transforming customer service is in backend operations. It helps streamline support infrastructure, boosting efficiency and enabling quicker responsiveness for both agents and customers. The customer service sector is increasingly adopting AI to develop intelligent support ecosystems that enrich the experience for users and support teams alike. From adaptive chatbots to AI-powered virtual agents, these technologies are reshaping how services are delivered—offering seamless, efficient assistance. AI’s integration into service delivery improves customer satisfaction, sharpens support strategies, and optimizes operational workflows.

The 360 Quadrant maps the AI for Customer Service companies based on criteria such as revenue, geographic presence, growth strategies, investments, and sales strategies for the market presence of the AI for Customer Service quadrant. The top criteria for product footprint evaluation included By END USER (BFSI, Media & Entertainment, Telecommunications, Government & Public Sector, Healthcare & Life Sciences, Manufacturing, Retail & E-Commerce, Technology & Software, Travel & Hospitality, Transportation & Logistics, Other End Users), By PRODUCT (Type, By Deployment Mode, By Customer Service Delivery Mode, By Functional Area), and By CUSTOMER INTERACTION CHANNEL (Text and Email, Voice, Video/Visual, Omnichannel).

Key Players

Key players in the Ai for Customer Service market include major global corporations and specialized innovators such as 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, and Afiniti. These companies are actively investing in research and development, forming strategic partnerships, and engaging in collaborative initiatives to drive innovation, expand their global footprint, and maintain a competitive edge in this rapidly evolving market.

Top 3 Companies

Microsoft

Microsoft holds a significant market share due to its strategic focus on AI technologies, such as generative AI and cloud-based solutions, enhancing the customer service landscape. Their robust product portfolio, including Microsoft Dynamics 365, offers AI-driven capabilities that improve customer engagement and operational efficiency. The company's positioning strategy includes expansion through partnerships, such as with HCLTech, to innovate in customer service solutions. Microsoft's product portfolio is diverse, catering to various sectors with a focus on integrating AI to streamline customer interactions.

IBM

IBM's strong position in the customer service AI market is anchored by its Watsonx platform, which enhances data processing and analytics, thereby improving customer service delivery. The company excels in providing hybrid cloud and AI solutions, which solidifies its presence across different industries. IBM's strategy includes significant collaborations, such as with Elasticsearch, to enhance conversational AI capabilities. Despite facing competitive pressures, IBM's market share and extensive product offerings make it a formidable player.

