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The call center artificial intelligence market size is forecast to increase by USD 4.30 billion and is estimated to grow at a CAGR of 27.17% between 2023 and 2028. In today's business landscape, the shift towards cloud-based call center solutions has become a necessity for organizations seeking to enhance customer engagement and streamline operations. This transition enables businesses to leverage advanced features, such as real-time analytics and automated call distribution, to improve customer experience and drive revenue growth. Additionally, the importance of effective CRM systems cannot be overstated, as they provide valuable insights into customer behavior and preferences, enabling personalized engagement and targeted marketing efforts. Furthermore, the increasing demand for self-service options through web channels underscores the need for seamless integration between call center solutions and web platforms, ensuring a consistent and efficient customer journey across all touchpoints.
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The market is witnessing significant growth due to the increasing adoption of AI-centric solutions in various industries. Omnichannel engagement platforms that integrate AI technologies like chatbots, voice analysis software, Interactive Voice Response (IVR), and Intelligent Virtual Assistants (IVAs) are becoming increasingly popular. These solutions help in automating routine tasks, improving customer experience, and ensuring compliance with industry regulations. Service providers are leveraging machine learning algorithms and automation to offer advanced AI solutions. Telecommunications, banking, healthcare, financial services, and insurance sectors are major contributors to the market growth. Emotion Research Lab's Anthropic PBC is an example of AI being used to analyze customer emotions and improve engagement. The market can be segmented into on-premises deployment and cloud segment. Large enterprises are leading the adoption of AI in call centers due to their size and resources. Small and medium enterprises are also adopting AI solutions to stay competitive. The IT and telecom industries are expected to show the highest growth in the market. Quality assurance technology is another area where AI is being used to improve call center operations by analyzing customer interactions and providing real-time feedback to agents. Overall, the market is poised for continued growth in the coming years. Our researchers analyzed the data with 2023 as the base year, along with the key drivers, trends, and challenges. A holistic analysis of drivers will help companies refine their marketing strategies to gain a competitive advantage.
Rising adoption of cloud-based call centers is notably driving market growth. The call center industry is witnessing a significant shift towards AI-centric solutions as businesses aim to enhance customer engagement and streamline operations. Omnichannel engagement platforms are gaining popularity, integrating chatbots, voice analysis software, Interactive Voice Response (IVR) systems, and Intelligent Virtual Assistants (IVAs) to provide seamless customer experiences. AI technologies, such as machine learning and generative AI, are being employed to develop advanced virtual agents for predictive call routing, journey orchestration, and sentiment analysis.
Moreover, service providers are offering AI-enabled solutions to cater to various sectors, including telecommunications, banking, healthcare, financial services, and insurance. Emotion Research Lab's anthropic PBC technology is being used to analyze customer emotions and improve quality assurance. Thus, such factors are driving the growth of the market during the forecast period.
Integration of chatbots for better turnaround times is the key trend in the market. In today's business landscape, providing exceptional call center service is crucial for customer retention and loyalty. However, human agents may not always be able to provide immediate responses due to the need to retrieve relevant data or handle complex queries. This delay can lead to dissatisfied customers seeking alternatives or turning to competitors.
Moreover, to address this challenge, call centers are increasingly adopting AI-centric solutions, such as chatbots, voice analysis software, Interactive Voice Response (IVR) systems, and Intelligent Virtual Assistants (IVAs). These AI-enabled tools offer numerous benefits, including predictive call routing, journey orchestration, sentiment analysis, workforce management, advanced scheduling, and quality management. Thus, such trends will shape the growth of the market during the forecast period.
Integration issues between front-end and back-end knowledge bases is the major challenge that affects the growth of the market. The integration of Artificial Intelligence (AI) in call centers is revolutionizing the way businesses engage with their customers across various industry sectors such as telecommunications, banking, healthcare, and financial services. Omnichannel engagement platforms are becoming increasingly AI-centric, integrating chatbots, voice analysis software, Interactive Voice Response (IVR) systems, and Intelligent Virtual Assistants (IVAs).
