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Global Call Center AI Market By Deployment Type, By End User, By Component, By Regional Outlook, Industry Analysis Report and Forecast, 2021-2027

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    Report

  • 222 Pages
  • January 2022
  • Region: Global
  • Marqual IT Solutions Pvt. Ltd (KBV Research)
  • ID: 5553216
The Global Call Center AI Market size is expected to reach $4.7 billion by 2027, rising at a market growth of 24.3% CAGR during the forecast period.

Call Center AI refers to the utilization of artificial intelligence across call centers with the purpose of providing human-like services to customers with robotic assistance. In call centers, one of the most common uses of AI is to provide in-depth data on call times and first resolution along with other metrics. These technologies can detect patterns and have access to client data, allowing them to determine if customers are having a good or bad experience.

According to a study conducted by Oracle, more than 80% of businesses are now using chatbots for customer service or aim to do so by 2020. Respondents cited 24-hour service, rapid responses to inquiries, and solutions to easy questions as some of the advantages of AI deployment.

There are some instances wherein dealing with customer inquiries in real-time might be a difficult task for a customer service representative, as customers may not understand the context of their inquiry. This has necessitated the development of better data analytics skills.

For example, with AI, previous customer interactions and chat data may be examined in seconds, and concise information about the customer can be supplied to the executive. Because of its large in-house data scientists and analysts, Amazon, in partnership with its subsidiary Amazon Web Services, developed specific algorithms aimed at evaluating consumer wants and offering accurate responses based on those needs. As a result, the global market is growing due to the requirement for increased data analysis skills.



COVID-19 Impact Analysis


In the fourth quarter of 2019, the deadly COVID-19 emerged from the Wuhan City of China and till the end of the first quarter of 2020, it emerged as one of the most deadly and hazardous pandemics for both the people and economies. The COVID-19 caused Governments all over the world to enforce lockdowns across their countries which substantially slammed all the industries across the world. However, due to the increased necessity for organizations to replace old infrastructure to build a more flexible approach to customer engagement during the COVID-19 pandemic, the usage of advanced call center software solutions has surged.

Because call center software use has expanded despite unprecedented circumstances, the COVID-19 pandemic had a positive impact on the expansion of the call center AI market. Enterprises have seen an increase in the requirement to replace old infrastructure in order to build a more agile approach to client engagement.

Market Growth Factors:


Rising demand for enhanced customer experience

Customer experience must be maintained by providing accurate and timely feedback. Customer experience is critical to a company's long-term success. Call center as a service provides solutions that assist in providing appropriate customer support. By delivering real-time customer query-related data, the service assists agents in efficiently handling consumers. It displays information on clients and their buying history in pop-up windows. This saves time for the agent and allows them to rapidly resolve the customer's issue.

Advantages such as Scalability, Flexibility, and reduced cost

Traditional on-premises call centers are substantially more expensive than cloud-based call centers. Companies save money on overall expenses such as hardware installation and maintenance service charges by implementing AI solutions in a call center. Moreover, cloud-based services aid in the reduction of overhead costs, downtime, and power usage. It also offers a pay-per-use subscription model, which allows businesses to choose the plan that best suits their needs and budget. Web-based call centers are becoming more popular among businesses with minimal resources.

Marketing Restraining Factor:


Data security and privacy risks

The Call Center has a large amount of data that is vulnerable to malevolent attackers. Personal and confidential information, such as health information and credit card data, is stored in call centers. Internally and externally, there is a considerable risk of data breaches and hacking. Internally, for example, the agent could leak information or be bribed to provide it. This poses a significant risk of privacy violations. For example, in 2017, a data breach occurred at the LaunchPoint insurance company in the United States, when a corporate employee used his personal email to steal client healthcare information.



Deployment Type Outlook


Based on the Deployment Type, the Call center AI market is bifurcated into Cloud and On-premise. In 2020, the On-premise segment followed the cloud segment by acquiring the second-largest revenue share of the call center AI market. The on-premise deployment ensures data safety by saving all the databases and servers of the call center at the location of the organization.

