Global Artificial Intelligence in Customer Experience Market Size, Share & Trends Analysis Report, by Deployment, By Application, By End User Industry, By Region Forecasts, 2023 - 2030

Global Artificial Intelligence in Customer Experience Market Size, Share & Trends Analysis Report, by Deployment, By Application, By End User Industry, By Region Forecasts, 2023 - 2030



Global Artificial Intelligence in Customer Experience Market was valued at US $ 9.4 Billion in 2022 and is expected to reach US $ 28 Billion by 2030 growing at a CAGR of 14.6% during the forecast period 2023 – 2030.

The application of artificial intelligence technology and solutions to improve and optimise business-customer interactions is the focus of the market for artificial intelligence in customer experience, or AI CX or AI in CX. A vast array of AI-powered solutions, platforms, and applications are available in this sector, all aimed at enhancing different facets of the customer journey, from first interaction to post-purchase support. These AI-driven technologies are designed to help organisations optimise their operations and create enduring customer relationships, all while giving customers more individualised, effective, and gratifying experiences.

One important element driving the rise of AI in the customer experience market is the increase in demand for personalised experiences. Artificial intelligence (AI) technologies have become the solution in a time when consumers want personalised, one-of-a-kind experiences with companies. Businesses may meet these demands in a number of ways by utilising AI's capabilities. In addition to improving client engagement, personalisation fosters customer loyalty, lowers attrition, and raises customer lifetime value. Increased income is the obvious effect of AI's ability to customise content, offers, and product recommendations to match the unique profiles of each consumer, which leads to higher conversion rates. Personalised experiences are crucial because they increase consumer happiness, build brand loyalty, and encourage repeat business. Businesses benefit greatly from the data-driven insights that personalisation provides, since it provides a more profound comprehension of consumer behaviours and preferences. Future decisions about marketing, product development, and customer service are therefore informed by this data, enabling more focused and efficient strategies. Personalisation offers a big advantage as the competitive landscape gets more intense, and companies that are successful in this area will stand out. By finding opportunities based on consumer behaviour and past purchases, the AI-driven personalisation strategy also makes cross-selling and up-selling easier, boosting revenue and profit margins.

“Cloud Based segment, by deployment, to be dominating market from 2023 to 2030.”

With a 56.48% market share, cloud-based solutions are leading the AI in customer experience space and provide scalability, accessibility, cost-effectiveness, simplified maintenance, and seamless integration. Because of these benefits, cloud solutions are now the preferred option for companies looking to improve client experiences and maintain their agility in a market that is changing quickly.

“Customer service segment, by application, to be dominating market from 2023 to 2030.”

With a 28.3% market share, customer service leads the AI in customer experience industry. This is mainly because it provides organisations with cost-effectiveness, scalability, and improved productivity in addition to quick and noticeable changes. Chatbots and virtual assistants, for example, are AI-powered customer support systems that offer prompt responses, manage large quantities of inquiries, and let businesses quickly adjust to changing client needs.

“Retail segment, by end user industry, to be dominating market from 2023 to 2030.”

Because of its inherent customer-centric focus, wealth of data, early use of AI, and fierce competition, retail has a 26.5% market share and leads the AI in customer experience industry. In order to provide individualised shopping experiences, optimise processes, and obtain a competitive advantage in a congested market, the retail industry has embraced AI.

“North America to be largest region in Artificial Intelligence in Customer Experience market.”

Thanks to its early embrace of technology, developed tech ecosystem, and innovative culture, the North America (NA) region leads the world with a 32.4% market share in the AI customer experience industry. With access to significant venture finance, robust government backing, and tech hotspots like Silicon Valley, NA has made a name for itself as a leader in AI development for improving consumer experiences across a range of industries. With a 16.8% CAGR, the Asia-Pacific (APAC) region is, in contrast, the AI customer experience market with the quickest rate of growth. The region's enormous population, growing consumer market, and quickening digital revolution are the main drivers of its amazing growth. APAC is a rich field for AI-driven customer experience solutions because of the region's growing startup environment, government efforts, and rising e-commerce and mobile usage rates. Both areas are crucial in determining how AI is used in customer experiences globally.

Artificial Intelligence in Customer Experience Competitive Landscape

The competitive landscape of the Artificial Intelligence in Customer Experience market involves assessing the competitive landscape to understand the strengths, weaknesses, opportunities, and threats of the industry. Key industry players have recognized that the adoption of Artificial Intelligence in Customer Experience technology holds the potential for further growth. The growing desire among producers to optimize their production costs has spurred collaborative efforts among companies to scale up their production capacity. This strategic collaboration not only aims to increase revenue but also seeks to establish dominance in the market.

