The AI in Customer Relationship Management Market Size is valued at USD 14.8 billion in 2023 and is predicted to reach USD 138.6 billion by the year 2031 at a 32.5% CAGR during the forecast period for 2024-2031.
AI in Customer Relationship Management (CRM) enhances how businesses manage customer interactions by automating tasks, personalizing experiences, and providing insights into customer behavior. AI-powered tools like chatbots, virtual assistants, and predictive analytics improve customer service, sales forecasting, and lead scoring. AI also helps with personalized marketing, churn prediction, and sentiment analysis, enabling companies to optimize customer engagement and satisfaction. By automating routine tasks & offering real-time insights, AI makes CRM more efficient, customer-focused, and data-driven
The ability of AI to perform predictive analytics is a key benefit for CRM. AI systems can predict consumer behaviour, which enables companies to take proactive measures to resolve problems and grab opportunities. This predictive power helps to lower churn, find possible high-value clients, and increase customer lifetime value.
The AI in customer relationship management is being driven by several factors including demand for personalized customer experience, rising investment in AI, growing volume of customer data, need for improved customer support and many others. However, the market growth of this market is restricted by some variables like a shortage of skilled workforce, data privacy and security concerns, technical limitations and others.
Furthermore, integration with other technologies such as IoT and big data analytics are some of the major potential opportunities for market growth during the projected period.
The AI in the customer relationship management market is segmented as type, application, end-use industry and deployment model. Based on type, the market is segmented into machine learning, natural language processing (NLP), image and speech recognition, predictive analytics, chatbots, and virtual assistants. By application, the market is further segmented into sales automation, customer service and support, marketing personalization, customer data analysis and lead scoring and qualification. Based on industry the industry is bifurcated into retail and e-commerce, banking and finance, healthcare, telecommunications, travel, and hospitality. Based on the deployment model, the global AI in customer relationship management market is divided into Cloud-based AI-CRM, On-premises AI-CRM and Hybrid AI-CRM.
The chatbots and virtual assistants category is expected to hold a major share of the global AI in the CRM market. Routine interactions with customers are automated by chatbots as well as virtual assistants, which eliminates the need for human agents. Businesses save an enormous amount of money as a result, freeing up resources for more difficult jobs. Providing 24/7 help improves client retention and happiness. Companies don't need to hire more workers to service clients in multiple time zones. Furthermore, through conversations, chatbots and virtual assistants collect useful customer data that can be examined to learn more about the preferences, behaviour, and problems of the user. This data-driven methodology aids in the improvement of sales and marketing plans. Thus, during the forecast period, this is anticipated to fuel market expansion.
The customer service and support segment is projected to grow at a rapid rate in the global AI in customer relationship management market. By automating interactions, delivering tailored experiences, and improving operational efficiency, artificial intelligence (AI) is completely changing customer service and support in the CRM market. Although there are certain difficulties with AI-driven customer care solutions, such as data protection, integration complexity, and client acceptability, they are greatly outweighed by the advantages. The use of AI in CRM will increase as technology develops, leading to notable gains in consumer satisfaction and organizational effectiveness.
The North American AI in customer relationship management market is expected to report the largest market share in the near future. AI & machine learning (ML) are among the cutting-edge technologies that North American businesses are quick to embrace. Enhancing customer service and engagement has expedited the incorporation of AI into CRM systems. Additionally, the area is home to top IT firms that are pioneering the development and application of AI-driven CRM solutions, such as Salesforce, Microsoft, Oracle, and Adobe. The creation of creative AI solutions in CRM is further supported by large R&D expenditures made by the public and commercial sectors, which promote ongoing advancement and the development of fresh abilities. In addition, Europe is likely to grow rapidly in the global AI in customer relationship management market due to rapid digital transformation and increasing government initiatives and investments.