End User Outlook


Based on the End-user, the Call center AI market is segregated into BFSI, Retail & E-commerce, Telecom, Healthcare, Media & Entertainment, Travel & Hospitality, and Others. In 2020, the retail and E-commerce segment accounted for a promising revenue share of the call center AI market. The increased growth of this segment of the market is attributed to the fact that a lot of stores and supermarkets are adopting the newly introduced method of providing over-the-phone services to their customers. This method offers convenience and an enhanced shopping experience to customers.

Component Outlook


Based on the Component, the Call center AI market is segmented into Solution, Compute platform, and Services. The solution segment accounted for the largest revenue share of the call center AI market in 2020. This is due to the widespread use of chatbots/IVAs in many processes. In comparison to other verticals, the BFSI sector has the highest rate of adoption of call center platforms and solutions. Call center AI solutions to help financial organizations interact with consumers perfectly, improve customer experience, and reduce response time, all while enhancing overall efficiency. This is the factor driving the growth of this segment.

Regional Outlook


Based on the Region, the Call center AI market is analyzed across North America, Europe, APAC, and LAMEA. In 2020, North America led the call center AI market by accounting for the largest revenue share of the market across the world. In addition, the increasing growth for the market in this region is attributed to the ongoing growth in call center solutions spending across the United States and Canada. Moreover, the widespread adoption of call center AI solutions in sectors such as BFSI, healthcare, retail, and government to deliver exceptional customer service is expected to further boost the growth of the regional call center AI market during the forecasting period.

Cardinal Matrix - Call Center AI Market Competition Analysis




The major strategies followed by the market participants are Product Launches. Based on the Analysis presented in the Cardinal matrix; Reliance Industries Limited (Jio Haptik technologies limited) are the forerunners in the Call Center AI Market. Companies such as Infosys Limited (EdgeVerve Systems), NICE Ltd. (inContact, Inc.), Conversica, Inc. are some of the key innovators in the Market.

The market research report covers the analysis of key stake holders of the market. Key companies profiled in the report include Reliance Industries Limited (Jio Haptik technologies limited), Artificial Solutions International AB, Conversica, Inc., Rulai, Inc., Kore.ai, Inc., Pypestream, Inc., Infosys Limited (EdgeVerve Systems), Avaamo, Inc., and NICE Ltd. (inContact, Inc.).

Recent Strategies Deployed in Agricultural Ventilation Fans Market


» Partnerships, Collaborations and Agreements:

  • Oct-2021: Conversica partnered with CDK Global, the largest provider of automotive dealership solutions for auto dealers. The partnership aimed to offer dealerships a competitive advantage in the ability to scale consumer communication by integrating Converica's Automotive Sales Conversational Artificial Intelligence (AI) Assistants with CDK's Elead customer relationship management (CRM).
  • Aug-2021: Artificial Solutions extended its collaboration with Circle K, an international chain of convenience stores. Through this extended collaboration, the companies aimed to continue to provide support for consumers & employees of the convenience retail outlets of Circle K in the US & Scandinavia.
  • Jul-2021: Artificial Solutions along with its partner Microsoft joined hands with A1 Bulgaria, the GSM mobile phone operator in the country. Through this collaboration, A1 Bulgaria is expected to deploy a range of conversational applications in the company's consumer service with LUIS^Teneo, Artificial Solutions' cloud-based integrated development environment for Microsoft LUIS’ consumers.
  • Mar-2021: Infosys partnered with LivePerson, a global leader in Conversational AI. The partnership aimed to help brands manage AI-powered conversations with customers & employees over SMS, apps, websites, & messaging channels for everyday use and also enable the companies to grow.
  • Sep-2020: Pypestream came into partnership with Conviva, the leader in global streaming media intelligence. Through this partnership, the companies aimed to deliver proactive consumer experiences within digital conversational experiences through notifications, eliminating the requirement of consumers to reactively call or email a call center and also help Pypestream in delivering true AI-driven consumer experiences which help a business’s bottom line by exceeding customer expectations. In addition, Sling TV use the feature to provide consumers with smart self-service solutions & always-on conversational brand experiences.
  • Aug-2020: Infosys came into partnership with Genesys, a global leader in cloud customer experience and contact center solutions. This partnership is expected to improve & expand the consumer experience and contact center offerings of both organizations.
  • Jun-2020: Conversica extended its existing partnership with AutoAlert, an automotive software company. Under this partnership, AutoAlert is expected to offer full capabilities & skills for the Conversica Automotive Sales AI Assistant & Conversica and help in boosting sales as well as service revenue. This partnership aimed to deliver an integrated platform that is expected to provide an improved consumer experience.