The Artificial Intelligence in Customer Experience market is highly competitive, with numerous companies vying for market share. Prominent companies in the Artificial Intelligence in Customer Experience Market include:

IBM, Google, Microsoft, Abode, SAP, Salesforce, Oracle, Avaya, Genesys, Pegasystems, Liveperson, Inmoment, Medallia, Zendesk, Uipath, Freshservices, Satmetrix, NICE, Twilio, Automation Anywhere and others.

Recent developments:

The well-known conversational commerce platform LivePerson debuted its most recent AI-powered chatbot in October 2023 with the goal of helping companies increase customer satisfaction and provide round-the-clock customer care. Using machine learning (ML) and natural language processing (NLP), this chatbot uses LivePerson's Conversational AI platform to understand user intents and provide pertinent answers. It also works in unison with LivePerson's Engagement Cloud platform, giving companies a unified view of their client interactions through all available channels of communication.

Salesforce, a well-known provider of CRM software, unveiled its most recent set of Einstein AI-powered sales and marketing automation solutions in September 2023. These state-of-the-art tools are designed to help organisations increase customer interaction, streamline productivity, and automate repetitive processes. Some of the suite's standout features include Einstein Activity Capture, which updates Salesforce records and records customer interactions automatically; Einstein Sales Insights, which provides insightful data on customer behaviour and sales prospects; and Einstein Marketing Automation, which streamlines marketing campaigns and email outreach by automating them.