However, the adoption of these advanced AI technologies poses challenges in terms of system integration and interoperability. To address these challenges, service providers are offering control compliance suites and quality assurance technology to ensure seamless integration of AI-enabled solutions with existing IT infrastructure. Hence, the above factors will impede the growth of the market during the forecast period.
The market forecasting report includes the adoption lifecycle of the market, covering from the innovator’s stage to the laggard’s stage. It focuses on adoption rates in different regions based on penetration. Furthermore, the report also includes key purchase criteria and drivers of price sensitivity to help companies evaluate and develop their market growth analysis strategies.
Customer Landscape
Companies are implementing various strategies, such as strategic alliances, partnerships, mergers and acquisitions, geographical expansion, and product/service launches, to enhance their presence in the market.
Alphabet Inc: The company offers call center AI solutions with free human agents to focus on more difficult and specialized calls, providing them with real-time information, workflows, and turn-by-turn guidance.
The market research and growth report also includes detailed analyses of the competitive landscape of the market and information about key companies, including:
Qualitative and quantitative analysis of companies has been conducted to help clients understand the wider business environment as well as the strengths and weaknesses of key market players. Data is qualitatively analyzed to categorize companies as pure play, category-focused, industry-focused, and diversified; it is quantitatively analyzed to categorize companies as dominant, leading, strong, tentative, and weak.
The BFSI segment is estimated to witness significant growth during the forecast period. The market is witnessing significant growth as businesses increasingly adopt AI-centric omnichannel engagement platforms to enhance customer experience.
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The BFSI segment was the largest segment and valued at USD 281.10 million in 2018. These platforms incorporate advanced technologies such as control compliance suites, quality assurance technology, and AI-powered chatbots, voice analysis software, Interactive Voice Response (IVR) systems, and Intelligent Virtual Assistants (IVAs). Anthropic PBC, Emotion Research Lab, and various other service providers offer AI-enabled solutions, including machine learning and automation, to improve call center efficiency and productivity. Hence, such factors are fuelling the growth of this segment during the forecast period.
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APAC is estimated to contribute 36% to the growth of the global market during the forecast period. Technavio’s analysts have elaborately explained the regional trends and drivers that shape the market during the forecast period. Artificial Intelligence (AI) in call centers is revolutionizing customer engagement by automating repetitive tasks and enhancing human interactions. Two primary deployment models exist: Cloud-based and On-premise. Large enterprises often prefer Cloud-based AI solutions due to their scalability and cost-effectiveness. Medium enterprises, however, may opt for On-premise deployment for greater control over data security and customization. Natural Language Processing (NLP) is a crucial component of call center AI, enabling efficient call routing, sentiment analysis, and speech recognition. Both deployment models offer unique advantages, and the choice between them depends on an organization's specific needs and resources. Hence, such factors are fuelling the growth of this segment during the forecast period.
The market research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in "USD billion " for the period 2024-2028, as well as historical data from 2018 - 2022 for the following segments.
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The market is rapidly evolving with advancements in AI technology, particularly in enhancing customer service functions across various sectors including retail, consumer goods, IT, telecom, and energy industries. Security and privacy remain critical with stringent measures in place for data ownership, Personally Identifiable Information (PII), and Privacy Impact Assessments (PIAs) to mitigate risks such as data breaches and hacking incidents. The market offers solutions across different deployment models including on-premises and cloud-based services, catering to diverse needs in the travel, hospitality, and logistics sectors. As AI continues to advance, call center AI vendors are focusing on enhancing AI capabilities in handling technical network issues and providing real-time call analytics. This ensures efficient management of customer inquiries and supports the digital transformation of contact centers into agile, data-driven hubs for customer engagement.