» Product Launches and Product Expansions:

  • Nov-2021: Conversica introduced Conversational Account-Based Marketing (ABM) capabilities. The ABM solution is available through the company's AI Assistants. The launch is aimed to automate personalized outreach across SMS, website chat, and emails.
  • Oct-2021: Kore.ai released SmartAssist, an AI-native end-to-end Contact Center as-a-Service (CCaaS) solution. The SmartAssist aimed to help live agents understand past history/context, and an intuitive desktop console which allows agents to easily manage conversations. Also, SmartAssist focuses on accurately responding to the most sophisticated conversations across voice or digital channels, automatically escalating conversations to live agents with seamless contextual continuity to move conversations forward towards successful outcomes.
  • Sep-2021: Kore.ai launched SmartAssist, the world’s first AI-native end-to-end Contact Center as-a-Service [CCaaS] solution. This solution comes integrated with the AgentAssist aimed to help live agents understand past history/context along with an intuitive desktop console that enables agents to easily manage conversations.
  • Sep-2021: EdgeVerve Systems launched AssistEdge 19.0, latest version of the company's automation platform. The latest version is designed to support and scale large process automation programs for global enterprises.
  • Sep-2021: Kore.ai unveiled BankAssist, an omni-channel conversational virtual assistant. BankAssist is expected to help to automate highly accurate natural conversations with maximum containment to drive extraordinary consumer experiences by voice and other digital channels.
  • May-2021: Reliance Industries introduced AI-enabled WhatsApp chatbox, American freeware, cross-platform centralized instant messaging (IM) and voice-over-IP (VoIP) service. The new AI chatbox is the first one rolled out for a public offering developed by Jio Haptik Technologies which is expected to answer shareholders' queries on the Rs 53,125 crore rights issue. The launch is aimed to assist investors in the Indian stock markets for the first time.
  • May-2021: NICE introduced InterACT, a new AI-powered recording solution. InterACT is expected to automate end-to-end recording decisioning processes, dramatically reducing manual configurations, saving time and decreasing human errors. Through this, the company is expected to transform the way contact centers manage interaction recording.
  • Mar-2021: Pypestream unveiled Customer Engagement Center (CEC), a cloud-based solution. The CEC is expected to help consumers to interact with the company on any device, anytime directly. In addition, the CEC automates all consumer interactions & escalates to services such as Amazon Connect, the omnichannel cloud contact center from AWS.
  • Mar-2021: Talkdesk introduced Talkdesk AI Trainer, the first human-in-the-loop (HITL) tool for contact centers. Through this launch, the company is expected to improve accuracy and increase consumer satisfaction as well as decrease the cost per case.
  • Mar-2021: NICE inContact introduced new capabilities in its exsisting product CXone. The product is expected to be first-of-its-kind artificial intelligence (AI) innovations with Real-Time Interaction Guidance for agents. Through this, the company aimed to expand its self-service capabilities, extend digital-first reach, and empower highly effective work-from-anywhere teams.
  • Jan-2021: Infosys introduced Infosys Cortex, a customer engagement platform. The launch of Cortex is focused on leveraging technology from Genesys along with Contact Center AI services from Google Cloud and Infosys's managed artificial intelligence (AI) & analytics services.
  • Oct-2020: Conversica launched Intelligent Virtual Assistants (IVAs). The IVAs is expected to engage with website visitors & quickly connect them to the information visitors seek through chat, use email & SMS aimed to nurture them by a qualification process & pass hot qualified opportunities to consumer-facing teams along with delivering a personalized experience which digital natives now demand across multiple channels.