Google

Google leads the market with its advanced AI technologies, underpinned by their Gemini model, which offers superior data analysis and decision-making capabilities. The company's robust AI product portfolio is continuously expanded through strategic partnerships, like the one with Tata Consultancy Services, to enhance AI adoption in diverse sectors. These products aim to offer seamless, efficient, and personalized customer interactions, reinforcing Google’s market dominance. Their strategic expansion through partnerships and innovations keeps them competitive and addresses diverse customer needs.
Tables List
Table 1 Ai For Customer Service Market: Ecosystem
Table 2 Ai For Customer Service Market: Detailed List Of
Conferences And Events, 2025–2026
Table 3 Patents Filed, 2014–2024
Table 4 Ai For Customer Service Market: List Of Patents Granted, 2023–2024
Table 5 Ai For Customer Service Market: Overview Of Strategies Adopted
By Key Vendors, 2020–2024
Table 6 Ai For Customer Service Market: Degree Of Competition, 2023
Table 7 Ai For Customer Service Market: Region Footprint
Table 8 Ai For Customer Service Market: Product Type Footprint
Table 9 Ai For Customer Service Market:
Customer Interaction Channel Footprint
Table 10 Ai For Customer Service Market: End User Footprint
Table 11 Ai For Customer Service Market: Detailed List Of Key Startups/Smes
Table 12 Ai For Customer Service Market:
Competitive Benchmarking Of Startups/Smes
Table 13 Ai For Customer Service Market:
Product Launches & Enhancements, January 2021–january 2025
Table 14 Ai For Customer Service Market: Deals, January 2021–january 2025
Table 15 Microsoft: Company Overview
Table 16 Microsoft: Products/Solutions/Services Offered
Table 17 Microsoft: Product Launches And Enhancements
Table 18 Microsoft: Deals
Table 19 Ibm: Company Overview
Table 20 Ibm: Products/Solutions/Services Offered
Table 21 Ibm: Product Launches And Enhancements
Table 22 Ibm: Deals
Table 23 Google: Company Overview
Table 24 Google: Products/Solutions/Services Offered
Table 25 Google: Product Launches And Enhancements
Table 26 Google: Deals
Table 27 Aws: Company Overview
Table 28 Aws: Products/Solutions/Services Offered
Table 29 Aws: Product Launches And Enhancements
Table 30 Aws: Deals
Table 31 Salesforce: Company Overview
Table 32 Salesforce: Products/Solutions/Services Offered
Table 33 Salesforce: Product Launches And Enhancements
Table 34 Atlassian: Company Overview
Table 35 Atlassian: Products/Solutions/Services Offered
Table 36 Atlassian: Product Launches And Enhancements
Table 37 Servicenow: Company Overview
Table 38 Servicenow: Products/Solutions/Services Offered
Table 39 Servicenow: Product Launches And Enhancements
Table 40 Zendesk: Company Overview
Table 41 Zendesk: Products/Solutions/Services Offered
Table 42 Zendesk: Product Launches And Enhancements
Table 43 Zendesk: Deals
Table 44 Sap: Company Overview
Table 45 Sap: Products/Solutions/Services Offered
Table 46 Sap: Deals
Table 47 Sprinklr: Company Overview
Table 48 Sprinklr: Products/Solutions/Services Offered
Table 49 Sprinklr: Deals
Table 50 Openai: Company Overview
Table 51 Openai: Products/Solutions/Services Offered
Table 52 Openai: Product Launches And Enhancements
Table 53 Openai: Deals
Table 54 Primary Interviews
Figures List
Figure 1 Ai For Customer Service Market: Drivers, Restraints,
Opportunities, And Challenges
Figure 2 Evolution Of Ai For Customer Service Market
Figure 3 Ai For Customer Service Market Ecosystem: Key Players
Figure 4 Porter’s Five Forces Analysis
Figure 5 Number Of Patents Granted To Vendors In Last 10 Years
Figure 6 Regional Analysis Of Patents Granted, 2014–2024
Figure 7 Trends/Disruptions Impacting Customer Business
Figure 8 Market Potential Of Generative Ai In Enhancing
Ai For Customer Service Across Key End Users
Figure 9 Ai For Customer Service Market: Revenue Analysis Of
Five Key Players, 2019–2023
Figure 10 Share Analysis Of Leading Companies In
Ai For Customer Service Market, 2023
Figure 11 Product Comparative Analysis, By Product Type
Figure 12 Company Valuation And Financial Metrics Of Key Vendors
Figure 13 Year-to-date (Ytd) Price Total Return And
5-year Stock Beta Of Key Vendors
Figure 14 Ai For Customer Service Market:
Company Evaluation Matrix (Key Players), 2023
Figure 15 Ai For Customer Service Market: Company Footprint
Figure 16 Ai For Customer Service Market:
Company Evaluation Matrix (Startups/Smes), 2023
Figure 17 Microsoft: Company Snapshot
Figure 18 Ibm: Company Snapshot
Figure 19 Google: Company Snapshot
Figure 20 Aws: Company Snapshot
Figure 21 Salesforce: Company Snapshot
Figure 22 Atlassian: Company Snapshot
Figure 23 Servicenow: Company Snapshot
Figure 24 Sprinklr: Company Snapshot
Figure 25 Ai For Customer Service Market: Research Design