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Report Attribute |
Specifications |
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Market Size Value In 2023 |
USD 14.8 Bn |
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Revenue Forecast In 2031 |
USD 138.6 Bn |
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Growth Rate CAGR |
CAGR of 32.5% from 2024 to 2031 |
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Quantitative Units |
Representation of revenue in US$ Bn and CAGR from 2024 to 2031 |
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Historic Year |
2019 to 2023 |
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Forecast Year |
2024-2031 |
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Report Coverage |
The forecast of revenue, the position of the company, the competitive market structure, growth prospects, and trends |
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Segments Covered |
By Type, Application, End-Use Industry and Deployment Model |
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Regional Scope |
North America; Europe; Asia Pacific; Latin America; Middle East & Africa |
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Country Scope |
U.S.; Canada; U.K.; Germany; China; India; Japan; Brazil; Mexico; France; Italy; Spain; South East Asia; South Korea |
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Competitive Landscape |
Salesforce Inc., Microsoft Corporation, Oracle Corporation, IBM Corporation, SAP SE, Zendesk Inc., Adobe Inc., C3.ai Inc., Zoho Corporation, Genesys, Freshworks Inc., Pegasystems Inc. and other market plyers. |
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Customization Scope |
Free customization report with the procurement of the report and modifications to the regional and segment scope. Particular Geographic competitive landscape. |
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Pricing And Available Payment Methods |
Explore pricing alternatives that are customized to your particular study requirements. |
Chapter 1. Methodology and Scope
1.1. Research Methodology
1.2. Research Scope & Assumptions
Chapter 2. Executive Summary
Chapter 3. Global AI in Customer Relationship Management Market Snapshot
Chapter 4. Global AI in Customer Relationship Management Market Variables, Trends & Scope
4.1. Market Segmentation & Scope
4.2. Drivers
4.3. Challenges
4.4. Trends
4.5. Investment and Funding Analysis
4.6. Industry Analysis – Porter’s Five Forces Analysis
4.7. Competitive Landscape & Market Share Analysis
4.8. Impact of Covid-19 Analysis
Chapter 5. Market Segmentation 1: by Industry Estimates & Trend Analysis
5.1. by Industry & Market Share, 2019 & 2031
5.2. Market Size (Value (US$ Mn)) & Forecasts and Trend Analyses, 2019 to 2031 for the following by Industry:
5.2.1. Retail and E-commerce
5.2.2. Banking and Finance
5.2.3. Healthcare
5.2.4. Telecommunications
5.2.5. Travel and Hospitality
Chapter 6. Market Segmentation 2: by Application Estimates & Trend Analysis
6.1. by Application & Market Share, 2019 & 2031
6.2. Market Size (Value (US$ Mn)) & Forecasts and Trend Analyses, 2019 to 2031 for the following by Application:
6.2.1. Sales Automation
6.2.2. Customer Service and Support
6.2.3. Marketing Personalization
6.2.4. Customer Data Analysis
6.2.5. Lead Scoring and Qualification
Chapter 7. Market Segmentation 3: by Type Estimates & Trend Analysis
7.1. by Type & Market Share, 2019 & 2031
7.2. Market Size (Value (US$ Mn)) & Forecasts and Trend Analyses, 2019 to 2031 for the following by Type:
7.2.1. Machine Learning
7.2.2. Natural Language Processing (NLP)
7.2.3. Image and Speech Recognition
7.2.4. Predictive Analytics
7.2.5. Chatbots and Virtual Assistants
Chapter 8. Market Segmentation 4: by Deployment Model Estimates & Trend Analysis
8.1. By Deployment Model & Market Share, 2019 & 2031
8.2. Market Size (Value (US$ Mn)) & Forecasts and Trend Analyses, 2019 to 2031 for the following By Deployment Model:
8.2.1. Cloud-based AI-CRM
8.2.2. On-premises AI-CRM
8.2.3. Hybrid AI-CRM
Chapter 9. AI in Customer Relationship Management Market Segmentation 5: Regional Estimates & Trend Analysis
9.1. North America
9.1.1. North America AI in Customer Relationship Management Market Revenue (US$ Million) Estimates and Forecasts by Industry, 2024-2031
9.1.2. North America AI in Customer Relationship Management Market Revenue (US$ Million) Estimates and Forecasts by Application, 2024-2031
9.1.3. North America AI in Customer Relationship Management Market Revenue (US$ Million) Estimates and Forecasts by Type, 2024-2031
9.1.4. North America AI in Customer Relationship Management Market Revenue (US$ Million) Estimates and Forecasts by Deployment Model, 2024-2031
9.1.5. North America AI in Customer Relationship Management Market Revenue (US$ Million) Estimates and Forecasts by country, 2024-2031
9.2. Europe
9.2.1. Europe AI in Customer Relationship Management Market Revenue (US$ Million) Estimates and Forecasts by Industry, 2024-2031
9.2.2. Europe AI in Customer Relationship Management Market Revenue (US$ Million) Estimates and Forecasts by Application, 2024-2031
9.2.3. Europe AI in Customer Relationship Management Market Revenue (US$ Million) Estimates and Forecasts by Type, 2024-2031
9.2.4. Europe AI in Customer Relationship Management Market Revenue (US$ Million) Estimates and Forecasts by Deployment Model, 2024-2031
9.2.5. Europe AI in Customer Relationship Management Market Revenue (US$ Million) Estimates and Forecasts by country, 2024-2031
9.3. Asia Pacific