Scope of the Study


Market Segments Covered in the Report:


By Deployment Type

  • Cloud
  • On-Premise

By End User

  • Telecom
  • BFSI
  • Travel & Hospitality
  • Retail & Ecommerce
  • Media & Entertainment
  • Healthcare
  • Others

By Component

  • Solution
  • Compute Platforms
  • Services

By Geography


  • North America
  • US
  • Canada
  • Mexico
  • Rest of North America
  • Europe
  • Germany
  • UK
  • France
  • Russia
  • Spain
  • Italy
  • Rest of Europe
  • Asia Pacific
  • China
  • Japan
  • India
  • South Korea
  • Singapore
  • Malaysia
  • Rest of Asia Pacific
  • LAMEA
  • Brazil
  • Argentina
  • UAE
  • Saudi Arabia
  • South Africa
  • Nigeria
  • Rest of LAMEA

Key Market Players


List of Companies Profiled in the Report:

  • Reliance Industries Limited (Jio Haptik technologies limited)
  • Artificial Solutions International AB
  • Conversica, Inc.
  • Rulai, Inc.
  • Kore.ai, Inc.
  • Pypestream, Inc.
  • Infosys Limited (EdgeVerve Systems)
  • Avaamo, Inc.
  • NICE Ltd. (inContact, Inc.)

Unique Offerings from the Publisher

  • Exhaustive coverage
  • The highest number of market tables and figures
  • Subscription-based model available
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  • Assured post sales research support with 10% customization free