1 Introduction Of Global Artificial Intelligence In Customer Experience Market
1.1 Overview Of The Market
1.2 Scope Of Report
1.3 Assumptions
2 Executive Summary
3 Research Methodology
3.1 Data Mining
3.2 Validation
3.3 Primary Interviews
3.4 List Of Data Sources
4 Global Artificial Intelligence In Customer Experience Market Outlook
4.1 Overview
4.2 Market Dynamics
4.2.1 Drivers
4.2.2 Restraints
4.2.3 Opportunities
4.3 Porters Five Force Model
4.3.1. Bargaining Power Of Suppliers
4.3.2. Threat Of New Entrants
4.3.3. Threat Of Substitutes
4.3.4. Competitive Rivalry
4.3.5. Bargaining Power Among Buyers
4.4 Value Chain Analysis
5 Global Artificial Intelligence In Customer Experience Market, By Deployment
5.1 Overview
5.2 On Premise
5.3 Cloud Based
5.4 Hybrid
6 Global Artificial Intelligence In Customer Experience Market, By Application
6.1 Overview
6.2 Customer Service
6.3 Personalized
6.4 Predictive Analytics
6.5 Sentiment Analysis
6.6. Customer Onboarding
6.7 Proactive Issue Resolution
7 Global Artificial Intelligence In Customer Experience Market, By End-user Industry
7.1 Overview
7.2 Retail
7.3 Banking And Financial Services
7.4 Healthcare
7.5 Manufacturing
7.6 Telecommunication
7.7 Travel And Hospitality
8 Global Artificial Intelligence In Customer Experience Market, By Region
8.1 North America
8.1.1 U.S.
8.1.2 Canada
8.2 Europe
8.2.1 Germany
8.2.3 U.K.
8.2.4 France
8.2.5 Rest Of Europe
8.3 Asia Pacific
8.3.1 China
8.3.2 Japan
8.3.3 India
8.3.4 South Korea
8.3.5 Singapore
8.3.6 Malaysia
8.3.7 Australia
8.3.8 Thailand
8.3.9 Indonesia
8.3.10 Philippines
8.3.11 Rest Of Asia Pacific
8.4 Others
8.4.1 Saudi Arabia
8.4.2 U.A.E.
8.4.3 South Africa
8.4.4 Egypt
8.4.5 Israel
8.4.6 Rest Of Middle East And Africa (Mea)
8.4.7 Brazil
8.4.8 Argentina
8.4.9 Mexico
8.4.10 Rest Of South America
9 Company Profiles
9.1 Ibm
9.1.1. Company Overview
9.1.2. Key Executives
9.1.3. Operating Business Segments
9.1.4. Product Portfolio
9.1.5. Financial Performance (As Per Availability)
9.1.6 Key News
9.2 Google
9.2.1. Company Overview
9.2.2. Key Executives
9.2.3. Operating Business Segments
9.2.4. Product Portfolio
9.2.5. Financial Performance (As Per Availability)
9.2.6. Key News
9.3 Microsoft
9.3.1. Company Overview
9.3.2. Key Executives
9.3.3. Operating Business Segments
9.3.4. Product Portfolio
9.3.5. Financial Performance (As Per Availability)
9.3.6. Key News
9.4 Salesforce
9.4.1. Company Overview
9.4.2. Key Executives
9.4.3. Operating Business Segments
9.4.4. Product Portfolio
9.4.5. Financial Performance (As Per Availability)
9.4.6. Key News
9.5 Adobe
9.5.1. Company Overview
9.5.2. Key Executives
9.5.3. Operating Business Segments
9.5.4. Product Portfolio
9.5.5. Financial Performance (As Per Availability)
9.5.6. Key News
9.6 Sap
9.6.1. Company Overview
9.6.2. Key Executives
9.6.3. Operating Business Segments
9.6.4. Product Portfolio
9.6.5. Financial Performance (As Per Availability)
9.6.6. Key News
9.7 Pegasystems
9.7.1. Company Overview
9.7.2. Key Executives
9.7.3. Operating Business Segments
9.7.4. Product Portfolio
9.7.5. Financial Performance (As Per Availability)
9.7.6. Key News
9.8 Oracle
9.8.1. Company Overview
9.8.2. Key Executives
9.8.3. Operating Business Segments
9.8.4. Product Portfolio
9.8.5. Financial Performance (As Per Availability)
9.8.6. Key News
9.9 Avaya
9.9.1. Company Overview
9.9.2. Key Executives
9.9.3. Operating Business Segments
9.9.4. Product Portfolio
9.9.5. Financial Performance (As Per Availability)
9.9.6. Key News
9.10 Geneysy
9.10.1. Company Overview
9.10.2. Key Executives
9.10.3. Operating Business Segments
9.10.4. Product Portfolio
9.10.5. Financial Performance (As Per Availability)
9.10.6. Key News
9.11 Liveperson
9.11.1. Company Overview
9.11.2. Key Executives
9.11.3. Operating Business Segments
9.11.4. Product Portfolio
9.11.5. Financial Performance (As Per Availability)
9.11.6. Key News
9.12 Inmoment
9.12.1. Company Overview
9.12.2. Key Executives
9.12.3. Operating Business Segments
9.12.4. Product Portfolio
9.12.5. Financial Performance (As Per Availability)
9.12.6. Key News
9.13 Medallia
9.13.1. Company Overview
9.13.2. Key Executives
9.13.3. Operating Business Segments
9.13.4. Product Portfolio
9.13.5. Financial Performance (As Per Availability)
9.13.6. Key News
9.14 Satmetrix
9.14.1. Company Overview
9.14.2. Key Executives
9.14.3. Operating Business Segments
9.14.4. Product Portfolio
9.14.5. Financial Performance (As Per Availability)
9.14.6. Key News
9.15 Zendesk
9.15.1. Company Overview
9.15.2. Key Executives
9.15.3. Operating Business Segments
9.15.4. Product Portfolio
9.15.5. Financial Performance (As Per Availability)
9.15.6. Key News
9.16 Freshservice
9.16.1. Company Overview
9.16.2. Key Executives
9.16.3. Operating Business Segments
9.16.4. Product Portfolio
9.16.5. Financial Performance (As Per Availability)
9.16.6. Key News
9.17 Uipath
9.17.1. Company Overview
9.17.2. Key Executives
9.17.3. Operating Business Segments
9.17.4. Product Portfolio
9.17.5. Financial Performance (As Per Availability)
9.17.6. Key News
9.18 Automation Anywhere
9.18.1. Company Overview
9.18.2. Key Executives
9.18.3. Operating Business Segments
9.18.4. Product Portfolio
9.18.5. Financial Performance (As Per Availability)
9.18.6. Key News
9.19 Nice
9.19.1. Company Overview
9.19.2. Key Executives
9.19.3. Operating Business Segments
9.19.4. Product Portfolio
9.19.5. Financial Performance (As Per Availability)
9.19.6. Key News
9.20 Twilio
9.20.1. Company Overview
9.20.2. Key Executives
9.20.3. Operating Business Segments
9.20.4. Product Portfolio
9.20.5. Financial Performance (As Per Availability)
9.20.6. Key News

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