Table of Contents

175 Pages
1 Introduction
1.1 Market Definition
1.2 Inclusions & Exclusions
1.3 Stakeholders
2 Executive Summary
3 Market Overview And Industry Trends
3.1 Introduction
3.2 Market Dynamics
3.2.1 Drivers
3.2.1.1 Improved Customer Engagement With Omni-channel
Self-service Options
3.2.1.2 Maximizing Agent Efficiency Through Ai Integration
3.2.1.3 Enhancing Efficiency And Satisfaction With Intelligent Routing
3.2.2 Restraints
3.2.2.1 Mitigating Deepfake Threats In Customer Service
3.2.3 Opportunities
3.2.3.1 Transforming Customer Service With Generative Ai Innovations
3.2.3.2 Empowering Proactive Customer Service With Ai Solutions
3.2.4 Challenges
3.2.4.1 Threats Of Job Displacements In Customer Service
3.3 Industry Trends
3.3.1 Evolution Of Ai For Customer Service Market
3.3.2 Ecosystem Analysis
3.3.2.1 Chatbots And Virtual Assistant Providers
3.3.2.1.1 Rule-based Chatbots
3.3.2.1.2 Conversational Bots
3.3.2.1.3 Voice Assistants
3.3.2.2 Ai-driven Ticketing System Providers
3.3.2.2.1 Automated Ticket Routing
3.3.2.2.2 Self-service Portals
3.3.2.2.3 Case Resolution Assistant
3.3.2.3 Sentiment And Feedback Analysis Tools
3.3.2.3.1 Sentiment & Emotion Detection
3.3.2.3.2 Customer Feedback
3.3.2.3.3 Social Media Monitoring
3.3.2.4 Recommendation Systems
3.3.2.4.1 Dynamic Faqs
3.3.2.4.2 Knowledge Base Platforms
3.3.2.5 Visual And Diagnostic Tools
3.3.2.5.1 Image Recognition Tools
3.3.2.5.2 Voice-based Assistance
3.3.2.6 Workflow Automation
3.3.2.6.1 Robotic Process Automation
3.3.2.6.2 Integrated Crm Automation
3.3.2.7 Content Management
3.3.2.7.1 Content Distribution
3.3.2.7.2 Content Generation
3.3.2.7.3 Content Moderation
3.3.2.8 Ai Agents
3.3.2.8.1 Performance Analytics
3.3.2.8.2 Conversation Intelligence
3.3.2.9 Customer Interaction Channels
3.3.2.9.1 Text And Email
3.3.2.9.2 Voice
3.3.2.9.3 Video/Visual
3.3.2.9.4 Omnichannel
3.3.2.10 End Users
3.3.3 Technology Analysis
3.3.3.1 Key Technologies
3.3.3.1.1 Nlp And Deep Learning
3.3.3.1.2 Big Data Analytics
3.3.3.1.3 Generative Ai
3.3.3.1.3.1 Rule-based Models
3.3.3.1.3.2 Statistical Models
3.3.3.1.3.3 Deep Learning Models
3.3.3.1.3.4 Generative Adversarial Networks (Gans)
3.3.3.1.3.5 Autoencoders
3.3.3.1.3.6 Convolutional Neural Networks (Cnns)
3.3.3.1.3.7 Transformer-based Large Language Models (Llms)
3.3.3.1.4 Ai Agent Memory
3.3.3.1.4.1 Short-term Memory (Stm)
3.3.3.1.4.2 Long-term Memory (Ltm) Type 1
3.3.3.1.4.3 Long-term Memory (Ltm) Type 2
3.3.3.1.4.4 Long-term Memory (Ltm) Type 3
3.3.3.1.5 Robotic Process Automation (Rpa)
3.3.3.2 Adjacent Technologies
3.3.3.2.1 Cloud Computing
3.3.3.2.2 Edge Computing
3.3.3.2.3 Internet Of Things
3.3.3.2.4 5g And Advanced Connectivity
3.3.3.3 Complementary Technologies
3.3.3.3.1 Cybersecurity
3.3.3.3.2 Augmented Reality (Ar) And Virtual Reality (Vr)
3.3.3.3.3 Blockchain