Table of Contents

Chapter 1. Market Scope & Methodology
1.1 Market Definition
1.2 Objectives
1.3 Market Scope
1.4 Segmentation
1.4.1 Global Call Center AI Market, by Deployment Type
1.4.2 Global Call Center AI Market, by End User
1.4.3 Global Call Center AI Market, by Component
1.4.4 Global Call Center AI Market, by Geography
1.5 Methodology for the research
Chapter 2. Market Overview
2.1 Introduction
2.1.1 Overview
2.1.1.1 Market Composition and Scenario
2.2 Key Factors Impacting the Market
2.2.1 Market Drivers
2.2.2 Market Restraints
Chapter 3. Competition Analysis - Global
3.1 Cardinal Matrix
3.2 Recent Industry Wide Strategic Developments
3.2.1 Partnerships, Collaborations and Agreements
3.2.2 Product Launches and Product Expansions
3.3 Top Winning Strategies
3.3.1 Key Leading Strategies: Percentage Distribution (2017-2021)
3.3.2 Key Strategic Move: (Product Launches and Product Expansions 2020, Oct - 2021, Nov) Leading Players
Chapter 4. Global Call Center AI Market by Deployment Type
4.1 Global Cloud Market by Region
4.2 Global On-premise Market by Region
Chapter 5. Global Call Center AI Market by End User
5.1 Global Telecom Market by Region
5.2 Global BFSI Market by Region
5.3 Global Travel & Hospitality Market by Region
5.4 Global Retail & Ecommerce Market by Region
5.5 Global Media & Entertainment Market by Region
5.6 Global Healthcare Market by Region
5.7 Global Other End User Market by Region
Chapter 6. Global Call Center AI Market by Component
6.1 Global Solution Market by Region
6.2 Global Compute Platforms Market by Region
6.3 Global Services Market by Region
Chapter 7. Global Call Center AI Market by Region
7.1 North America Call Center AI Market
7.1.1 North America Call Center AI Market by Deployment Type
7.1.1.1 North America Cloud Market by Country
7.1.1.2 North America On-premise Market by Country
7.1.2 North America Call Center AI Market by End User
7.1.2.1 North America Telecom Market by Country
7.1.2.2 North America BFSI Market by Country
7.1.2.3 North America Travel & Hospitality Market by Country
7.1.2.4 North America Retail & Ecommerce Market by Country
7.1.2.5 North America Media & Entertainment Market by Country
7.1.2.6 North America Healthcare Market by Country
7.1.2.7 North America Other End User Market by Country
7.1.3 North America Call Center AI Market by Component
7.1.3.1 North America Solution Market by Country
7.1.3.2 North America Compute Platforms Market by Country
7.1.3.3 North America Services Market by Country
7.1.4 North America Call Center AI Market by Country
7.1.4.1 US Call Center AI Market
7.1.4.1.1 US Call Center AI Market by Deployment Type
7.1.4.1.2 US Call Center AI Market by End User
7.1.4.1.3 US Call Center AI Market by Component
7.1.4.2 Canada Call Center AI Market
7.1.4.2.1 Canada Call Center AI Market by Deployment Type
7.1.4.2.2 Canada Call Center AI Market by End User
7.1.4.2.3 Canada Call Center AI Market by Component
7.1.4.3 Mexico Call Center AI Market
7.1.4.3.1 Mexico Call Center AI Market by Deployment Type
7.1.4.3.2 Mexico Call Center AI Market by End User
7.1.4.3.3 Mexico Call Center AI Market by Component
7.1.4.4 Rest of North America Call Center AI Market
7.1.4.4.1 Rest of North America Call Center AI Market by Deployment Type
7.1.4.4.2 Rest of North America Call Center AI Market by End User
7.1.4.4.3 Rest of North America Call Center AI Market by Component
7.2 Europe Call Center AI Market
7.2.1 Europe Call Center AI Market by Deployment Type
7.2.1.1 Europe Cloud Market by Country
7.2.1.2 Europe On-premise Market by Country
7.2.2 Europe Call Center AI Market by End User
7.2.2.1 Europe Telecom Market by Country
7.2.2.2 Europe BFSI Market by Country
7.2.2.3 Europe Travel & Hospitality Market by Country
7.2.2.4 Europe Retail & Ecommerce Market by Country
7.2.2.5 Europe Media & Entertainment Market by Country
7.2.2.6 Europe Healthcare Market by Country
7.2.2.7 Europe Other End User Market by Country
7.2.3 Europe Call Center AI Market by Component
7.2.3.1 Europe Solution Market by Country
7.2.3.2 Europe Compute Platforms Market by Country
7.2.3.3 Europe Services Market by Country