9.3.1. Asia Pacific AI in Customer Relationship Management Market Revenue (US$ Million) Estimates and Forecasts by Industry, 2024-2031
9.3.2. Asia Pacific AI in Customer Relationship Management Market Revenue (US$ Million) Estimates and Forecasts by Application, 2024-2031
9.3.3. Asia-Pacific Thermal Cyclers Asia-Pacific AI in Customer Relationship Management Market Revenue (US$ Million) Estimates and Forecasts by Type, 2024-2031
9.3.4. Asia-Pacific AI in Customer Relationship Management Market Revenue (US$ Million) Estimates and Forecasts by Deployment Model, 2024-2031
9.3.5. Asia Pacific AI in Customer Relationship Management Market Revenue (US$ Million) Estimates and Forecasts by country, 2024-2031
9.4. Latin America
9.4.1. Latin America AI in Customer Relationship Management Market Revenue (US$ Million) Estimates and Forecasts by Industry, 2024-2031
9.4.2. Latin America AI in Customer Relationship Management Market Revenue (US$ Million) Estimates and Forecasts by Application, 2024-2031
9.4.3. Latin America AI in Customer Relationship Management Market Revenue (US$ Million) Estimates and Forecasts by Type, 2024-2031
9.4.4. Latin America AI in Customer Relationship Management Market Revenue (US$ Million) Estimates and Forecasts by Deployment Model, 2024-2031
9.4.5. Latin America AI in Customer Relationship Management Market Revenue (US$ Million) Estimates and Forecasts by country, 2024-2031
9.5. Middle East & Africa
9.5.1. Middle East & Africa AI in Customer Relationship Management Market Revenue (US$ Million) Estimates and Forecasts by Industry, 2024-2031
9.5.2. Middle East & Africa AI in Customer Relationship Management Market Revenue (US$ Million) Estimates and Forecasts by Application, 2024-2031
9.5.3. Middle East & Africa AI in Customer Relationship Management Market Revenue (US$ Million) Estimates and Forecasts by Type, 2024-2031
9.5.4. Middle East & Africa AI in Customer Relationship Management Market Revenue (US$ Million) Estimates and Forecasts by Deployment Model, 2024-2031
9.5.5. Middle East & Africa AI in Customer Relationship Management Market Revenue (US$ Million) Estimates and Forecasts by country, 2024-2031
Chapter 10. Competitive Landscape
10.1. Major Mergers and Acquisitions/Strategic Alliances
10.2. Company Profiles
10.2.1. Salesforce
10.2.2. Microsoft Corporation
10.2.3. IBM Corporation
10.2.4. Oracle Corporation
10.2.5. SAP SE
10.2.6. Adobe Inc.
10.2.7. Pegasystems Inc.
10.2.8. HubSpot Inc.
10.2.9. Zendesk Inc.
10.2.10. Freshworks Inc.
10.2.11. Genesys Telecommunications Laboratories, Inc.
10.2.12. Zoho Corporation
10.2.13. SugarCRM Inc.
10.2.14. Insightly Inc.
10.2.15. Infusionsoft by Keap
10.2.16. Nimble LLC
10.2.17. Act-On Software Inc.
10.2.18. Copper Inc.
10.2.19. Agile CRM Inc.
10.2.20. Apptivo Inc.
10.2.21. EngageBay Inc.
10.2.22. Ontraport Inc.
10.2.23. Really Simple Systems Ltd.
10.2.24. Soffront Software Inc.
10.2.25. Maximizer Services Inc.
AI in Customer Relationship Management Market By Type-
AI in Customer Relationship Management Market By Application-
AI in Customer Relationship Management Market By Industry-
AI in Customer Relationship Management Market By Deployment Model-
AI in Customer Relationship Management Market By Region-
North America-
Europe-
Asia-Pacific-
Latin America-
Middle East & Africa-
InsightAce Analytic follows a standard and comprehensive market research methodology focused on offering the most accurate and precise market insights. The methods followed for all our market research studies include three significant steps – primary research, secondary research, and data modeling and analysis - to derive the current market size and forecast it over the forecast period. In this study, these three steps were used iteratively to generate valid data points (minimum deviation), which were cross-validated through multiple approaches mentioned below in the data modeling section.
Through secondary research methods, information on the market under study, its peer, and the parent market was collected. This information was then entered into data models. The resulted data points and insights were then validated by primary participants.
Based on additional insights from these primary participants, more directional efforts were put into doing secondary research and optimize data models. This process was repeated till all data models used in the study produced similar results (with minimum deviation). This way, this iterative process was able to generate the most accurate market numbers and qualitative insights.
Secondary research
The secondary research sources that are typically mentioned to include, but are not limited to:
The paid sources for secondary research like Factiva, OneSource, Hoovers, and Statista
Primary Research:
Primary research involves telephonic interviews, e-mail interactions, as well as face-to-face interviews for each market, category, segment, and subsegment across geographies
The contributors who typically take part in such a course include, but are not limited to:
Data Modeling and Analysis:
In the iterative process (mentioned above), data models received inputs from primary as well as secondary sources. But analysts working on these models were the key. They used their extensive knowledge and experience about industry and topic to make changes and fine-tuning these models as per the product/service under study.
The standard data models used while studying this market were the top-down and bottom-up approaches and the company shares analysis model. However, other methods were also used along with these – which were specific to the industry and product/service under study.