3.3.4 Porter’s Five Forces Analysis
3.3.4.1 Threat Of New Entrants
3.3.4.2 Threat Of Substitutes
3.3.4.3 Bargaining Power Of Suppliers
3.3.4.4 Bargaining Power Of Buyers
3.3.4.5 Intensity Of Competitive Rivalry
3.3.5 Key Conferences And Events (2025–2026)
3.3.6 Patent Analysis
3.3.6.1 Methodology
3.3.6.2 Patents Filed, By Document Type
3.3.6.3 Innovations And Patent Applications
3.3.7 Trends/Disruptions Impacting Customer Business
3.3.8 Impact Of Generative Ai On Ai For Customer Service Market
3.3.8.1 Top Use Cases & Market Potential
3.3.8.2 Key Use Cases
3.3.8.2.1 Enhanced Efficiency And Productivity
3.3.8.2.2 24/7 Availability
3.3.8.2.3 Personalized Customer Interactions
3.3.8.2.4 Cost Reduction
3.3.8.2.5 Proactive Customer Engagement
3.3.8.2.6 Scalability
4 Competitive Landscape
4.1 Overview
4.2 Key Player Strategies/Right To Win, 2020–2024
4.3 Revenue Analysis, 2019–2023
4.4 Market Share Analysis, 2023
4.4.1 Market Share Analysis Of Key Players
4.4.2 Market Ranking Analysis
4.5 Product Comparative Analysis, By Product Type
4.5.1 Product Comparative Analysis, By Chatbots And Virtual Assistants
4.5.1.1 Google Dialogflow
4.5.1.2 Ibm Watson Assistant
4.5.1.3 Xo Automation (Kore.Ai)
4.5.2 Product Comparative Analysis, By Ai-driven Ticketing Systems
4.5.2.1 Freedy Ai (Freshdesk)
4.5.2.2 Ai Bot (Zendesk)
4.5.2.3 Zia Ai (Zoho)
4.5.3 Product Comparative Analysis, By Recommendation Systems
4.5.3.1 Amazon Personalize (Aws)
4.5.3.2 Product Recommendation Engines (Salesforce)
4.5.3.3 Dynamic Yield
4.6 Company Valuation And Financial Metrics Of Key Vendors
4.7 Company Evaluation Matrix: Key Players, 2023
4.7.1 Stars
4.7.2 Emerging Leaders
4.7.3 Pervasive Players
4.7.4 Participants
4.7.5 Company Footprint: Key Players
4.7.5.1 Company Footprint
4.7.5.2 Region Footprint
4.7.5.3 Product Type Footprint
4.7.5.4 Customer Interaction Channel Footprint
4.7.5.5 End User Footprint
4.8 Company Evaluation Matrix: Startups/Smes, 2023
4.8.1 Progressive Companies
4.8.2 Responsive Companies
4.8.3 Dynamic Companies
4.8.4 Starting Blocks
4.8.5 Competitive Benchmarking: Startups/Smes, 2023
4.8.5.1 Detailed List Of Key Startups/Smes
4.8.5.2 Competitive Benchmarking Of Key Startups/Smes
4.9 Competitive Scenario
4.9.1 Product Launches & Enhancements
4.9.2 Deals
5 Company Profiles
5.1 Introduction
5.2 Key Players
5.2.1 Microsoft
5.2.1.1 Business Overview
5.2.1.2 Products/Solutions/Services Offered
5.2.1.3 Recent Developments
5.2.1.3.1 Product Launches And Enhancements
5.2.1.3.2 Deals
5.2.1.4 Mnm View
5.2.1.4.1 Key Strengths
5.2.1.4.2 Strategic Choices
5.2.1.4.3 Weaknesses And Competitive Threats
5.2.2 Ibm
5.2.2.1 Business Overview
5.2.2.2 Products/Solutions/Services Offered
5.2.2.3 Recent Developments
5.2.2.3.1 Product Launches And Enhancements
5.2.2.3.2 Deals
5.2.2.4 Mnm View
5.2.2.4.1 Key Strengths
5.2.2.4.2 Strategic Choices