7.2.4 Europe Call Center AI Market by Country
7.2.4.1 Germany Call Center AI Market
7.2.4.1.1 Germany Call Center AI Market by Deployment Type
7.2.4.1.2 Germany Call Center AI Market by End User
7.2.4.1.3 Germany Call Center AI Market by Component
7.2.4.2 UK Call Center AI Market
7.2.4.2.1 UK Call Center AI Market by Deployment Type
7.2.4.2.2 UK Call Center AI Market by End User
7.2.4.2.3 UK Call Center AI Market by Component
7.2.4.3 France Call Center AI Market
7.2.4.3.1 France Call Center AI Market by Deployment Type
7.2.4.3.2 France Call Center AI Market by End User
7.2.4.3.3 France Call Center AI Market by Component
7.2.4.4 Russia Call Center AI Market
7.2.4.4.1 Russia Call Center AI Market by Deployment Type
7.2.4.4.2 Russia Call Center AI Market by End User
7.2.4.4.3 Russia Call Center AI Market by Component
7.2.4.5 Spain Call Center AI Market
7.2.4.5.1 Spain Call Center AI Market by Deployment Type
7.2.4.5.2 Spain Call Center AI Market by End User
7.2.4.5.3 Spain Call Center AI Market by Component
7.2.4.6 Italy Call Center AI Market
7.2.4.6.1 Italy Call Center AI Market by Deployment Type
7.2.4.6.2 Italy Call Center AI Market by End User
7.2.4.6.3 Italy Call Center AI Market by Component
7.2.4.7 Rest of Europe Call Center AI Market
7.2.4.7.1 Rest of Europe Call Center AI Market by Deployment Type
7.2.4.7.2 Rest of Europe Call Center AI Market by End User
7.2.4.7.3 Rest of Europe Call Center AI Market by Component
7.3 Asia Pacific Call Center AI Market
7.3.1 Asia Pacific Call Center AI Market by Deployment Type
7.3.1.1 Asia Pacific Cloud Market by Country
7.3.1.2 Asia Pacific On-premise Market by Country
7.3.2 Asia Pacific Call Center AI Market by End User
7.3.2.1 Asia Pacific Telecom Market by Country
7.3.2.2 Asia Pacific BFSI Market by Country
7.3.2.3 Asia Pacific Travel & Hospitality Market by Country
7.3.2.4 Asia Pacific Retail & Ecommerce Market by Country
7.3.2.5 Asia Pacific Media & Entertainment Market by Country
7.3.2.6 Asia Pacific Healthcare Market by Country
7.3.2.7 Asia Pacific Other End User Market by Country
7.3.3 Asia Pacific Call Center AI Market by Component
7.3.3.1 Asia Pacific Solution Market by Country
7.3.3.2 Asia Pacific Compute Platforms Market by Country
7.3.3.3 Asia Pacific Services Market by Country
7.3.4 Asia Pacific Call Center AI Market by Country
7.3.4.1 China Call Center AI Market
7.3.4.1.1 China Call Center AI Market by Deployment Type
7.3.4.1.2 China Call Center AI Market by End User
7.3.4.1.3 China Call Center AI Market by Component
7.3.4.2 Japan Call Center AI Market
7.3.4.2.1 Japan Call Center AI Market by Deployment Type
7.3.4.2.2 Japan Call Center AI Market by End User
7.3.4.2.3 Japan Call Center AI Market by Component
7.3.4.3 India Call Center AI Market
7.3.4.3.1 India Call Center AI Market by Deployment Type
7.3.4.3.2 India Call Center AI Market by End User
7.3.4.3.3 India Call Center AI Market by Component
7.3.4.4 South Korea Call Center AI Market
7.3.4.4.1 South Korea Call Center AI Market by Deployment Type
7.3.4.4.2 South Korea Call Center AI Market by End User
7.3.4.4.3 South Korea Call Center AI Market by Component
7.3.4.5 Singapore Call Center AI Market
7.3.4.5.1 Singapore Call Center AI Market by Deployment Type
7.3.4.5.2 Singapore Call Center AI Market by End User
7.3.4.5.3 Singapore Call Center AI Market by Component
7.3.4.6 Malaysia Call Center AI Market
7.3.4.6.1 Malaysia Call Center AI Market by Deployment Type
7.3.4.6.2 Malaysia Call Center AI Market by End User
7.3.4.6.3 Malaysia Call Center AI Market by Component
7.3.4.7 Rest of Asia Pacific Call Center AI Market
7.3.4.7.1 Rest of Asia Pacific Call Center AI Market by Deployment Type
7.3.4.7.2 Rest of Asia Pacific Call Center AI Market by End User
7.3.4.7.3 Rest of Asia Pacific Call Center AI Market by Component
7.4 LAMEA Call Center AI Market
7.4.1 LAMEA Call Center AI Market by Deployment Type
7.4.1.1 LAMEA Cloud Market by Country
7.4.1.2 LAMEA On-premise Market by Country
7.4.2 LAMEA Call Center AI Market by End User
7.4.2.1 LAMEA Telecom Market by Country
7.4.2.2 LAMEA BFSI Market by Country