AI-powered chatbots and autonomous virtual agents are transforming traditional call centers by automating repetitive tasks and providing hyper-customized customer experiences through omnichannel solutions. Key trends in the market include the integration of AI and machine learning technologies for predictive call routing and unsupervised self-learning capabilities. This allows AI-enabled chatbots to handle complex queries with emotional intelligence and conversational AI, mimicking human-like interactions. The market landscape depends on the Call center AI vendor, AI and ML technologies, IT and telecom sector, Retail sector, Privacy Impact Assessment, Solutions segment, Services segment, On premises segment, Cloud deployment segment, Predictive call routing segment, Large scale enterprises segment, Call center AI market , e-commerce segment, IT and telecommunication industry, Energy industry, AI enabled chatbots, Transportation and logistics sector, unsupervised self learning, control compliance suite, hyper customized customer experience, on premise Call Center AI, call center as a service, travel and hospitality industry. Large-scale enterprises are adopting AI platforms to optimize customer interactions and streamline operations, leveraging historic data and predictive analytics for cross-selling and upselling opportunities.
The market is undergoing a transformative shift with the integration of AI and machine learning (ML) technologies into customer service operations across various sectors. Social media platforms, transportation, logistics, retail, consumer goods, IT, telecom, energy, and travel industries are adopting AI-powered chatbots and AI-enabled solutions to streamline customer queries and enhance the customer service function. AI-powered chatbots are replacing traditional human sales reps and call center agents in handling customer interactions, optimizing cross-selling and upselling opportunities through hyper-customized customer experiences. These technologies automate repetitive and manual processes, leveraging AI and ML capabilities for predictive call routing and unsupervised self-learning. They are deployed via cloud computing services or on-premises models, ensuring scalability and flexibility for large-scale enterprises and e-commerce segments alike. Security measures, including Privacy Impact Assessments (PIAs) and control compliance suites, are implemented to safeguard Personally Identifiable Information (PII) in compliance with regulations. The AI platform model supports data analytics skills for real-time insights and decision-making, catering to the dynamic needs of the IT, telecom, and energy industries. Overall, the market continues to evolve with advancements in technology, offering comprehensive solutions and services that enhance operational efficiency and customer satisfaction across diverse sectors.
Market Scope |
|
Report Coverage |
Details |
Page number |
189 |
Base year |
2023 |
Historic period |
2018 - 2022 |
Forecast period |
2024-2028 |
Growth momentum & CAGR |
Accelerate at a CAGR of 27.17% |
Market growth 2024-2028 |
USD 4.3 billion |
Market structure |
Fragmented |
YoY growth 2023-2024(%) |
20.98 |
Regional analysis |
North America, APAC, Europe, South America, and Middle East and Africa |
Performing market contribution |
APAC at 36% |
Key countries |
US, China, UK, Germany, and Japan |
Competitive landscape |
Leading Companies, Market Positioning of Companies, Competitive Strategies, and Industry Risks |
Key companies profiled |
Alphabet Inc., Amazon.com Inc., Artificial Solutions International AB, Avaamo Inc., Avaya LLC, Conversica Inc., Creative Virtual Ltd., EdgeVerve Systems Ltd., Inbenta Holdings Inc., Jio Haptik Technologies Ltd., Kore.ai Inc., Microsoft Corp., NICE Ltd., Nuance Communications Inc., Oracle Corp., Pypestream Inc., Rulai, SAP SE, Talkdesk Inc., and Zendesk Inc. |
Market dynamics |
Parent market analysis, market report , market forecast , Market growth inducers and obstacles, Fast-growing and slow-growing segment analysis, COVID-19 impact and recovery analysis and future consumer dynamics, Market condition analysis for forecast period |
Customization purview |
If our report has not included the data that you are looking for, you can reach out to our analysts and get segments customized. |
1 Executive Summary
2 Market Landscape
3 Market Sizing
4 Historic Market Size
5 Five Forces Analysis
6 Market Segmentation by End-user
7 Market Segmentation by Channel
8 Customer Landscape
9 Geographic Landscape
10 Drivers, Challenges, and Opportunity/Restraints
11 Competitive Landscape
12 Competitive Analysis
13 Appendix
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