5.2.2.4.3 Weaknesses And Competitive Threats
5.2.3 Google
5.2.3.1 Business Overview
5.2.3.2 Products/Solutions/Services Offered
5.2.3.3 Recent Developments
5.2.3.3.1 Product Launches And Enhancements
5.2.3.3.2 Deals
5.2.3.4 Mnm View
5.2.3.4.1 Key Strengths
5.2.3.4.2 Strategic Choices
5.2.3.4.3 Weaknesses And Competitive Threats
5.2.4 Aws
5.2.4.1 Business Overview
5.2.4.2 Products/Solutions/Services Offered
5.2.4.3 Recent Developments
5.2.4.3.1 Product Launches And Enhancements
5.2.4.3.2 Deals
5.2.4.4 Mnm View
5.2.4.4.1 Key Strengths
5.2.4.4.2 Strategic Choices
5.2.4.4.3 Weaknesses And Competitive Threats
5.2.5 Salesforce
5.2.5.1 Business Overview
5.2.5.2 Products/Solutions/Services Offered
5.2.5.3 Recent Developments
5.2.5.3.1 Product Launches And Enhancements
5.2.5.4 Mnm View
5.2.5.4.1 Key Strengths
5.2.5.4.2 Strategic Choices
5.2.5.4.3 Weaknesses And Competitive Threats
5.2.6 Atlassian
5.2.6.1 Business Overview
5.2.6.2 Products/Solutions/Services Offered
5.2.6.3 Recent Developments
5.2.6.3.1 Product Launches And Enhancements
5.2.7 Servicenow
5.2.7.1 Business Overview
5.2.7.2 Products/Solutions/Services Offered
5.2.7.3 Recent Developments
5.2.7.3.1 Product Launches And Enhancements
5.2.8 Zendesk
5.2.8.1 Business Overview
5.2.8.2 Products/Solutions/Services Offered
5.2.8.3 Recent Developments
5.2.8.3.1 Product Launches And Enhancements
5.2.8.3.2 Deals
5.2.9 Sap
5.2.9.1 Business Overview
5.2.9.2 Products/Solutions/Services Offered
5.2.9.3 Recent Developments
5.2.9.3.1 Deals
5.2.10 Sprinklr
5.2.10.1 Business Overview
5.2.10.2 Products/Solutions/Services Offered
5.2.10.3 Recent Developments
5.2.10.3.1 Deals
5.2.11 Openai
5.2.11.1 Business Overview
5.2.11.2 Products/Solutions/Services Offered
5.2.11.3 Recent Developments
5.2.11.3.1 Product Launches And Enhancements
5.2.11.3.2 Deals
5.2.12 Aisera
5.2.13 Uipath
5.2.14 Hubspot
5.2.15 Nice
5.2.16 Intercom
5.2.17 Qualtrics
5.2.18 Freshworks
5.2.19 Liveperson
5.2.20 Helpshift
5.2.21 Yellow.Ai
5.2.22 Cogito
5.2.23 Smartaction
5.2.24 Talkdesk
5.2.25 Five9
5.2.26 Ringcentral
5.2.27 Nextiva
5.2.28 Kore.Ai
5.2.29 Dynamic Yield
5.2.30 Jiohaptik
5.2.31 Oracle
5.2.32 Afiniti
5.3 Startups/Smes
5.3.1 Kommunicate
5.3.2 Help Scout
5.3.3 Gorgias
5.3.4 Atera
5.3.5 Ada
5.3.6 Kustomer
5.3.7 Levity
5.3.8 Cognigy
5.3.9 Engageware
5.3.10 Netomi
5.3.11 Levelai
5.3.12 Sybill Ai
5.3.13 One Ai
5.3.14 Brainfish
5.3.15 Sentisum
5.3.16 Balto
5.3.17 Tovie Ai
5.3.18 Guru
5.3.19 Tidio
5.3.20 Quiq
5.3.21 Aircall
5.3.22 Onereach.Ai
5.3.23 Cresta
5.3.24 Deepdesk
5.3.25 Front
5.3.26 Fullview
5.3.27 Crescendo Ai
5.3.28 Gridspace
6 Appendix
6.1 Research Methodology
6.1.1 Research Data
6.1.1.1 Secondary Data
6.1.1.2 Primary Data
6.1.2 Research Limitations
6.2 Company Evaluation Matrix: Methodology
6.3 Author Details

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