7.4.2.3 LAMEA Travel & Hospitality Market by Country
7.4.2.4 LAMEA Retail & Ecommerce Market by Country
7.4.2.5 LAMEA Media & Entertainment Market by Country
7.4.2.6 LAMEA Healthcare Market by Country
7.4.2.7 LAMEA Other End User Market by Country
7.4.3 LAMEA Call Center AI Market by Component
7.4.3.1 LAMEA Solution Market by Country
7.4.3.2 LAMEA Compute Platforms Market by Country
7.4.3.3 LAMEA Services Market by Country
7.4.4 LAMEA Call Center AI Market by Country
7.4.4.1 Brazil Call Center AI Market
7.4.4.1.1 Brazil Call Center AI Market by Deployment Type
7.4.4.1.2 Brazil Call Center AI Market by End User
7.4.4.1.3 Brazil Call Center AI Market by Component
7.4.4.2 Argentina Call Center AI Market
7.4.4.2.1 Argentina Call Center AI Market by Deployment Type
7.4.4.2.2 Argentina Call Center AI Market by End User
7.4.4.2.3 Argentina Call Center AI Market by Component
7.4.4.3 UAE Call Center AI Market
7.4.4.3.1 UAE Call Center AI Market by Deployment Type
7.4.4.3.2 UAE Call Center AI Market by End User
7.4.4.3.3 UAE Call Center AI Market by Component
7.4.4.4 Saudi Arabia Call Center AI Market
7.4.4.4.1 Saudi Arabia Call Center AI Market by Deployment Type
7.4.4.4.2 Saudi Arabia Call Center AI Market by End User
7.4.4.4.3 Saudi Arabia Call Center AI Market by Component
7.4.4.5 South Africa Call Center AI Market
7.4.4.5.1 South Africa Call Center AI Market by Deployment Type
7.4.4.5.2 South Africa Call Center AI Market by End User
7.4.4.5.3 South Africa Call Center AI Market by Component
7.4.4.6 Nigeria Call Center AI Market
7.4.4.6.1 Nigeria Call Center AI Market by Deployment Type
7.4.4.6.2 Nigeria Call Center AI Market by End User
7.4.4.6.3 Nigeria Call Center AI Market by Component
7.4.4.7 Rest of LAMEA Call Center AI Market
7.4.4.7.1 Rest of LAMEA Call Center AI Market by Deployment Type
7.4.4.7.2 Rest of LAMEA Call Center AI Market by End User
7.4.4.7.3 Rest of LAMEA Call Center AI Market by Component
Chapter 8. Company Profiles
8.1 Reliance Industries Limited (Jio Haptik technologies limited)
8.1.1 Company Overview
8.1.2 Financial Analysis
8.1.3 Segmental Analysis
8.1.4 Research & Development Expenses
8.1.5 Recent strategies and developments
8.1.5.1 Product Launches and Product Expansions
8.2 Artificial Solutions International AB
8.2.1 Company Overview
8.2.2 Recent strategies and developments
8.2.2.1 Partnerships, Collaborations, and Agreements
8.3 Conversica, Inc.
8.3.1 Company Overview
8.3.2 Recent strategies and developments
8.3.2.1 Partnerships, Collaborations, and Agreements
8.3.2.2 Product Launches and Product Expansions
8.4 Rulai, Inc.
8.4.1 Company Overview
8.5 Kore.ai, Inc.
8.5.1 Company Overview
8.5.2 Recent strategies and developments
8.5.2.1 Product Launches and Product Expansions
8.6 Pypestream, Inc.
8.6.1 Company Overview
8.6.2 Recent strategies and developments
8.6.2.1 Partnerships, Collaborations, and Agreements
8.6.2.2 Product Launches and Product Expansions
8.7 Infosys Limited (EdgeVerve Systems)
8.7.1 Company Overview
8.7.2 Financial Analysis
8.7.3 Segmental and Regional Analysis
8.7.4 Research & Development Expense
8.7.5 Recent strategies and developments
8.7.5.1 Partnerships, Collaborations, and Agreements
8.7.5.2 Product Launches and Product Expansions
8.7.6 SWOT Analysis
8.8 Avaamo, Inc.
8.8.1 Company Overview
8.9 Talkdesk
8.9.1 Company Overview
8.9.2 Recent strategies and developments
8.9.2.1 Product Launches and Product Expansions
8.10. NICE Ltd. (inContact, Inc.)
8.10.1 Company Overview
8.10.2 Financial Analysis
8.10.3 Segmental and Regional Analysis
8.10.4 Research & Development Expenses
8.10.5 Recent strategies and developments
8.10.5.1 Partnerships, Collaborations, and Agreements
8.10.5.2 Product Launches and Product Expansions

Companies Mentioned

  • Reliance Industries Limited (Jio Haptik technologies limited)
  • Artificial Solutions International AB
  • Conversica, Inc.
  • Rulai, Inc.
  • Kore.ai, Inc.
  • Pypestream, Inc.
  • Infosys Limited (EdgeVerve Systems)
  • Avaamo, Inc.
  • NICE Ltd. (inContact, Inc.)

Methodology

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